Everlaw

AI Helps Palo Alto Networks Legal Move at the Speed of Commerce

2026-04-26T08:35:44Z

AI Helps Palo Alto Networks Legal Move at the Speed of Commerce

AGC Hayden Creque shares insights on leadership in the age of AI, plus actionable legal prompting tips

by Petra Pasternak

Reading Time — 7 minutes

April 21, 2026

Survey after survey shows generative AI adoption growing among legal professionals. In-house teams are experimenting to find the best use cases and moving beyond pilots to practical application. Some are even building their own bots.

Hayden Creque, Assistant General Counsel for Sourcing and Operations at leading cybersecurity company Palo Alto Networks, heads up a five-person global procurement legal team and oversees more than $500 million in annual transaction volume. He uses GenAI daily in his work, and the team is experimenting with Agentic AI.

Like most in-house professionals, Creque is responding to pressure for speed and doing more with less in a fast-moving and increasingly complex regulatory, business, and tech environment. GenAI tools can be powerful assistants that help shave substantial time off rote tasks, he says, including triaging contracts, synthesizing complex regulatory updates, and drafting routine correspondence.

Creque sat down with Everlaw to discuss the leadership qualities needed to create a culture of innovation, and why making space for failure is crucial. He says GenAI can help move legal pros from a drafting role into a consultative one – with transformative results. And he shares practical tips for how to get started.

The most valuable asset for a modern lawyer isn’t a library of static prompts, he says, but the engineering mindset required to build them.

Hayden Creque, AGC, Palo Alto Networks

You’re an enthusiastic GenAI user. How did you get started and how do you use these tools in your personal life?

I have always been technology curious and Palo Alto Networks incentivized that curiosity. Our CEO rolled out an AI challenge. That served as a catalyst. I found in my personal life I could use AI to generate a website for my side-hustle. I do voiceover work occasionally. My niece loves to write and I fed her stories into the AI to generate comic books for her.

Where is GenAI helpful in your legal practice?

I’ve learned that if you’re still drafting from a blank page, you’re already behind. Even a generic AI tool can make a practice more efficient. I no longer build presentations or documents like contract amendments, statements of work, or correspondence from scratch. Instead, I feed the base materials into AI to generate about 95% of the initial output.

I never treat its output as a final product, but it saves considerable time and frees you up for more consequential work.

How does Palo Alto Networks make sure people are adopting AI tools?

Like many technology companies, Palo Alto Networks embraced AI at scale almost right out of the box. With the mandate coming from the top, the company invested in first-level, first-tier, non-purpose-driven AI that has been deployed across the entire organization.

The pitch was that this makes you more effective. To incentivize first use, our CEO announced a company-wide competition a week after deployment. People submitted AI ideas, and they got hundreds of submissions. We ended up with a database of ideas, several of which have now been brought to fruition. Everyone who made a submission got a small bonus. I think the word of mouth after that payment really got people thinking.

For our legal team, starting with the enterprise tools your company already uses has been most efficient. They are secure, vetted, low cost, and provide a safe environment to experiment with AI without exposing sensitive data. We’re now headed with our adoption beyond those foundational AI tools and looking at very purpose-driven AI applications.

"AI cannot be a solution in search of a problem. You need to start with the bottlenecks."

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What are some of the most successful GenAI use cases that have made your legal department shine with the business?

AI cannot be a solution in search of a problem. You need to start with the bottlenecks where there is a disconnect between the speed of commerce and the speed that legal was going. My, at the time, three-person legal team was inundated with a high-pain, high-volume, yet low-complexity drafting and document review. We identified several tasks that I would argue are repetitive and ministerial that AI can solve.

For example, our sourcing team needed a way to consistently generate termination letters, so we designed a Gemini Gem. The user can submit a single contract or a spreadsheet, and the AI generates letters based on the contract’s requirements for termination.

We are also deploying other specifically configured AI sub-tools that empower our clients in procurement to do things they would traditionally have approached legal for. It’s those repeatable, relatively simple tasks that take up an inordinate amount of attorney time for relatively low value.

This allows my team to move from the drafting chair to the review and consultation chair. You’re much happier spending 10 minutes helping clarify an issue than an hour drafting an amendment.

What's been the result?

The impact’s been transformational. Our turnaround times for these routine documents have shrunk from about five business days to just one business day and saves the legal team 20 to 40 hours per month. Our internal clients are happier and the business achieves its goals faster.

I’d advise others looking to move from experimentation to implementation to not try to solve all problems with a single tool. Start with one tool that solves one specific problem. That will build stakeholder trust, help with funding, and fuel future AI projects.

AI is not infallible, and has well-known limitations, such as hallucinations. How do you build trust in its accuracy and quality of outputs?

Our pitch, anytime we deploy a tool, is this is the alpha version, it’s not guaranteed to work. We believe that it’s good to experiment even if we blow up and fail miserably. And we want users to try it because we think it will empower and enable them to move faster. Their use also serves to help vet and improve the tool. Speed is a premium, I suspect, at every company, but certainly at ours.

The key is making certain that your internal clients know when to come see you. To mitigate against errors we’ve designed guardrails that direct the AI to throw up red flags. We say, “If you go beyond this point, you need to send a message to the user that this document needs to be checked with legal before it’s given to suppliers.”

Different tasks require different levels of review. If I'm extending an effective date, verification takes two seconds. If there's a $2 million deal, I'm still reading that contract end-to-end. AI is better at ministerial tasks than at nuance in my experience.

In your practical AI adoption framework for in-house legal teams, you emphasize the idea that AI adoption is a leadership challenge, not just a tech challenge, requiring trust building and managing change thoughtfully. Can you elaborate?

There is zero value proposition in AI unless you are willing to experiment. My personal belief is that your first AI project isn’t actually supposed to succeed. If it fails spectacularly, that is often a better outcome than if it works perfectly, because failure is where you actually learn about the limits of the technology and learn about ensuring appropriate guardrails.

As a leader, my job is to instill a culture where it’s safe to make those mistakes. For example, early on, we tried using NotebookLM as an engine for document generation. We thought we could automate the drafting of complex deal summaries by feeding it a massive corpus of data.

It failed for that specific purpose. It wasn’t the drafting chair solution we expected. However, that failure taught us something vital: the tool was actually an incredible analytical engine. It was better at finding the needle in the haystack across 50 documents than it was at writing the final memo.

Because we didn’t fall apart when the automation didn’t work, the team lost their fear of the tech. We stopped looking for a magic button and started looking for the right tool for the right task.

That is the leadership challenge: moving the team from a place of anxiety. From, “What if the AI is wrong?” and to a place of curiosity, where you ask “How can I break this tool to find its limits?” When you remove the penalty for failure, you gain the freedom to innovate.

[Edit. Note: Learn more in "The AI-Empowered Counsel: A Practical Framework for In-house Legal Teams."]

"Do not underestimate your abilities. For the first time probably ever, without a coding background, you can create a pretty solid prompt that will give you accurate results on a repeatable basis."

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We’ve been focusing on GenAI. But the headlines have moved on to Agentic AI – the autonomous systems that can actually take action and learn on their own over time. What risks and opportunities do you see with agents compared to GenAI?

I view GenAI as a partner that helps me move from a blank page to a first draft. Agentic AI is the next leap — it’s about moving from drafting to doing.

The opportunity is the ability to automate entire ministerial workflows. An agent doesn’t just draft a document; it can be configured to check a contract’s notice requirements, verify dates against a database, and package the final result for my review. For a high-volume team, that is a massive force multiplier.

However, I approach this with healthy skepticism. The more autonomy you give a tool, the higher the risk that a hallucination becomes a process error rather than just a typo. In legal, you cannot have an agent taking autonomous action without a solid governance framework.

My philosophy is that AI can process, but it cannot think or discriminate based on complex fact patterns. You still need a human in the loop to navigate the nuance and gray areas.

Are you building your own agents for legal?

We are already experimenting. We use Gems and custom-instructed tools to handle repeatable tasks for our internal clients. But we aren’t just handing out finished bots; we’re focused on teaching our team to fish by building a centralized prompt library. We have our eye on the bleeding edge, but we only deploy where the guardrails are as strong as the technology.

"When you remove the penalty for failure, you gain the freedom to innovate."

Share this quote:

You discuss prompting as a core legal skill. Will all lawyers need to become prompt engineers to use AI effectively?

I believe the entirety of the AI game, from an attorney’s standpoint, is about how good a prompt engineer you become. The AI can do most everything you need on a day-to-day basis. The issue is some practitioners have not yet become proficient at giving the AI sufficient direction to make things more efficient.

I like to say to other attorneys, especially the skeptics, do not underestimate your abilities. For the first time probably ever, without a coding background, you can actually create a pretty solid prompt that will give you accurate results on a repeatable basis. You know, ChatGPT uses Projects as the mechanism to store custom instructions, Gemini uses a system called Gems.

A lot of the problems that we saw where the work involved routine, repetitive, and largely ministerial tasks, we’ve been able to squash within the legal department just doing prompt engineering on our own.

And here’s the beautiful part about any of the AI that’s out there: if you don’t know how to prompt engineer, it’ll teach you that, too. It’s not that hard to learn how to get very sophisticated and even go so far as to develop a fully-fledged in-house agent.

[Edit. note: For Creque's comprehensive guide to legal prompting, with templates and prompt language to get started in multiple practice areas and matter types, see "The 6-Vector Legal AI Prompt Framework."]

What’s your advice to legal teams who fear that AI will replace them in their work?

The entire AI game in my humble opinion is about prompting. The worst thing you can do if you lead attorneys – as I have the privilege of doing every day – is when somebody says “Can I have the prompt?” and you give it to them. AI prompting is very much along the lines of, “Teach a man to fish.”

Teach your people, your colleagues, and indeed your bosses, how to construct a prompt, because that’s going to be way more important in the grander scheme than giving them the particular prompt that gave a particular output today. Don’t be afraid to experiment, even if you fail. The return on investment is clear if you use it for the right tasks.

When AI first rolled out to the public, I thought lawyers would lose jobs in five years. Now that I’ve used it, I think it’ll be much longer, if it ever happens at all. AI can analyze and process, but it cannot think or discriminate based on complex fact patterns, understand nuance, or bring to the fore the panoply of experiences I have had over more than 20 years of practice. With hallucinations, we’re years away.

Petra Pasternak is a writer and editor focused on the ways that technology makes the work of legal professionals better and more productive. Before Everlaw, Petra covered the business of law as a reporter for ALM and worked for two Am Law 100 firms. See more articles from this author.

Digital Spoliation of Evidence: Risks, Rules, and Prevention

2026-04-26T08:35:44Z

Digital Spoliation of Evidence: Risks, Rules, and Prevention

by David Pemberton

Reading Time — 7 minutes

April 16, 2026

The preservation of evidence is a foundational requirement in litigation, guaranteeing all parties equal access to the information necessary to reach a fair and just determination. Today, the vast majority of discoverable evidence exists in the form of electronically stored information, which is naturally more fragile than its physical counterpart.

That’s why a successful ediscovery strategy should include mastering the technical and legal nuances of digital spoliation.

Key Takeaways for Legal Teams

Digital spoliation happens when ESI is lost, altered, or destroyed after the duty to preserve has been triggered.
Courts may impose sanctions if relevant or potentially relevant ESI is spoliated.
Legal holds are critical for preventing the loss of ESI.
Maintaining well-documented processes strengthens defensibility during preservation challenges, and can demonstrate to the court that any spoliation was inadvertent, thereby avoiding severe sanctions.

What Is the Digital Spoliation of Evidence?

Digital spoliation is considered to be the intentional or negligent destruction, alteration, or loss of any ESI that may be relevant to a given legal matter. It happens when data is lost after the legal duty to preserve it has been triggered, potentially compromising the judicial process.

Why It Matters

Spoliation can be a deliberate action taken by a party to destroy, hide, or remove incriminating evidence, but it can also happen inadvertently and through negligence. If a party fails to adjust their email client’s retention settings after litigation is anticipated, those emails will likely be deleted and thereby become spoliated. In either case, lost ESI deprives the opposing party of evidence and should be taken seriously.

Because the Federal Rules of Civil Procedure mandate different judicial responses for intentional versus negligent acts, the court’s assessment of a party’s intent is pivotal in applying the appropriate remedy.

Rule 37(e)

While the duty to preserve is a long-standing common law practice, Rule 37(e) of the Federal Rules of Civil Procedure provides the specific framework for how federal courts handle the loss of ESI. This rule is designed to address the unique challenges of digital information, moving away from a standardized penalty system and instead focusing on proportionality.

Under Rule 37(e), if ESI that should have been preserved is lost because a party failed to take reasonable steps to protect it, the court first determines if the information can be restored or replaced. If it cannot, the court may take one of several actions.

In instances of negligent spoliation, courts first evaluate whether the lost data prejudices the opposing party. If a party unintentionally deletes emails in violation of a legal hold, but the loss does not result in prejudice, the court will likely forgo sanctions. However, if the unintentional destruction of ESI does prejudice the opposition, the court will implement corrective measures rather than punitive ones.

On the other hand, If it’s proven that a party acted with the specific intent to deprive another party of information, the court may impose severe sanctions. These sanctions can range anywhere from case dismissals to default judgements, or even an adverse inference instruction, in which the jury would be instructed to assume the spoliated evidence was damaging to the offending party’s case.

By focusing on reasonable steps, Rule 37(e) encourages legal teams to implement defensible, documented workflows in the pursuit of preserving ESI.

Intentional vs. Negligent Spoliation

The difference between intentional and negligent spoliation often dictates the severity of the court’s response.

Intentional spoliation involves the deliberate destruction of data with the specific goal of hiding evidence or gaining a tactical advantage.
Negligent spoliation is more common and typically results from user error, such as forgetting to disable an automatic deletion feature or failing to communicate a litigation hold to all relevant custodians.

While accidental loss is often treated with less severity than bad-faith spoliation, both can lead to sanctions if the court finds that the spoliation has harmed the opposing party’s case.

How Does Digital Spoliation Happen?

Digital spoliation is often the result of subtle, automated technical processes rather than deliberate action. Even routine data management can lead to the improper modification of relevant data. To maintain a defensible workflow, legal teams should understand where ESI is most vulnerable within their organization’s digital environment.

Automatic Deletion: The most frequent threat to digital evidence typically stems from standard efficiency practices. Most enterprise systems, like Microsoft Office or Google Workspaces, are configured to purge records after a set period of time. This setting, which is usually set by default, can inadvertently destroy ESI if not disabled.
Team and Messaging Platforms: Most offices and organizations utilize messaging platforms like Slack, Google Chats, or Microsoft Teams. These collaboration tools may have short retention cycles, meaning they may autodelete conversations regularly and often. These tools also give users the ability to edit or remove content without admin access, making the importance of a properly executed legal hold and data preservation process all the more relevant.
Documents and Metadata: Spoliation doesn’t always mean that a file has been destroyed, it can also refer to the loss of file integrity. It’s important to remember that modifying ESI can occur after the slightest interaction. Simply opening or moving a file without proper safeguards can alter the digital footprint that may be crucial for establishing a proper case timeline.
Device Loss or Destruction: Digital spoliation can also occur when the physical device that stores it is compromised. Computers and other devices can become lost, stolen, or even destroyed without the direct intent to do so. If a personal computer is left in a cafe and never recovered, or if a phone accidentally drops into a bathtub, any ESI that isn’t backed up elsewhere will be spoliated.
Failed Legal Holds: The first defense against unintentional spoliation is the timely implementation of a legal hold, which is the formal process in which organizations instruct their employees to preserve specific data for potential litigation.

Relevant data is frequently lost to routine digital maintenance when a gap exists between the anticipation of litigation and the issuance of a hold. Necessary preservation is difficult to achieve without a formal legal hold to override standard policies. Custodians may delete ESI or allow ESI to be deleted unintentionally, potentially hindering litigation.

Duty to Preserve

Timing is everything in the world of modern litigation. The duty to preserve ESI doesn’t wait for a formal subpoena or the start of discovery. It begins when litigation can be reasonably anticipated. That’s why understanding preservation triggers is essential for maintaining a defensible workflow.

Reasonably anticipated litigation: This is the most common trigger, occurring when a party becomes aware of facts or circumstances that would lead a reasonable person to expect a lawsuit.
Regulatory investigations: Inquiries from government bodies often carry immediate preservation mandates that mirror civil litigation duties.
Internal investigations: If an organization begins an internal probe into potential misconduct, the duty to preserve relevant ESI should be assumed.
Government inquiries: Even informal requests for information from state or federal agencies can serve as a signal that formal litigation or enforcement actions are on the horizon.

Once one of the above triggers occurs, legal teams should move quickly to implement legal holds and preservation protocols. These holds act as a manual override to an organization’s standard data retention policies, making sure potentially relevant evidence is locked down before it can be overwritten or deleted.

Consequences of Spoliation

More often than not, spoliation can result in significant consequences. Depending on the severity of spoliation and its impact on the case, a court may issue several types of sanctions.

Adverse inference instructions: The court may instruct the jury to assume that the lost or destroyed ESI would have been damaging to the party responsible for its spoliation.
Monetary penalties: Fines may be ordered to compensate the opposing party for additional costs incurred due to spoliated ESI, or the costs associated with bringing a motion forward related to spoliated ESI.
Exclusion of evidence: A party may be barred from introducing specific testimony or related evidence if the underlying digital records were spoliated.
Case dismissal: In the most extreme cases, typically involving efforts that were clearly made in bad faith, a court may dismiss a claim or enter a default judgment.
Referral for criminal prosecution: A court may also decide to refer a party for potential prosecution, if it finds that spoliation was intentional and designed to deny other parties access to potential evidence.

How Courts Respond to Spoliation

Judicial responses are made on a case by case basis. Courts typically weigh three primary factors when determining the appropriate consequence:

Effort to Preserve: The court will examine whether the offending party took reasonable steps to protect the data, such as implementing timely litigation holds and documenting their preservation workflows. If reasonable steps were taken and the data was lost anyway, spoliation sanctions are unlikely to follow.
Prejudice: When assessing spoliation, courts will consider the harm dealt to the opposing party’s ability to prove their case or defend their position. Spoliation of evidence that may be foundational to an opposing party’s argument will likely be treated more severely than the spoliation of evidence that has little to no material effect on the court’s final decision.
Intent: The court will also take into account the intent behind spoliation. If the evidence was lost through a routine automated process, the court will likely act more favorably than if there was a deliberate intent to deprive the opposing party of information.

How to Prevent Digital Spoliation

Mitigating the risk of evidence loss requires a proactive strategy that aligns legal obligations with technical execution. The best way for legal teams to achieve this is through implementing standardized workflows.

Move Fast on Legal Holds

The most effective way to prevent spoliation is the immediate issuance of a legal hold once a preservation duty is triggered. These holds notify custodians to cease any manual deletion and serve as a formal directive to bypass standard automated cleanup processes. A well-executed legal hold helps ESI to remain intact across large systems.

Coordinate With IT

Defensible preservation is a collaborative effort between legal teams and IT departments. To prevent the accidental loss of data, these teams should work closely to:

Grant system access so that legal or forensics teams have the necessary permissions to collect and/or lock down ESI.
Suspend retention policies by identifying and pausing any and all automated clean up protocols or expiration settings that would otherwise purge relevant ESI.
Maintain technical documentation by keeping a detailed log of all preservation actions taken, which serves as a critical audit trail if the effort to preserve is challenged in court.

Preserve ESI

Legal teams should categorize and prioritize data types to ensure comprehensive coverage. This includes traditional files like emails and spreadsheets, as well as more ephemeral sources such as social media or mobile data. Identifying these sources early is the start of ediscovery and the first step in preservation.

How Ediscovery Platforms Support Preservation

Modern legal obligations require modern technological solutions. Using a quality ediscovery platform is essential for maintaining a compliant and efficient discovery process. Modern ediscovery platforms can help legal teams track evidence, document preservation decisions, and help maintain a defensible workflow throughout the discovery process.

By leveraging purpose-built technology, legal teams can address the following critical areas:

Automated legal holds implement intuitive, user-friendly interfaces that streamline the issuance of notices and help legal teams keep track of when holds are deployed and acknowledged without adding administrative friction.
Targeted custodian surveys help legal teams gain granular visibility into the data landscape, allowing for the quick identification of relevant data sources and the custodians who manage them.
Proactive preservation controls help to deploy robust preservation tools that are purpose built to safeguard ESI at the source, helping to avoid the risk of inadvertent deletion or spoliation while maintaining a rigorous audit trail.

Learn more about preserving ESI and avoiding spoliation by building a defensible discovery workflow with Everlaw.

David Pemberton is an associate content marketer at Everlaw. His writing explores the influence of emerging technologies on the practice of law. See more articles from this author.

Five Ways Generative AI Is Reinventing Modern Litigation Workflows

2026-04-26T08:35:44Z

Five Ways Generative AI Is Reinventing Modern Litigation Workflows

by Justin Smith

Reading Time — 5 minutes

April 14, 2026

For decades, the discovery phase of litigation has involved a rigorous, manual search process. Legal teams often found themselves in a high-stakes game of digital hide-and-seek, leveraging armies of associates and contract review attorneys to search through millions of documents. While these methods were long considered the norm, the sheer volume of modern data has pushed these legacy processes to their natural limits, often delaying strategic insights until months into a case.

With the introduction of generative AI into the litigation process, it’s not just accelerating these old tasks, but fundamentally reimagining the lifecycle. By allowing legal professionals to focus on a strategy-first approach, AI tools allow them to interrogate their data in plain language, automate the heavy lifting of document coding, and bridge the gap between evidence and advocacy with live-linked drafting.

Initial Fact-Finding: From Keyword Guessing to Direct Interrogation

Historically, the early phase of discovery involved attorneys spending days crafting complex search strings, a process that essentially forced a high-stakes guessing game where one missed term or piece of internal jargon could mean missing the evidence entirely.

With Everlaw’s generative AI tool Deep Dive, however, you can now use natural language questions to interrogate an entire database. The AI understands the context of the inquiry, not just the literal characters in a search string.

For example, in a lawsuit against a chemical manufacturer, you might ask whether any internal discussions mention bypasses of the filtration system during the heavy rain events of 2022.

Based on that single question, Deep Dive can identify a chain of technical Slack messages where a supervisor tells a technician to open the secondary gate to prevent overflow. It’ll then synthesize an answer that connects this action to the specific dates of the rain, providing direct links to the logs.

Instead of spending weeks refining keywords and missing hidden jargon, the lead attorney now has a clear narrative of events within the first hour of opening the database. That frees up time to immediately begin building their case narrative, getting a head start on the other side.

Document Review: From Doc Review Marathons to Strategic Validation

Document review has long been a time-consuming process in which teams of associates and contract review attorneys would click through thousands of emails, often leading to reviewer fatigue and inconsistent coding.

Through the use of Everlaw^AI Coding Suggestions, you can now accelerate the review process by classifying documents on a scale based on a specific set of criteria that you provide, and then applying that criteria across entire document sets.

Coding Suggestions allows users to evaluate documents in accordance with their coding sheet, which contains all the coding categories a user has created. For every code configured for use, Coding Suggestions will offer a suggestion of whether it should be applied to the document or not, and provide rationale for its suggestion based on analysis of the document text. Users can easily apply, remove, or replace a code directly in the review assistant based on the suggestion.

For example, imagine that a former engineer at a tech company is accused of stealing proprietary code. You set a protocol for the tool to analyze, review, and code unauthorized data transfers to personal repositories.

The AI flags a "soft yes" on an email that doesn't mention "code" but discusses "backing up my personal settings" on the day the employee resigned. It notes that the file size attached is suspiciously large for "settings," alerting human reviewers to a potential smoking gun.

By maintaining your criteria across millions of files, the AI filters out the noise, allowing the high-priced legal team to focus only on the 2% of documents that actually matter and cutting review time significantly.

Evidence Synthesis: From Siloed Drafting to Integrated Storytelling

In traditional litigation, the finding of evidence and the writing of advocacy were often siloed. This created a constant, inefficient loop of exporting documents, copy-pasting quotes into separate Word files, and manually re-searching for those same files weeks later to verify a footnote. With large, multi-office cases, marrying up tranches of documents, deposition highlights, and expert reports was a full-time administrative job—a literal search for where the yellow Post-it matched the yellow highlighter.

Everlaw bridges this gap by integrating Storybuilder and Everlaw^AI Writing Assistant into the drafting process directly into the evidence environment. Instead of manual synthesis, attorneys can use AI to build connections across a shared digital brain, allowing the team to shift from administrative coordination to high-level strategy.

Say for example you’re representing a plaintiff against a pharmaceutical company that has been accused of ignoring early safety warnings for one of its medications. Your team has already identified a massive tranche of documents—ranging from 50-page clinical trial reports to informal internal Slack threads—that suggest the company ignored early safety warnings. Instead of an associate spending days manually cross-referencing these files to build a timeline, you prompt Writing Assistant to draft a statement of facts regarding internal knowledge of adverse cardiovascular events prior to 2018.

The AI generates a structured narrative based on the documents you’ve already surfaced, and links every sentence to the specific documents where it appears. If you click on a paragraph about a 2016 internal study, the original PDF opens instantly on your screen.

This helps your team move past the manual labor of citation. It ensures the narrative is always anchored in the record, making the final brief much more resilient to challenges.

Complex Data Extraction: Taming the Document Behemoth

Some documents are too dense for a quick human scan—think 100-page reports or 20-page meeting agendas. Reviewers often skim these, potentially missing a single line that changes the case.

As a feature within Everlaw^AI Review Assistant, Everlaw’s custom extractions tool can be used to pull structured information out of long, unstructured documents in seconds. You can extract out specific values from large document sets, which can be particularly helpful when keyword or regular expression searches are too ineffectual or cumbersome.

For example, consider you’re investigating a global construction firm for potential bribery. You have a 150-page unstructured ledger that details years of project expenses. Using Everlaw’s custom extractions, you configure the tool to extract three specific data points: Any individual or entity receiving funds, the specific dollar value of the transaction, and the internal justification or project code associated with the spend.

The tool then generates a clean, sortable table with the results. By looking at these specific fields in tandem, you quickly spot three entries listed as "Consulting Fee - Government Liaison." Because the tool has organized the dates and amounts for you, it becomes immediately obvious that these specific payments coincided exactly with a major contract win.

Now, what was once a three-day manual data entry task is a 10-second automated summary. The tool catches small details that a human eye would almost certainly skim over in a 150-page PDF.

Post-Deposition Analysis: Finding Inconsistencies at Scale

After a deposition, attorneys typically spend days highlighting transcripts and manually cross-referencing them against previous testimony or exhibits. Identifying where a witness changed their story across eight hours of testimony is a manual, error-prone task.

With generative AI, you can interrogate transcripts at scale, comparing testimony across different witnesses and against the documentary evidence.

For example, in a case against a technology company, you can ask the AI to identify any instances where the CEO's testimony about the “blind” hiring process contradicts internal emails or other witness statements.

The AI uncovers that on page 82, the CEO claimed he never saw candidate names, but then it cites a specific internal email from three months prior where he explicitly requested the names of candidates for the final round.

This provides instant material you can use in your case. You aren't just summarizing what was said, but are actively hunting for the truth across the entire record.

The New Bottom Line

By automating the most labor-intensive parts of the discovery lifecycle—from initial fact-finding to post-deposition analysis—generative AI allows legal teams to focus on what they do best: high-level analysis, client counseling, and building a narrative that helps win their case.

Attorneys need a tool that works alongside them and adapts to their processes. Discovery is rarely linear. It’s an iterative process of asking a factual question, following a hunch, and often pivoting strategy the moment a key document comes to light. Generative AI adapts to this fluid reality, keeping pace with an attorney's intuition and allowing them to interrogate the evidence as quickly as new theories emerge.

Ultimately, these tools provide a significant competitive advantage. Instead of being buried by the volume of modern data, you can use generative AI as the foundation for a winning strategy. In the high-stakes world of litigation, the smoking gun is no longer found through luck or manual labor—it’s found through intelligence.

Justin Smith is a Senior Content Marketing Manager at Everlaw. He focuses on the ways AI is transforming the practice of law, the future of ediscovery, and how legal teams are adapting to a rapidly changing industry. See more articles from this author.

ILS + Everlaw

2026-04-26T08:35:44Z

ILS + Everlaw

How Deep Dive Is Changing Litigation for Plaintiffs' Attorneys

2026-04-26T08:35:44Z

How Deep Dive Is Changing Litigation for Plaintiffs' Attorneys

2026-04-26T08:35:44Z

How Deep Dive Is Changing Litigation for Plaintiffs' Attorneys

by Gina Jurva

Reading Time — 4 minutes

April 13, 2026

Elizabeth Koenig spent 8 years litigating at Milbank on the defense side before joining ILS to focus on plaintiff’s ediscovery. As senior vice president of consulting services at ILS, she leads a team of attorneys who provide ESI protocol consulting and project management for plaintiffs in mass torts and class actions.

ILS has worked on major litigation: Volkswagen diesel scandal, 3M combat earplugs, JUUL vaping, opioid crisis. The firm is exclusively plaintiffs-only, never taking work from defense firms or corporate defendants.

These cases share common challenges: massive document sets that can span decades, complex questions of fact buried in millions of pages, and well-funded corporate defendants with the resources to wage prolonged discovery battles. For plaintiffs' firms, the asymmetry is built into the system.

"We're mission driven," Koenig explained. "We're aligned with our clients in that sense that we are attempting to use the technology to level the playing field for individual plaintiffs, harmed parties who are aggrieved by corporate misdeeds and malfeasance."

That mission shapes how she thinks about technology, particularly Everlaw^AI Deep Dive, which she believes is changing how plaintiffs handle document-intensive cases.

Deep Dive is Everlaw's AI-powered tool that allows attorneys to ask natural language questions directly to their document set like "What did the CEO know about the defect in 2019?", and receive answers with supporting evidence and citations. For Koenig, it represents a fundamental shift.

"Deep Dive, Everlaw's newest tool, is one of the most exciting developments I've seen in over a decade in this industry," Koenig said.

The Resource Gap Is Real

Plaintiffs' attorneys face a structural disadvantage in discovery. They don't have the same staffing levels as corporate defendants. They can't deploy legions of associates to review millions of documents. The economy doesn’t work that way.

"We are often at a disadvantage in terms of attorneys who can staff our cases. We don't have the same resources that the corporate defendants do," Koenig said. "A tool like Deep Dive allows us to do significantly more work with fewer people and to surface critical documents that can be very difficult to find."

She's watched client’s beta test Deep Dive on a massive case with millions of documents, using it almost exclusively for deposition and trial prep. The results have been striking.

"They've been able to cut their review time significantly, improve their ability to get quickly to the critical documents that they need, and see some things that they haven't seen even though they've been working on this case, in these documents, for over a year," Koenig said.

That last part matters. These weren't fresh eyes finding new things; these were attorneys who had been living in the case documents for months, and Deep Dive surfaced materials critical to their case.

"It's really a game changer," Koenig said.

Why Deep Dive Is Different

Deep Dive works through natural language questions, making it immediately accessible for attorneys at all levels, from senior litigation partners to junior associates.

"It’s very accessible because of the natural language use, so they're a great fit for lawyers who are already asking questions. That's part of what lawyers have been doing for hundreds of years," Koenig said. "We ask questions in deposition, in trial, and so now a tool like Deep Dive allows you to do that same kind of questioning."

"A tool like Deep Dive allows us to do significantly more work with fewer people and to surface critical documents that can be very difficult to find."

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The adoption pattern has been different. "What we're seeing is lawyers who might not have wanted to get into a database before and let their associates do it, now they do want to get in. They want to ask their own questions."

She compared it to the jump from paper to electronic platforms, noting that people already use similar AI tools in their personal lives. Generative AI platforms like ChatGPT have made the concept familiar.

Practical Applications Beyond Trial Prep

ILS clients are finding uses for Deep Dive that go beyond the obvious deposition and trial prep scenarios.

One application: quality control on outgoing productions. Plaintiffs produce documents too, and they need to ensure nothing privileged or improperly redacted goes out. But they rarely have the resources for multiple levels of review.

"We're able to use a tool like Deep Dive to do a QC," Koenig said. "Maybe we don't have the resources to do a second and a third-level review the way that you'd have a defense firm having a legion of lawyers who are able to review outgoing productions. With a tool like Deep Dive, we can take our production set and make sure we're catching everything."

Medical records present another significant opportunity for efficiency. Mass tort cases often involve lengthy patient histories; records can run three or four thousand pages, dense with medical terminology. Traditionally, firms hire teams of nurses to review them.

Now, using Everlaw's suite of generative AI tools including Deep Dive, document summarization, and Coding Suggestions, attorneys can process medical records much faster. "They're able to use some of the different suite of GenAI tools that Everlaw has to summarize those, to dive into those in a much quicker way," Koenig noted.

Foreign language documents have become more manageable as well, thanks to Everlaw’s AI Translation functionality. Cases involving Asian or European languages used to require hiring attorneys fluent in those languages—an expense that could price plaintiffs out of effective representation. "Now they're able to have much less of a need for that with the GenAI technology," Koenig said.

The Transparency Question

As plaintiffs' counsel, Koenig thinks about how defendants will use AI tools—and how to hold them accountable to discovery rules.

The frameworks for predictive coding and search terms should apply to generative AI, she argues. "Just because these tools are different, just because there's perhaps more of an ease in iterating on the particular prompts that are used, it does not obviate a producing party's need to be transparent," Koenig said.

"What we're seeing is lawyers who might not have wanted to get into a database before and let their associates do it, now they do want to get in. They want to ask their own questions."

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She expects courts will start ordering disclosure of prompts the same way they order disclosure of search terms. The validation techniques used for predictive coding can be applied to generative AI workflows. She's already working on protocols and expects court orders addressing GenAI within the year.

There will be fights about this. Not every case will require transparent AI processes, but in high-stakes litigation, it will happen, she believes.

Why the Partnership Works

ILS partnered with Everlaw in 2022. Since then, it's become a critical part of their technology stack.

"Everlaw has a history of working with plaintiffs, with nonprofits, with government entities, which makes it a great fit for ILS," Koenig said.

She's been impressed by how Everlaw has integrated generative AI seamlessly, but also thoughtfully. Deep Dive remains in beta because Everlaw is being careful. "That is, of course, as a service provider, incredibly important for us because we're also standing behind the tool," Koenig explained.

What Comes Next

Koenig sees this moment as an opportunity to develop new workflows clients haven't considered yet.

"This technology is completely different than most things that we've used before. It's, in my mind, a chance to be creative, to bring a new consultative approach to clients," she said.

For plaintiffs facing well-resourced corporate defendants, that matters. Deep Dive won't solve every problem. But for the first time in Koenig's decade in the industry, she's seeing a tool that plaintiffs' attorneys are excited to use themselves, not just delegate. That changes the equation.

Gina Jurva is an attorney and seasoned content strategist located in Manhattan, with over 16 years of legal and risk management expertise. A former Deputy District Attorney and criminal defense lawyer, her diverse litigation skills underscore her steadfast commitment to justice, while her innovative storytelling strategies combine legal acumen with deep insight. See more articles from this author.

DeNISTing in Ediscovery: What It Is and Why It Matters

2026-04-26T08:35:44Z

DeNISTing in Ediscovery: What It Is and Why It Matters

by David Pemberton

Reading Time — 4 minutes

April 9, 2026

Not all data is created equal in the world of ediscovery. That’s why navigating modern litigation requires a strategy for dealing with the junk data that often clogs up and slows down the ediscovery process.

Electronically stored information can include relevant and valuable data, like chat logs or email threads, alongside junk data, like application and operation files. These junk files are not user-generated, contain no relevant data, and offer no advantage in early case assessment.

Thankfully, irrelevant files can be removed before review begins with the help of a process called deNISTing.

Key Takeaways for Legal Teams

DeNISTing is an ediscovery data-filtering process that removes known, non-user-generated files such as system, application, and executable files.
DeNISTing utilizes the NIST list, which is maintained by the National Institute of Standards and Technology.
DeNISTing is different from deduping, which removes exact and near exact document copies from a dataset.
DeNISTing takes place during data ingestion and is designed to give legal teams a head start in ECA.

What Is DeNISTing?

To put it simply, deNISTing is an easy way to remove irrelevant data in the early stages of ediscovery. The process is a version of data filtering that removes system files, program files, and other immaterial data. In culling these files, deNISTing simplifies ediscovery by making ESI easier to navigate and analyze.

The files removed by deNISTing are generally essential for running operating systems and software applications, but they aren’t going to contain any valuable information for either party in a legal matter. A common example of the data culled by deNISTing would be an .exe file, which is used to install software. Anyone who has installed a new program on their computer has likely engaged with an .exe file. Once the program is installed, users are encouraged to delete the file because it’s no longer useful. When included in ediscovery, data like .exe files add unneeded complexity to review, wasting both time and money.

The NIST List

The deNISTing process is built on work provided by the National Institute of Standards and Technology, an agency of the U.S. Department of Commerce. They maintain an authoritative list of known file types that are non-user-generated with a project called the National Software Reference Library.

This list is updated quarterly, which means it stays up-to-date on new file types, thereby acting as a universal authority for the process. DeNISTing takes advantage of the NIST list by using it to identify irrelevant files.

How DeNISTing Works

Like many aspects of ediscovery, deNISTing might sound complicated at first. The important thing to remember is that the process uses the NIST list to check data against irrelevant file types. Here’s a step-by-step breakdown of how it all works:

Hash Value

DeNISTing cleans up data by using something called an “MD5 Hash Value,” which acts similarly to a physical barcode. Just as a barcode identifies a specific product on a shelf, every unique file has its own specific hash value.

Comparison

The hash value identified for each file in a dataset is then compared to the NIST list, automatically tagging any matching hash values.

Culling

The files identified will be removed during the deNISTing process, oftentimes greatly reducing data volume prior to review.

Common File Types Removed by DeNISTing

The file types culled by deNISTing are those used to install or run other programs and assets on a computer or device. Below are a few of the most common non-user-generated file types culled in deNISTing:

Executable files such as .exe, .com, .bat, and .cmd
System files such as .dll, .sysm, .ini, and .ocx
Fonts including .ttf, .fon, and .otf
Shortcut files such as .lnk and .pif

While the above list is in no way comprehensive, it’s important to remember that the NIST list is updated on a quarterly basis, which means new file types are added regularly. Thankfully, the most up-to-date version of the list is always available via the official NIST National Software Reference Library.

Why DeNISTing Matters

DeNISTing is an essential first step for reviewers facing mountains of digital evidence. Legal teams can drastically reduce data volumes before review begins by automatically filtering out the known system files identified by the NIST list.

Clearing out digital clutter also streamlines ECA by giving reviewers a considerable headstart in identifying substantive evidence. Legal teams are generally looking for specific information produced by a party in a given legal matter, information that is likely found in files like emails, documents, and chat logs. These teams don’t want, or need, access to the innumerable files that make email, word processing, and chat programs operate.

DeNISTing vs. Deduping

Deduping (or deduplication) identifies identical or near identical files within a dataset before culling redundant information. Similar to deNISTing, deduplication generates unique hashes to represent each file’s binary content. If two files share the same hash value they are considered identical, and only one copy is retained while the others are removed.

How Deduping Works

Deduping can save reviewers time and energy by avoiding the need to sift through and manually parse identical documents. Similar to deNISTing, the process begins with generating a hash value for every document.

Hash Value

Deduplication identifies redundant data by using the same MD5 Hash Value system as deNISTing. When the process begins, every file is assigned a hash based on its contents.

Comparison

During the deduplication process, the system calculates the hash value for every file and compares them against one another. When the system identifies multiple files with the exact same hash value, it flags them as duplicates.

Culling

Once duplicates are identified, the system keeps one master copy and culls the redundant versions. This process makes sure reviewers only see a unique document once, greatly reducing data volume.

Of course, deduping in no way replaces the work done by deNISTing. That’s why, when dealing with large, complex datasets, it should be considered a best practice to add both deNISTing and deduplication to ingestion workflows.

Key Similarities

Both utilize hash values to identify files quickly.
Both serve as essential filters during ECA by reducing the volume of data.
Both are best performed during the ingestion phase, after collection and before review.

Big Differences

DeNISTing removes irrelevant junk data, deduplication removes duplicate, user-created data.
DeNISTing targets non-user-generated files like .exe files, deduplication targets identical and near identical copies of documents.
DeNISTing compares file hashes against the NIST list, deduplication compares file hashes against each other.

Creating a Workflow That Works

Automatically filtering out irrelevant files is just one of the ways in which ediscovery platforms bridge the gap between complex technical processing and practical legal workflows. By utilizing deNISTing to cull massive datasets, legal teams can bypass the noise and direct their expertise toward the high-value files that actually influence case strategy.

Learn more about how Everlaw supports efficient document review workflows by helping legal teams process large amounts of data efficiently while maintaining transparency throughout pretrial discovery.

Frequently Asked Questions

What file types are removed by deNISTing?

DeNISTing targets system and application files that are not user-created. While these files (such as .exe files) are essential for running software, they almost never contain evidentiary value in standard litigation. By filtering these out during ingestion, legal teams can significantly reduce data volume without losing valuable ESI.

Is deNISTing required in ediscovery?

No, deNISTing isn’t explicitly mandated. Instead, it’s considered a best practice because it’s an automated process based on a verified national standard. Practically speaking, there are very few reasons not to take full advantage of the deNISTing process.

When should deNISTing happen?

DeNISTing takes place during the ingestion phase, after data is collected but before it is reviewed. Filtering at this stage helps to lower costs and increase efficiency by removing irrelevant system files and expediting human review.

How is deNISTing different from deduplication?

Both deNISTing and deduplication are forms of automated data filtering. Both target different file types and will result in the culling of different kinds of files. DeNISTing removes junk files that were not user-created, deduplication removes redundant copies of identical and near identical files.

David Pemberton is an associate content marketer at Everlaw. His writing explores the influence of emerging technologies on the practice of law. See more articles from this author.

Stephen Lee Law + Everlaw

2026-04-26T08:35:44Z

Stephen Lee Law + Everlaw

Solo Practitioner Stephen Lee Leverages Everlaw to Level the Playing Field

2026-04-26T08:35:44Z

Solo Practitioner Stephen Lee Leverages Everlaw to Level the Playing Field

by Justin Smith

Reading Time — 4 minutes

April 7, 2026

In the early days of legal practice, a lawyer’s strength was often measured by the height of the paper stacks on their desk and the number of associates available to carry them. Victory in complex cases were often wars of attrition, won by the side with the most boots on the ground to sift through endless bankers' boxes.

But as the legal world has moved from the filing cabinet to the cloud, a new era has emerged—one where the solo practitioner can stand toe-to-toe with the government and the largest law firms. The equalizer isn't just a deeper understanding of the law, but the strategic application of technology that can synthesize a digital ocean of data into a single, winning narrative.

This shift is where attorney Stephen Lee has thrived for much of his career. Based in Chicago, Lee has built a practice that feels less like a traditional law office and more like a high-tech investigative unit. By blending the instincts of a veteran journalist with the institutional knowledge of a former federal prosecutor, he has redefined what it means to be a solo practitioner in the age of big data litigation.

The Journalist’s Lens on Ediscovery

Before Lee started his legal career, he was a reporter for the Dallas Morning News and the Chicago Tribune. In the newsroom, he learned how to explain complicated topics to a wide audience, and that details and data can be just as compelling as what someone says, if not more.

When he transitioned to the law—first at Debevoise & Plimpton and then during an 11-year tenure as an Assistant U.S. Attorney in the Northern District of Illinois—he brought that same investigative rigor with him.

Now, as the founder of his own defense firm, Lee focuses on some of the most complex and high-stakes litigation there is, including criminal charges involving federal health care fraud and the federal Anti-Kickback Statute. These are cases where the government doesn't just present a few key documents; they dump a digital universe of encrypted messages, WhatsApp threads, and years of billing data onto the defense.

As a solo practitioner, Lee cannot afford to spend weeks manually reviewing documents. He uses Everlaw to act as his digital force multiplier. By leveraging advanced search, data analytics, and targeted searches, he can ingest massive datasets and immediately begin identifying the documents that will form the backbone of his defense. This allows him to focus on the high-level strategy that wins cases, rather than getting lost in the weeds of administrative document management.

“Everlaw is pretty intuitive,” Lee said. “The platform makes it easy to find what you need, especially with all the filtering that we were doing to show my client what the government’s case was and what really happened. It makes a lot of sense.”

Navigating the Tide of Massive Enforcement

The scale of modern federal investigations is often defined by wide-reaching, multi-jurisdictional initiatives that cast an incredibly wide net. These sweeping enforcement actions can sometimes sweep up well-meaning individuals alongside those with criminal intent. For Lee, matters stemming from these massive federal operations represent the ultimate challenge in discovery management. During one case that went to trial, it immediately became clear that he would have to out-organize the prosecution to make his case.

“We knew what happened from our point of view, but we had to figure out what the government believed happened and where they went wrong in their investigation,” Lee said. “They ran a pretty shoddy investigation, and they quickly made up their minds to charge my client and wouldn’t back down.”

This was especially important because Lee’s client planned to testify. People charged in criminal cases do not have to testify, but choosing to can help jurors understand what really happened from the defendant’s perspective, which is often the key issue in a criminal case.

Preparing to testify is a daunting task for any lawyer or client, and the client must be able to explain incidents and conversations from years prior with as much precision as possible to help the jury understand their story and to survive cross-examination.

Everlaw became a big part of how Lee and the client prepared. Rather than handing his client a stack of paper that would inevitably be re-tabbed and reorganized as the trial progressed, Lee gave him direct access to a dedicated project within the Everlaw platform.

“I thought, ‘Wait a second. If I make a project and put all the documents there in Everlaw, I can just teach my client how to navigate the platform, and he can review all the documents on his computer, so if I need to update something, I can do it easily,’” Lee said. “I had the master chronology, and rather than me emailing him this report or that report, he could just see everything in Everlaw.”

This allowed the client to log in from his own computer and review his own history—his emails, messages, and calendar—in a way that was intuitive and searchable. The client used Everlaw to prepare himself with and without Lee, and was better equipped to explain the context of every document with confidence during trial. Ultimately, the client testified for several days about every document or incident that the government had brought up in its case-in-chief. At the end of the case, the client was acquitted of every charge.

The Solo Practitioner as a Legal Powerhouse

The success of Lee’s practice serves as a blueprint for the future of the legal profession. For a solo practitioner, the goal is no longer to be the biggest firm in the room, but the most agile.

Lee has replaced expensive physical storage and manual labor with a platform in Everlaw that scales with his needs. This allows him to take on some of the most complex health care fraud cases in the country with the confidence that he can manage the discovery process as effectively as any large firm or government agency.

For example, in another recent case, the government had two lawyers, two agents, and a paralegal on their side, with just Lee and his client on the other. Lee was able to use Everlaw during the trial to respond quickly to the government’s case without any additional help, including showing how the government had taken emails and text messages out of context. The case ended with the client’s acquittal.

Whether he is securing an acquittal in a telemedicine case or overturning a conviction in the Seventh Circuit, Lee’s focus remains the same: using technology to help ensure that the jury hears what really happened.

“In this day and age, we're drowning in discovery and drowning in too much information,” Lee said. “A big part of an attorneys’ job is trying to organize all of that and sift through what we really need. I think using technology to organize the data and try to get some handle on it is really important.”

Morgan v. V2X, Inc. Decision Sets Precedent on AI Disclosure in Discovery

2026-04-26T08:35:44Z

Morgan v. V2X, Inc. Decision Sets Precedent on AI Disclosure in Discovery

by Justin Smith

Reading Time — 4 minutes

April 2, 2026

One of the top concerns legal professionals have had regarding he use of generative AI is focused largely on hallucinations—the tendency of LLMs to invent fake case law. However, a recent decision from the U.S. District Court for the District of Colorado suggests the bench is moving toward a much more sophisticated concern: data privacy and the underlying data ingestion that powers these models.

In Morgan v. V2X, Inc. (D. Colo. Mar. 30, 2026), a routine employment discrimination case escalated into a high-stakes battle over how confidential discovery materials are handled in the age of AI. The result is a modified protective order that serves as a potential blueprint for modern litigation. This is the first order of its kind, as far as we are aware.

The Core Dispute: Productivity vs. Privacy

The conflict began when the plaintiff, appearing pro se, sought to use AI tools to bridge the technological gap between an unrepresented litigant and a well-funded corporate defendant. The defendant, V2X, Inc., raised alarms about whether its confidential information—including trade secrets and personnel files—was being fed into mainstream AI platforms like ChatGPT or Gemini.

This is an issue because if models are trained on privileged or confidential information, it’ll then replicate some or all of that information in future outputs.

While the plaintiff argued that his choice of software was protected work product, the court disagreed. Magistrate Judge Maritza Dominguez Braswell ruled that while a party’s mental impressions are protected, the identity of the AI tool is not. If confidential data is being uploaded to an AI platform that may compromise its confidentiality, the opposing side has a legitimate right to know where that data is going.

Privacy and Confidential Materials in the AI Age

One of the most intriguing parts of the decision is the court’s discussion of the Fourth Amendment and the reasonable expectation of privacy. The court acknowledged that in 2026, almost all data passes through third-party systems like Gmail. “Does that mean that anyone with a Gmail account has forfeited all rights to confidentiality and privacy?,” the court asked.

Contextualizing its analysis in Fourth Amendment search and seizure case law, the court determined that the answer was a simple “no.”

“The Fourth Amendment governs searches and seizures and offers a wholly different legal framework from the work product doctrine, but the principle reflected in those cases is informative: routing information through a third-party system does not forfeit all privacy,” the order said.

However, Judge Braswell noted that unlike passive search engines, AI chatbots are designed to foster interactions that encourage the disclosure of sensitive information.

“Unlike a general-purpose search engine, which passively returns results, many modern AI platforms are specifically designed and trained to engage,” Judge Braswell wrote. “They invite candid and significant disclosure of information, including sensitive information. They simulate empathy, foster trust, and interact in a way that feels genuine and intimate. Research confirms that people share personal and sensitive information with AI chatbots, often without appreciating what happens to that information once shared.”

For pro se litigants, the court noted, those interactions “closely resembles the kind of confidential, strategy-laden iterative work product that Rule 26(b)(3) was designed to protect.”

However, while work-product protections may have shielded the plaintiff from disclosing their AI usage – and the court does leave its determination at may – the plaintiff ultimately failed to make his case.

“Even if it is possible that in some contexts disclosing an AI tool can reveal mental impressions or strategy,” the court determined, “Plaintiff has not carried his burden to demonstrate that here.”

The court concluded that while routing data through an AI system doesn't automatically waive all protections, it does create a risk that mainstream, low-cost tools will persistently collect and store data for their own purposes.

The Court’s AI-Specific Language

In its decision, the court moved beyond general warnings and established a precise set of contractual must-haves for any legal professional looking to integrate AI into their workflow. To ensure that sensitive data remains protected from model training and unauthorized exposure, the court’s modified protective order explicitly mandates:

No party or authorized recipient may input, upload, or submit CONFIDENTIAL Information into any modern artificial intelligence platform, including any generative, analytical, or large language model-based tool (“AI”), unless the AI provider is contractually prohibited from:

(1) storing or using inputs to train or improve its model; and (2) disclosing inputs to any third party except where such disclosure is essential to facilitating delivery of the service. Where disclosure to a third party is essential to service delivery, any such third party shall be bound by obligations no less protective than those required by this Order. In addition, the AI provider must contractually afford the party or authorized recipient the ability to remove or delete all CONFIDENTIAL information upon request. A party intending to use AI that it contends meets these requirements must retain written documentation of these contractual protections.

Implications for Pro Se Litigants

A central part of the case was the plaintiff’s status as a pro se litigant seeking to leverage AI to manage a complex case. In the decision, the court directly addressed the reality that secure AI systems often come with a higher price tag.

“The Court recognizes that practically speaking, and in light of the current state of AI, this provision will (at least for now) bar the parties from using most, if not all, mainstream low-to-no cost AI to process Confidential Information. This type of restriction disadvantages pro se litigants,” the decision read.

It went on to discuss the fact that enterprise-tier AI accounts are often only available through organization-wide procurement and are too expensive for pro se litigants to access. However, it also acknowledged that the risks of uploading confidential data to mainstream tools was a real issue that needed to be addressed.

While the court’s intention with this order was to prevent the uploading of confidential information to openly available AI tools, it also highlighted that it did not restrict the pro se litigant from using them all together.

“To be clear, the Court does not intend to leave pro se Plaintiff without the benefits of AI,” the order read. “Modern AI tools may be used in many ways that do not involve uploading Confidential Information, and nothing in this particular Order restricts those uses.”

The New Rules of Engagement

To mitigate these risks, the court issued an amended protective order with three strict requirements for using AI with confidential discovery.

Training Bans. The AI provider must be contractually prohibited from using inputs to train or improve its models.
Strict Confidentiality. The provider cannot disclose inputs to third parties unless essential for service delivery.
Right to Delete. The user must have the contractual ability to remove or delete all confidential information upon request.

The Bottom Line for Practitioners

The Morgan decision effectively bars the use of standard or free versions of mainstream AI for processing sensitive case data. As firms (and pro se litigants) look to integrate AI, the burden is now on the attorney to verify the terms of service.

In the eyes of the court, a secure environment isn't just about preventing hacks—it’s about ensuring your client’s data doesn't become the training set for tomorrow’s algorithm.

What Is Chain of Custody? A Guide for Ediscovery Teams

2026-04-26T08:35:44Z

What Is Chain of Custody? A Guide for Ediscovery Teams

by Petra Pasternak

Reading Time — 8 minutes

March 26, 2026

Chain of custody, in the simplest of terms, is the chronological, documented record of everyone who has handled, accessed, or stored a piece of evidence. It serves as a “paper trail” that tracks the journey from the moment evidence is collected until it is presented in a legal proceeding. The purpose is to prove it has not been tampered with or altered in any way.

Such documentation is important to establish trust that the evidence is authentic and therefore admissible in court. The Federal Rules of Evidence govern the admissibility and authentication of evidence. Proper chain of custody helps convince the court there is a reasonable probability that the evidence is what the party claims it is, and is in substantially the same condition as when it was collected.

Without documentation showing who collected the evidence, when and where, who handled or accessed it, and how it was stored or transferred, opposing counsel may argue that it is unreliable or inadmissible, which can jeopardize the case.

Chain of custody documentation is a best practice for the handling of both physical and digital evidence.

Key Takeaways for Legal Teams

Chain of custody is a documented record that tracks how evidence is collected, handled, accessed, and preserved to prove its authenticity and integrity in court.
Courts evaluate custody to assess whether evidence was managed in a reasonably reliable and defensible manner, not whether handling was perfect.
Breakdowns in the chain of custody can lead to admissibility challenges, adverse inference instructions, monetary sanctions, or other remedial measures.
In ediscovery, consistency, traceability, and auditability are critical because if digital data is improperly duplicated, modified, or moved, it becomes harder to validate its authenticity.
Defensible chain of custody is critical during discovery planning, where parties define how evidence will be handled so the approach can later be explained and justified.
Strong custody practices allow legal teams to focus on substantive arguments rather than defending their processes under scrutiny.

What Does Chain of Custody Mean in Legal Contexts?

In the legal context, chain of custody is defined as the “chronological documentation or paper trail that records the sequence of custody, control, transfer, analysis, and disposition of physical or electronic evidence.” This type of record helps establish that evidence is authentic, reliable, and substantially unchanged throughout its lifecycle.

Traditionally associated with physical evidence, chain of custody today applies equally to digital information. Proper documentation shows there were controls and safeguards in place continuously against alteration or loss of evidence. The documentation typically covers who had access, when, how it was stored, and how it moved between custodians or systems.

Modern custody of the evidence practices emphasize accountability, not just possession. Documentation that shows what controls were in place — such as locked storage for physical evidence or audit trails for electronic evidence — and whether handling procedures met reasonable standards helps establish integrity and allows a party to respond to tampering or contamination challenges. For electronic evidence, this may include controls around access permissions, audit trails, preservation measures, and defensible workflows that demonstrate responsible handling.

For legal teams, maintaining a defensible chain of custody means treating documentation as a continuous process rather than a single event. Collection details, transfers, processing steps, and secure storage practices all contribute to the record that supports admissibility. Ultimately, chain of custody is about demonstrating transparent, accountable stewardship over time.

How Chain of Custody Works in Practice

Chain of custody begins when evidence is collected and extends through handling and storage, all the way to discovery and trial.

Collection

Teams should have a plan to protect data integrity. This starts from the moment they begin to gather electronic information to preserve the original state of the data in anticipation of future legal scrutiny.

Digital material can easily be duplicated, modified, or accessed without obvious signs of change. Documentation during the gathering phase becomes the primary mechanism for creating a defensible record of how evidence was handled, helping to establish authenticity.

During collection of electronically stored data, investigators typically use forensic methods — such as creating verified copies or images of storage systems — while recording such essential details as the date, time, source, method of collection, and identity of the person responsible. All later handling can be evaluated from this baseline.

Handling and Access

Chain of custody relies on consistent records showing who accessed the data, what actions were taken, how it was stored, and how it moved between systems or parties. These records might include audit logs, metadata preservation, and controlled workflows.

Storage and Preservation

To demonstrate defensibility, legal teams would typically need to show the evidence was preserved in a way that reasonably prevents loss, unauthorized alteration, or accidental changes over time. In digital matters, that typically means being able to show consistent preservation controls — such as stable repositories, retained metadata, and access restrictions — and a clear record of where the authoritative version lived. Secure storage is essential.

Transfers

After initial collection, there are other key transition points at which documentation is critical. These include any transfers between custodians or platforms, processing and analysis, and any export or production of evidence.

Presentation or Production

Chain of custody culminates when evidence is produced in discovery or presented in court. The key is traceability: showing continuity from the source to output so the evidence can be evaluated and challenged on substance rather than process. At each step, proper documentation helps demonstrate continuity and reasonable safeguards against alteration.

Why Chain of Custody Matters in Legal Matters

Proper chain of custody ensures that evidence is viewed as credible and admissible. Clear custody records allow legal teams to focus on the merits of their case rather than defending their processes. Without that foundation, even crucial evidence may face heightened scrutiny or potential exclusion — with implications for the direction of the case.

Inconsistent chain of custody practices significantly increase the risk of legal challenges. Opposing counsel may question whether evidence was altered, mishandled, or accessed improperly, leading to disputes over authenticity or completeness.

In a criminal case, for example, the prosecutor is expected to provide evidence showing the defendant is guilty. A broken chain of custody can undermine the party’s case, leading to motions for dismissal or a weakened position in settlement negotiations, as well as open avenues for appealing of a ruling. Such issues may also lead to allegations of misconduct, adverse inference, imposition of sanctions, and reputational harm. Even when evidence is ultimately admitted, unresolved custody questions can undermine credibility and weaken the persuasive impact of otherwise strong material.

A broken custody chain can also cause delays and extra costs. When the integrity of evidence is challenged, legal teams may need to reconstruct handling histories, re-collect data, or engage forensic experts to validate processes that should have been documented from the start. This can affect litigation timelines, increase discovery expenses, and divert attention from case strategy.

These principles apply beyond traditional litigation. Establishing a chain of custody for physical and digital evidence is essential to criminal investigations, regulatory inquiries, compliance reviews, and government enforcement actions, where the reliability of digital evidence is crucial.

Whether responding to a subpoena, conducting a workplace investigation, or preparing for regulatory scrutiny, maintaining a transparent and well-documented custody record helps organizations demonstrate responsible stewardship of data and strengthens confidence in the conclusions drawn from it.

Chain of Custody for Digital Evidence

Electronic evidence by its very nature introduces new custody challenges. Unlike physical evidence, digital data often lives in multiple locations – such as emails, social media accounts, on hard and shared drives, and the cloud. It can also be altered, copied, or deleted easily and without obvious traces. Simply opening a file can change its metadata, potentially altering the access date and compromising the file’s original state. This requires a shift to tracking the system-based custody of the data itself.

As Steve Davis, VP of Forensics and Investigations at Everlaw partner Purpose Legal points out, forensic evidence is not simply data, it’s data gathered according to a specific process that preserves integrity, context, and defensibility. “The moment evidence is mishandled, even unintentionally, its credibility can be permanently compromised,” Davis writes.

Role of Metadata, Access Logs, and Audit Trails

Metadata, access logs, and audit trails all support chain of custody of ESI by documenting how evidence was preserved, handled, accessed, and transferred. Detailed records help demonstrate that the data’s authenticity has been reasonably maintained.

Metadata can provide important information about digital files such as who created them and when, and whether/when they were modified. In chain of custody, metadata helps prove continuity of handling and data integrity.
Access logs typically record who interacted with the hosting environment such as a SharePoint site or a Gmail inbox, including who viewed, copied, or modified data. In chain of custody, this can demonstrate that only authorized users handled it.
Audit trails can track the movement of data from ingestion through production. Because they provide information about the who, what, when, and how regarding interaction with data, audit trails provide defensibility.

For today’s legal and ediscovery professionals, one of the biggest challenges is the exponential proliferation of electronic data, as well as new data types and formats. Manually tracking of novel data types such as ephemeral messaging, Slack threads, or Teams messages is nearly impossible. If a legal team cannot demonstrate that such novel and ephemeral data types entered into evidence are authentic and validated by a clear chain of custody, that evidence may be challenged by opposing counsel. To ensure admissibility in court, legal teams need to provide a continuous, defensible history of the data’s life cycle.

What Happens if the Chain of Custody Is Broken?

A broken or incomplete chain of custody can raise questions about the integrity and authenticity of digital data and the unassailability of its handling. This can lead to its exclusion from trial and jeopardize case outcomes.

Gaps can come in various forms. If a legal team transfers files from a laptop using email or unsecured cloud storage without thorough documentation, the opposing side can question whether the files were modified during the transfer, or whether the data set is complete. Such gaps can undermine confidence in the evidence.

The chain can also be broken after collection. If various team members access or modify files outside of controlled workflows the resulting discrepancies between document versions won’t be easily explained. The resulting uncertainty opens the door to challenges from opposing counsel and can plant doubt in the jury’s mind.

Understanding the Consequences of a Broken Chain of Custody

Although the Federal Rules of Civil Procedure, or FRCP, do not cite chain of custody requirements for digital evidence, the importance of the concept is relevant under the rules governing authentication and spoliation. Not adhering to these can lead to legal and financial consequences and impact case outcomes.

While every jurisdiction handles these failures differently, the consequences generally fall into three categories of risk: admissibility challenges, reduced weight, and increased scrutiny.

Direct Evidence Challenges and Inadmissibility

The most immediate consequence of an incomplete chain of custody is a challenge to admissibility of evidence. If a party cannot prove the integrity of the evidence from the moment it was gathered to when it’s presented at trial, the court may rule that the evidence is unreliable.

In the most severe cases, this leads to the total exclusion of the evidence. Without the continuous documentation, even a smoking gun email can be barred from trial, potentially collapsing a case’s foundational merits.

Reduced Weight and Credibility

Even if the evidence is technically admitted, a broken chain of custody can significantly reduce its weight or credibility in the eyes of a judge or jury.

Opposing counsel can use gaps in the record to sow doubt, suggesting that the data could have been altered, accessed by unauthorized parties, or improperly handled. Once the presumption of integrity is lost, the legal team must work twice as hard to regain the court’s trust as the focus shifts from the facts of the case to the failures of the process.

Increased Scrutiny

Gaps in custody can lead judges or juries to view evidence with skepticism. This can trigger additional litigation over the process including court-ordered forensic audits and depositions of IT and ediscovery personnel.

Under FRCP 37(e) and related case law, both sides of a dispute are required to take “reasonable steps” to preserve ESI or face spoliation sanctions. Courts pay close attention to how parties handle their preservation obligations. If gaps suggest data may have been lost or altered, the court may even issue adverse inference instructions, monetary sanctions, or other remedial measures.

Once custody becomes a point of contention, the opposing side can shift attention away from the merits of the evidence toward procedural vulnerabilities. This can weaken a legal team’s negotiation position, complicate settlement discussions, and affect perceptions of the case overall.

From Understanding Chain of Custody to Defensible Ediscovery

Understanding the core chain of custody principles helps teams strengthen defensible ediscovery workflows. This is particularly true in criminal investigations or when forensic collections are involved. By documenting who collected evidence, how it was preserved, and how it was transferred or processed, legal teams can demonstrate the integrity of the data from collection through production.

A record of a continuous chain of custody helps establish both admissibility and authenticity of the evidence. It also mitigates against claims of spoliation – or the destruction or alteration of evidence once litigation is a possibility.

Modern businesses and individuals generate vast amounts of electronic data, making manual approaches to documentation and ediscovery unrealistic. Audit trails (which can log every action on a file such as when it was opened, deleted, etc.) and metadata (which may provide context such as who created a file, when and how it was modified) — both important tools to establish the authenticity of digital evidence.

Teams often rely on computer forensics experts, who employ specialized tools and techniques to recover, authenticate, and analyze digital evidence following strict chain-of-custody protocols.

Custody as a Component of Discovery Planning

Defensibility is strengthened when the chain of custody is built into broader ediscovery planning. This begins long before a single file is collected. Early strategic decisions shape how custody will later be documented and how the authenticity of the evidence can be demonstrated under scrutiny. For example, defining metadata requirements in an ESI protocol or selecting a review platform with strong auditability directly influences whether legal teams can trace how data was handled, accessed, and preserved throughout the matter.

When custody considerations are built into the overall strategy, they shift from a potential point of risk to a sign of disciplined practice. Chain of custody becomes the traceable record that connects evidence from its source through review and production. By prioritizing transparency and using systems that preserve audit trails and handling history, legal teams reduce the likelihood of spoliation disputes and keep the focus on the substance of their case.

For further guidance on building a defensible process, refer to The Everlaw Guide to Ediscovery.

Dinsmore & Shohl + Everlaw

2026-04-26T08:35:44Z

Dinsmore & Shohl + Everlaw

How Dinsmore & Shohl Engineered a 98.2% Recall Rate in High-Stakes Cyber Contract Review Using Everlaw

2026-04-26T08:35:44Z

How Dinsmore & Shohl Engineered a 98.2% Recall Rate in High-Stakes Cyber Contract Review Using Everlaw

Combining Coding Suggestions and Predictive Coding for Near-Perfect Recall

by Gina Jurva

Reading Time — 5 minutes

March 24, 2026

To rapidly review over 26,000 contracts in a cyber incident response, Dinsmore combined search, Everlaw^AI Coding Suggestions, and Predictive Coding—improving performance at each step. That layered approach pushed recall from 92% to 98.2%.

When a cyber incident hits, contractual notice obligations are absolute. Either every required counterparty is notified or the organization faces additional exposure for breach of contract.

This reality confronted the client of national law firm Dinsmore & Shohl, who then needed to rapidly review 26,000 contracts to identify every clause requiring notification of a security incident. A manual review was impractical. Time, cost, and risk made it untenable.

The legal team needed a smarter path. Together Peter Pepiton, Ediscovery Director, and Jennifer Mitchell, health care privacy and cybersecurity partner, worked in collaboration with the client, to develop a process that was thorough, defensible, and cost effective. Dinsmore turned to Everlaw’s platform to build a layered strategy. The firm stacked three different technologies: search, generative AI, and Predictive Coding, and then validated each step to build a foundation of institutional trust.

Here is how they built a workflow that achieved a 98.2% recall rate.

Why 80% Wasn’t Good Enough

In standard litigation, recall thresholds are often negotiated by the parties. Cyber incident response operates differently.

“When you're talking about notifying counterparties to whom you have a contractual obligation… 80% doesn't really do it," Pepiton explained. "You have to be substantially north of that."

The challenge wasn’t volume alone. It was the variability of the clauses. Pepiton described it: "The language can be tough, it can be hidden, it can be vague. Three people can look at it and come to different conclusions. But we had to notify all the counterparties."

In this context, they needed the confidence that they'd caught virtually everything.

The Method: A Layered Approach

Rather than relying on a single tool, Dinsmore built what Pepiton calls "a trimodal approach". Using different Everlaw technologies, search, Coding Suggestions, and Predictive Coding, they created three sequential filters, each designed to deliver improved accuracy at every phase.

Each layer served a distinct function. Each was validated before moving to the next.

Phase One: Strategic Search

The first step was straightforward culling. Using Everlaw's search capabilities, the team eliminated drafts, duplicates, and irrelevant documents to reduce noise before applying more advanced tools.

"First we went at it with search and figured that we could get rid of lots of drafts of the contracts and just wind up with final versions," Pepiton said. That simple step eliminated approximately 20,000 contracts, according to Pepiton, reducing the reviewable population before deploying AI and Predictive Coding.

Phase Two: Everlaw^AI Coding Suggestions

Next the team deployed Everlaw's Coding Suggestions, a generative AI tool that automatically classifies documents based on the team’s customized criteria. Operating off a team’s specified case description, code categories, and individual code descriptions, Coding Suggestions rapidly analyzes document sets to suggest whether or not an individual document matches that criteria, outputting nuanced recommendations with written justifications for every suggestion.

Attorneys, not technologists, drafted the instructions. They defined what constituted a notification clause in the context of a cyber incident, identifying relevant phrases and provided examples of generic confidentiality language that would not be responsive.

Then, they created a training set.

"We took a sample of 120 documents and had Jen's team review them to identify which ones contain notice provisions that required us to notify and which ones didn't," Pepiton explained.

After validating Coding Suggestions’ initial performance against that ground-truth set, the team ran Coding Suggestions across the full set of final contracts. The first pass achieved approximately 92% recall; impressive by typical discovery standards, where manual review often tops out at 80% recall. For Mitchell, the goal was to push recall even higher.

The team ran Coding Suggestions two more times on the same contract set. The subsequent passes captured additional agreements requiring notification, thereby improving recall by just over one percentage point.

"Given the number of potential contracts we knew we wanted higher recall" Mitchell said. "So we went back to continue iterating. "

While 92-93% recall would satisfy most discovery obligations, it wasn't enough for incident response. With 26,000 contracts in scope, even small percentage improvements can have an outsized impact.

Phase Three: Predictive Coding as the Final Layer

The decisive step came with Predictive Coding.

By this stage, the team had something critical: a substantial set of documents analyzed by AI and validated through human review. That dataset was used to train a traditional Predictive Coding model within Everlaw.

Predictive Coding relies on machine learning to identify patterns in prior coding decisions, then scores documents based on how similar they are to the training examples, identifying which are more or less likely to align with past determinations. It's exceptionally good at surfacing clauses with unusual phrasing or buried placement.

The final layer provided an additional level of precision, capturing even more critical data points by building on the AI’s initial findings.

After running the model and conducting formal statistical validation, the team reported a 98.2% recall rate.

This metric provided the mathematical confidence and defensibility the situation demanded. At that point, Mitchell, as the attorney responsible for the outcome, made the call: "I think we're in a good enough spot."

The journey from 92% to 98.2% recall was the difference between already superior performance and a near-perfect outcome.

How the Tools Worked Together

Each technology served a distinct purpose. Search provided broad culling. Coding Suggestions excelled at pattern recognition based on natural language. Predictive Coding captured conceptual similarities based on the initial documents identified by generative AI. Together, they created a comprehensive filter.

Pepiton uses a vivid metaphor to explain the strategy, “By using these various tools in sequence, we constructed a net with smaller and smaller holes to make sure fewer and fewer things are going to fall through."

The Critical Step: Human-in-the-Loop Validation

Pepiton’s philosophy is simple: "Validation cures all."

After each phase, the team ran validation samples. Attorneys manually reviewed sample sets of documents from both the “requires notice” and “does not require notice” groups to measure how the tools were performing. They compared the AI’s determinations against human judgment to calculate precision and recall and decide whether adjustments were necessary before moving forward. Was the AI understanding the prompt? Were the results consistent? Was it safe to proceed to the next phase, or did they need to adjust?

In the Predictive Coding phase, a final round of sampling confirmed 98.2% recall: a threshold Mitchell felt comfortable defending. The technology wasn’t operating unchecked. Every step was tested before it advanced.

Moreover, for Mitchell this structured “human-in-the-loop” approach was the crucial link, enabling advanced technology to deliver value in a matter with such high risk. “I don't know that I'll ever be comfortable if I don't have some involvement in the process,“ she said. “I don't think it's ever something that I would turn over completely to AI".

What This Actually Achieved

The immediate outcome was confidence: the client could move quickly to notify counterparties knowing obligations were met. But the benefits extended further, starting with cost.

“It saved the client a lot of money,” Mitchell said.

Cost Control and Predictability: The firm avoided the open-ended expense of manual review, replacing it with predictable investment in technology and senior oversight. By Dinsmore's estimates, a manual review would have required approximately 260 attorney hours; more than six weeks of full-time work.

Strategic Resourcing: Associates and paralegals were freed from manual document review and redeployed to higher-value work such as incident response strategy, drafting notifications, and advising on next steps.

A Reusable Blueprint: This matter was not a one-off experiment. It proved a protocol. Dinsmore now has a documented, defensible playbook for any large-scale, pattern-based review, whether for compliance audits, merger due diligence, or other investigative work. The learning curve for the next case is gone.

Client Trust Through Transparency: Transparency regarding technology use served to align the firm’s incentives with the client’s goals, fostering a deep-seated trust that the objective, certainty, was being met efficiently and defensibly.

Precision Through Process

The Dinsmore case demonstrates what advanced technology can achieve when embedded in a disciplined legal workflow. By layering Everlaw’s tools strategically and validating every step through a rigorous human-in-the-loop process, the firm turned 26,000 contracts into a 98.2% recall rate.

Ultimately, this workflow did more than find clauses; it replaced the uncertainty of manual review with the absolute confidence of a validated result—transforming a high-stakes risk into a defensible standard of certainty.

NAAG + Everlaw

2026-04-26T08:35:44Z

NAAG + Everlaw

How State Attorneys General Offices Are Closing the Technology Gap

2026-04-26T08:35:44Z

How State Attorneys General Offices Are Closing the Technology Gap

How State Attorneys General Offices Are Closing the Technology Gap and Why It Matters

2026-04-26T08:35:44Z

How State Attorneys General Offices Are Closing the Technology Gap and Why It Matters

by Gina Jurva

Reading Time — 4 minutes

March 23, 2026

Stephanie Caldwell has spent her career in two roles: 17 years as a civil litigator at the Nebraska Attorney General's office, followed by nearly four years training Attorney General offices nationwide as Senior Counsel at the National Association of Attorneys General (NAAG).

That combination gives her a rare perspective. She's lived the challenges of the public sector – including budget constraints, staffing turnover, and red tape – and now helps AG offices navigate those obstacles while keeping pace with better-resourced opponents.

The gap between what the public sector needs and what it can access is real. But it's closing.

The Challenge: Doing More With Less

AG offices face unique constraints. Unlike private firms that can quickly purchase new platforms, government offices navigate procurement boards, budget cycles, and privacy regulations.

"Lawyers in the public sector are going to have more challenges," Caldwell explained. "We're dealing with things like budget constraints, staffing issues, and just limited availability to certain types of resources."

The workload hasn't shrunk. AG offices handle everything from consumer protection to multi-state litigation, often dealing with massive data sets spread across jurisdictions.

"We don't get to choose our cases that come to us in the public sector," Caldwell said. "We don't get to choose our facts. We don't get to choose our documents or our witnesses."

The question: How do you handle that volume with limited staff and budget? The answer: legal technology.

Why Technology Became Essential

For years, litigation platforms like Everlaw felt like nice-to-haves for government offices; things the private sector could afford but the public sector couldn't justify. That's changed.

"State attorney general offices are now realizing that these types of tools, things like generative AI or other technologies that are out there, are not so much a luxury anymore," Caldwell said. "They are really a necessity."

When staffing is limited and budgets are fixed, the only way to do more is to work faster and smarter. The discovery process, in particular, has been significantly transformed. Tasks that used to take weeks like processing large volumes of documents, reviewing for privilege and coding for relevance, can now be done in days.

"What used to take days, weeks, months, massive amounts of time can be so dramatically streamlined with the use of technologies that are out there," Caldwell noted.

But it's not just speed. It's quality. "This technology is out there, and it's not going to replace attorneys, but it's going to enhance them. It's going to make them better."

What Actually Matters When Adopting Tools

Through her work with AG offices, Caldwell has identified what matters when government offices evaluate new technology platforms.

Education. Many people hear "AI" and aren't sure what it means – or what it means to their work. Showing them specifically what the technology can do makes the difference. "What is vital and what is important is education, training, and information," Caldwell said.

Return on Investment. Government offices need to justify expenditures with specific value. "This product or this platform, this technology is going to save a certain amount of hours. You are now able to process 50,000 documents in a span of 24, 48 hours, versus what it would have taken in the past."

Security and Privacy. This is non-negotiable. AG offices handle citizen data, taxpayer records, confidential documents. "What's also important in the public sector is giving stakeholders that confidence," Caldwell said. "That confidence is important to let them know that whatever we're using, whatever tool it is, it's going to still ensure that we have privacy and security."

Real Impact: How Everlaw Changed the Workflow

Many AG offices, particularly in consumer protection divisions, now use Everlaw through their connection with NAAG. "A large majority of them use Everlaw, especially when it comes to their consumer protection cases because they have a connection with them through our organization, and we're able to provide them access," Caldwell explained.

The impact has been significant. Caldwell has heard from states that Everlaw has "completely changed the landscape of how they handle a case from beginning to end." Multi-state litigation can now be managed in cloud-based systems where teams collaborate in real time.

We have duties as well as attorneys to keep up to date with the latest trends and technologies. We're meeting that ethical obligation, but we're also meeting that public sector obligation that we have to the public in general to get these cases done.

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"That's my favorite part of working in the legal profession and especially in the public sector, is that ability to collaborate," Caldwell said.

Specific features have proven particularly valuable. States have given "really good feedback about the generative AI features, some of the Deep Dive features" where attorneys can ask the platform questions about their case directly. Deposition summaries, which used to consume hours, can now be automated.

"To be able to use that document summary where we can have then a platform go in, summarize a deposition and provide that to our client, it's amazing and it's incredibly invaluable," Caldwell said.

Tools like Storybuilder help develop and prove out potential case theories, a concept NAAG trains on extensively. "What is your theory of the case? How are you going to sell it? How are you going to show the fact finder what the case is about?" Caldwell explained. Finding the key documents to tell that story becomes possible even when dealing with massive data sets.

Cloud migration has been another game-changer for preservation. Instead of emailing legal holds and hoping clients comply, attorneys now have direct access to cloud systems. "It's a much easier way for the teams to then come together, work through it, see what is all out there, and then process it."

The Stakes Are High and Personal

The work AG offices do matters. These are more than cases—they're investigations, prosecutions, and civil actions that affect real people.

"There are real individuals behind a lot of these cases that are waiting on outcomes," Caldwell said. "Individuals that might have been named in a lawsuit, individuals that are subject of an investigation. We want to ensure we can give them the best outcome."

That urgency is why technology adoption isn't optional. It's part of meeting ethical obligations and serving the public effectively.

"We have duties as well as attorneys to keep up to date with the latest trends and technologies," Caldwell noted. "We're meeting that ethical obligation, but we're also meeting that public sector obligation that we have to the public in general to get these cases done."

The gap is closing. AG offices are embracing tools like Everlaw that streamline their work, protect sensitive information, and free up attorneys to focus on strategy and storytelling rather than administrative drudgery. The ones leading that charge are proving that government legal work, done well, can set the standard.

Simplify DSAR Responses with Time-Saving Technology

2026-04-26T08:35:44Z

Simplify DSAR Responses with Time-Saving Technology

See How Everlaw^AI Helps Surface Crucial Data

by Petra Pasternak

Reading Time — 9 minutes

March 23, 2026

Organisations that approach data subject access requests, or DSARs, as routine administrative obligations may be underestimating their growing cost and risk.

Recent legal and regulatory developments are raising the bar for compliance, reshaping organisations’ response to DSARs and other disclosure requirements.

The Data (Use and Access) Act 2025 (DUAA), updated guidance from the Information Commissioner’s Office (ICO), and pivotal case law such as Ashley v HMRC [2025] EWHC 134 (KB) ("Ashley") introduce strict new procedural and transparency requirements. This leads to increased expectations around how organisations scope, search, and justify their responses.

At the same time, DSARs increasingly arise in litigation, employment disputes, regulatory scrutiny, and internal investigations. In employment disputes in particular, DSARs are more frequently used to obtain information before formal claims are filed, making them an early indicator of potential litigation. Expanding data volumes across collaboration platforms and cloud systems are also making it far more difficult to find and review personal data.

Together, these developments mean that DSAR responses increasingly resemble early-stage disclosure, where teams must identify relevant custodians, search across multiple systems, review large volumes of material, and apply statutory exemptions, all within strict regulatory timelines.

For data protection officers, privacy counsel, and compliance leaders, DSARs can no longer be handled simply as a compliance exercise. To protect their organisation, teams need clear scoping, defensible workflows, documented decision-making, and close coordination with other departments. For some teams, that can require a strategic overhaul of internal DSAR procedures.

A Unified Platform Powers Better Team Collaboration

As DSARs grow in volume and legal complexity, it is clear that traditional, often manual, approaches simply cannot scale. But the answer isn’t another niche point solution. Legal and compliance teams need a platform built for cross-functional collaboration, with enough flexibility to handle everything from routine privacy requests to high-stakes investigations and litigation.

Everlaw eliminates potential friction between HR, legal, and IT. Native features, like shared workspaces with role-based access and simple document sharing, remove the traditional handoff delays that stall reviews. When a complex DSAR requires a second, independent pair of eyes because of anticipated employment litigation, in-house teams can invite outside counsel to collaborate within the same secure environment in real time.

Getting the right people into the platform is one key step; the next is giving them the analytical tools to spot what actually matters within the data. Everlaw’s intuitive GenAI features and AI-powered visualisation tools help surface key patterns and relevant data, and reduce manual effort and the time it takes from review to response.

Addressing New DUAA, ICO, and Case Law Guidance with Everlaw

The DUAA codifies a number of practical flexibilities that were previously only available in ICO guidance or common law, the updated ICO guidance (running to 124 pages) tightens transparency rules, whilst recent case law presents some important takeaways.

Some non-exhaustive examples of these highlights, and how Everlaw can help with these, include:

1. The Reasonable and Proportionate Search Standard

Section 78 of the DUAA explicitly codifies that controllers are only required to conduct “reasonable and proportionate” searches. You no longer need to leave no stone unturned.

When justifying why a deeper or broader search is disproportionate, the updated ICO guidance states you may now explicitly rely on the volume of information that needs to be searched, alongside the circumstances of the request, search difficulties, and the fundamental right of access.

The language around burden of proof has also shifted slightly here; you must be able to show and document why a search is disproportionate, rather than merely justifying it.

Ashley provides additional guidance here; a holistic, potentially organisation-wide search approach is required, notwithstanding internal operational boundaries or departmental silos. If data is held elsewhere in the corporate structure by the same controller, it must be searched, and it does not render the request disproportionate. You are however also legally allowed to factor in the time it takes to review, redact, and apply exemptions to the data, not just the time it takes to run the initial search query, which is significant for organisations responding to more complex DSARs.

How Everlaw can help:

Everlaw^AI Deep Dive: When calculating if a cross-departmental search is disproportionate, you can use Deep Dive to instantly interrogate organisation-wide datasets using natural language in Everlaw, at scale if necessary. This can help to immediately surface the true volume and complexity of the data, to provide a basis for the metrics you need to help you document your “burden of proof.”
Everlaw^AI Coding Suggestions: By automating the first-pass review across as many documents as you need to review, Coding Suggestions can help to significantly reduce the time and effort required to review, produce and (where appropriate) exempt data, potentially shifting the bar on what constitutes a “disproportionate effort.” Importantly, if you are not using a tool like Everlaw, you are at risk of falling on the wrong side of the proportionality line if these questions arise from the regulator or courts.
Standard Everlaw functionality: Core Everlaw features, in themselves a revelation to those currently stuck with manual processes, underpin and reduce the cost of more advanced techniques. This business-as-usual functionality includes automatic deduplication, imaging and email threading, metadata filtering (e.g. by date, by parties etc.), blink-speed searching, and pre-configured data visualisations.

2. Intelligibility

The ICO has continued to stress that data must be provided in a concise, transparent, intelligible, and easily accessible form.

In Ashley however, HMRC provided heavily redacted documents where only Mr. Ashley's name or initials were visible, stripping away all surrounding text to protect third-party or non-personal data.

The court ruled that providing heavily redacted, incomprehensible data outputs was a breach of the rules; you must leave enough surrounding non-personal data, or provide a separate contextual summary, so the data subject actually understands what the document is about.

How Everlaw can help:

Everlaw^AI Document Summaries: Instead of spending hours manually drafting contextual narratives for heavily redacted files, EverlawAI can instantly generate clear, citation-backed summaries of the underlying documents. This provides a ready-made, intelligible summary that can help to satisfy the Ashley requirements without revealing the protected third-party data.
Everlaw^AI Custom Extractions: You can prompt Everlaw to automatically extract the data subject’s name whenever it appears, in addition to providing surrounding salient information to help you meet intelligibility requirements.
Extraction vs Redaction DSARs: Everlaw supports both extraction-type DSARs, and redaction-type DSARs.
- For extraction-type DSARs, data is extracted as opposed to redacted documents being produced. The format of this extraction provides flexibility in respect of your workflow, helping you to satisfy intelligibility requirements.
- For redaction-type DSARs, Everlaw provides you with powerful tools out of the box, including batch redactions, and the automated identification (and subsequent batch redaction) of personal data such as email addresses.
- Redaction stamps can also help to label exemptions visibly on the face of documents; when paired with batch redactions, they can significantly reduce work effort and provide insight safely and easily to data subjects on the face of the documents they have received. Notes can also be made against redactions, which whilst not visible on the face of the document, can be produced if desired or required.

3. The Scope of Personal Data in Business Disputes

The DUAA maintains the core definition of personal data, but requires controllers to be highly accurate in identifying it before applying exemptions.

In Ashley, HMRC argued that valuations of commercial properties owned by Mr. Ashley were not his personal data because they were data about objects (buildings), not a person. The court disagreed; in summary, it was held that data related to corporate assets, business initiatives, or financial instruments potentially crosses the threshold into personal data whenever it serves to assess the individual’s actions, liabilities, or workplace performance.

How Everlaw can help:

Everlaw^AI Deep Dive: Reviewers can simply ask Deep Dive to identify documents evaluating the employee’s actions, liabilities or workplace performance. Deep Dive will bypass corporate jargon and instantly surface examples of documents where business data crosses the threshold into personal data, and provide natural language analysis around this. The responses of these questions can then be iterated upon, or further search criteria can be determined if an exhaustive trawl is required.
Everlaw^AI Custom Extractions: You can configure Everlaw to automatically extract the data subject’s name whenever it appears near specific business concepts (e.g., financial metrics, HR disciplinary terms etc.), helping you to more precisely identify data that has potentially crossed the threshold.
Everlaw^AI Coding Suggestions: Coding Suggestions can be drafted using natural language to identify documents fitting the criteria you have set out, reducing the lift involved in a traditional document by document review, through an AI-powered batch process.

4. Applying Exemptions

The DUAA entrenches, refines and clarifies various statutory exemptions, including Legal Professional Privilege (“LPP”). When applying exemptions, the courts are taking a strict approach. In Ashley, HMRC tried to apply a broad “tax exemption”, but the ruling requires you to document a highly specific, tangible link to the prejudice or harm that would occur if the data were released, not blanket speculation, which will be struck down by the courts.

How Everlaw can help:

Everlaw^AI Coding Suggestions: You can establish custom criteria to automatically flag potential LPP or other exemptions requiring redactions or withholding of documents. Everlaw^AI Coding Suggestions are as flexible as your working methodologies, letting you avoid the unnecessary rigidity of other solutions on the market.
Everlaw^AI Deep Dive: When you need to justify withholding a class of documents, you can ask Deep Dive to help you summarise the specific risks, privilege or commercial sensitivities contained within those documents. You can then refine that response in a fully editable Storybuilder Draft. This helps to give your team the document-specific evidence required to demonstrate the strict approach required. It can also help to highlight and facilitate your rectification of any issues identified in your approach, in advance of sending out the documents to the data subject.

5. Format Demands and Repetitive Requests

The ICO clarifies that providing data via a secure portal in a commonly used electronic format satisfies your obligations in most instances. The requirement may also be satisfied by giving the data subject remote access to their information on a secure system. However, they will also need to be able to download a copy of the requested information in a format that is accessible to them.

Linked to these concepts is the scenario where a data subject downloads their data but repeatedly demands the same information in different formats. Under the guidance, you may now formally treat these subsequent requests as “manifestly unfounded or excessive”, allowing you to potentially refuse them, or charge a reasonable administrative fee.

How Everlaw can help:

Everlaw^AI Deep Dive: If requests are similar but not identical in terms of search criteria and scope, you can use Deep Dive to help you to verify that the repeated request would not indeed result in additional documents needing to be provided. Conversely, if you do conclude that additional disclosures are required, Deep Dive can help you to minimise the impact of this task.
Fully Integrated Productions: Everlaw’s easy to use, wizard-driven production tools allow you to instantly package, format, and share data via secure, trackable links in standard electronic formats. This creates an audit trail of exactly what was provided, in what format, and when it was accessed, helping to give you the documented proof necessary.
Partial Projects with Granular Access: It is possible to also give secure, locked-down access to the curated set of data subject data in a partial project, whilst granular access protects your organisation’s DSAR exemptions (including third party data and LPP).

6. “Stopping the Clock”

The DUAA formalises the ability to pause the one-month statutory deadline when requesting necessary clarification or verifying identity, with the ICO guidance removing the previous condition that you must process a large amount of information about the requester to ask for clarification.

You can now pause the clock on any request where clarification is genuinely required to provide an effective response. This must however be done in a timely manner, with ID and clarification requested as soon as possible, not at the end of the statutory period. It must also not be a routine stalling tactic; you must be able to document why the specific request was unclear and why you genuinely needed more information to proceed.

How Everlaw can help:

Everlaw^AI Deep Dive: When a vaguely worded DSAR request arrives, you can use Deep Dive to rapidly sample the raw data. It can help you to investigate, for example, the different contexts in which a data subject’s name appears. This can help your team to rapidly surface supporting evidence to revert to the requester with, to help justify why clarification is genuinely needed to proceed, and provide you with the factors to help justify pausing the clock.
Data Visualizer & Clustering: Everlaw’s visual dashboards can help to instantly map out a data subject’s footprint. Documenting that their name, for example, spans multiple departments and years helps to provide quantifiable proof to justify why a broadly worded request requires narrowing down before work can begin.
Search Term Report (“STR”): Running rapid STRs on the requester’s requests and/or their known identifiers helps to rapidly quantify the volume of potential hits. Reverting to a requester with concrete metrics is a highly effective way to help document the scale of a vague request.

Integrated AI for Workflows That Accelerate Review

As set out above, Everlaw^AI is fundamentally changing how investigatory, regulatory, and legal work is done. But too many platforms stitch hastily fabricated AI add-ons to their basic tool set rather than create a genuine AI-enabled solution.

Rather than fall into that legacy mindset, Everlaw applies a more holistic perspective that integrates AI and advanced analytics across the entire platform. This allows organisations to tailor their approach, with some adopting an AI-first approach while giving those who are just starting their AI journey to keep more traditional workflows that are powered by automations and optional AI. The result for legal and compliance teams is a unified search, review, and redaction experience.

This makes everything from DSAR scoping to prioritisation and extraction simpler and more efficient. Teams working on DSARs can capture every decision (for example, why a document was tagged relevant, why a redaction was applied, or why certain data was excluded) automatically using audit trails, which provide defensible answers, not just confidence scores.

A structured approach helps ensure that an organisation can justify which data it included if challenged in proceedings. It also puts your team at an advantage should a routine DSAR request evolve into a dispute.

Handling DSARs and Other Matters in a Single Platform

Many organisations opt to, maybe inadvertently, treat DSAR requests like a one-off task relying on traditional approaches, rather than part of a larger organisational strategy. This creates unnecessary risk.

When DSAR workflows are managed in disparate tools, teams run the risk that a search is incomplete or that siloed teams are duplicating efforts. Limited visibility across related matters can create compliance exposure while also making it harder to identify when a request is a precursor to litigation.

In a typical people, process and technology scenario, technical efficiency for organisations of any size comes from a unified platform. For larger corporations, and the external advisors that assist them, by managing DSARs in the same environment as legal holds, investigations, and litigation matters, teams eliminate the friction of navigating between disconnected systems (known as the “toggle tax”). It helps keep everyone on the same page and collaborating with greater transparency and timeliness.

With Everlaw’s unified environment for investigation, regulatory, and litigation workflows, teams aren’t just fulfilling a request, they’re building a strategic response and reducing risk.

Learn more about how Everlaw’s AI capabilities can support your DSAR workflow.

Center for Justice & Accountability + Everlaw

2026-04-26T08:35:44Z

Center for Justice & Accountability + Everlaw

How Dinsmore & Shohl Engineered a 98.2% Recall Rate in High-Stakes Cyber Contract Review

2026-04-26T08:35:44Z

How Dinsmore & Shohl Engineered a 98.2% Recall Rate in High-Stakes Cyber Contract Review

Ediscovery vs. Digital Forensics: Key Differences Explained

2026-04-26T08:35:44Z

Ediscovery vs. Digital Forensics: Key Differences Explained

by Justin Smith

Reading Time — 8 minutes

March 12, 2026

In an age when a single legal matter can span millions of files, the ability to distinguish between the broad reach of ediscovery and the narrow precision of digital forensics has become a prerequisite for effective litigation. The volume of electronically stored information (ESI) continues to grow exponentially, meaning legal professionals must navigate a complex web of technical disciplines to find the truth.

Two of the most prominent fields in this arena are ediscovery and digital forensics. While the terms are occasionally used interchangeably in casual conversation, they represent distinct methodologies with different goals, tools, and standards of success. Understanding the distinction between a legal process (ediscovery) and a technical investigation (forensics) is critical for ensuring data integrity, managing costs, and meeting judicial expectations.

At a high level, ediscovery is the systematic process of identifying, collecting, and reviewing ESI for production in a legal dispute. Conversely, digital forensics is a specialized technical discipline focused on the recovery and analysis of digital evidence in its native, often hidden state to answer fundamental questions of how, who, or when.

For example, consider a pharmaceutical company investigating a scientist suspected of leaking a proprietary formula. An ediscovery team would search the scientist's emails and OneDrive for any documents containing the formula or communications with a competitor. However, a digital forensics expert would investigate the laptop's system logs to see if the scientist wiped their browser history, or if they accessed the formula from an incognito window to bypass standard corporate monitoring. While ediscovery finds the document, forensics finds the intent and the action.

What Is Digital Forensics in Legal Matters?

Digital forensics is a branch of forensic science that focuses on the recovery and investigation of material found in digital or mobile devices. Although it’s typically associated with cybercrime investigations, in the context of legal matters, it is a highly technical discipline used to establish a scientific foundation for what occurred on a specific device or network.

Where ediscovery is often concerned with what a document says, digital forensics is focused on what a device did. For instance, in an investigation into the theft of trade secrets, a digital forensics expert might look to see if an employee plugged in an unauthorized USB drive at 2:00 a.m., copied the company’s client list, and then attempted to run wiping software to hide their tracks.

This field is frequently the domain of digital forensics experts—specialists who possess the training to handle fragile data without altering its state.

The Science of Investigation

Digital forensics goes beyond the active files a user sees on their desktop. It involves the use of specialized tools to perform forensic imaging, creating an exact replica of a hard drive, including its unallocated space. This allows investigators to see:

Deleted Data. Files that have been emptied from the trash but not yet overwritten by the operating system.
System Artifacts. Hidden logs that track when a computer was turned on, which USB drives were plugged in, or which files were accessed and when.
Application Residue. Fragments of data left behind by web browsers, chat applications, or cloud-syncing services.

Ensuring Data Integrity

One of the hallmarks of digital forensics is a relentless focus on data integrity. To ensure that digital evidence is admissible in court, experts use cryptographic hashing, which transforms data into a unique digital fingerprint. Think of a hash as a unique digital fingerprint generated by a mathematical algorithm that represents the exact state of a file or an entire hard drive at the moment of collection.

By generating this digital fingerprint, experts can prove to a court that not a single bit of information has been altered. Because these algorithms are incredibly sensitive, even a nearly invisible change—such as modifying a file's last accessed timestamp or adding a single space to a document—will result in a completely different hash value, instantly alerting investigators to potential tampering.

This level of rigor is essential in criminal investigations, trade secret theft investigations, and matters involving suspected evidence tampering.

What Is Ediscovery?

Electronic discovery, or ediscovery, is the process of sharing and reviewing ESI during discovery. It’s typically associated with civil litigation, and follows the path laid out in the Electronic Discovery Reference Model (EDRM), and focuses on the efficient movement of data from its original source to a final production set.

The types of electronic data considered as discoverable ESI are vast. They range from metadata and electronic documents to audio and video files. Even communication channels, such as emails, voicemails, instant messaging chats, and relevant information found on social media platforms or websites, fall under the ediscovery umbrella.

If digital forensics is a high-powered microscope used to examine a single slide, ediscovery is the map used to navigate a sprawling city of information.

The Role of Responsiveness and Metadata

The primary driver of ediscovery is potential relevance. In the Federal Rules of Civil Procedure (FRCP), Rule 26(b) defines the scope of discovery as any nonprivileged matter that is relevant to any party's claim or defense and proportional to the needs of the case. Adhering to this standard, legal teams must sift through millions of documents, including Slack messages, PDFs, and spreadsheets to find the specific communications that support or refute a legal claim.

In the ediscovery process, metadata plays a starring role. Metadata, or data about data, includes information such as the author and recipients of a message, timestamps showing when a document was created or sent, and the file path of where a document was stored on a company’s server.

Preserving this metadata is essential for complying with FRCP 34, which requires a party to produce ESI as it is kept in the usual course of business or in a reasonably usable form. Without metadata, a document often loses its context and searchability, making it difficult to satisfy the technical requirements of a production request.

Ediscovery platforms use this metadata to allow for high-speed searching and filtering. The goal is to reach a production-ready state where responsive, non-privileged documents are shared with the opposing party in a standardized format.

Privilege

While responsiveness is the engine of ediscovery, privilege acts as its essential guardrail. Even if a document is highly relevant to a case, it may be protected from disclosure under legal doctrines such as attorney-client privilege. Modern ediscovery platforms use advanced analytics to flag potentially privileged communications early in the review process, ensuring sensitive information stays protected.

To account for these withheld documents, legal teams must create a privilege log—a detailed list that allows the opposing party and the court to assess the validity of a privilege claim without seeing the protected content. By pulling directly from a file's metadata (such as author, date, and subject), ediscovery software can automate the generation of these logs, turning a historically burdensome manual task into a streamlined, defensible process.

Defensibility and Proportionality

Ediscovery is governed by the standard of reasonableness. In the eyes of the court, a defensible process is one that demonstrates the legal team acted in good faith to identify and preserve potentially relevant digital evidence. Defensibility is less about finding every single byte of data in existence and more about being able to explain the why and how behind your search. This requires a well-documented workflow—from the initial legal hold to the final production—supported by a clear audit trail.

Closely tied to defensibility is the principle of proportionality, which acknowledges a simple truth of the digital age: just because data exists doesn't mean it is fair or necessary to collect it all. Navigating proportionality is a strategic exercise. It involves looking at the amount in controversy, the parties’ resources, and the importance of the ESI in resolving the issues at hand. For example, a court may find it disproportionate to spend $50,000 on a digital forensics expert to recover deleted fragments from a legacy server if the total value of the legal case is only $100,000.

Key Differences: A Side-by-Side Comparison

To better understand how these two fields interact, it is helpful to look at them across several key dimensions.

Feature	Ediscovery	Digital Forensics
Primary Goal	Responsiveness, review, and production for litigation, as well as attorney-client privilege.	Investigation, recovery, and reconstructing events.
Data State	Active, accessible ESI (emails, documents, and cloud files).	Deleted, hidden, and system-level artifacts.
Primary Practitioners	Legal teams, paralegals, and document reviewers.	Digital forensics experts and investigators.
Technical Focus	Searchability, categorization, and metadata analysis.	Data integrity, recovery, and bit-level imaging.
Key Output	Productions, privilege logs, and redacted document sets.	Expert reports, timelines, and forensic images.
Primary Tools	Review and analytics platforms (e.g., Everlaw).	Specialized forensics tools for acquisition.

The Intersection of Cybersecurity and Forensic Investigation

In the modern corporate world, the responsibilities between legal, IT, and cybersecurity are increasingly interconnected. This is particularly evident during a data breach or an internal security incident.

When a cybersecurity incident occurs, digital forensics is the first responder. Specialists use their tools to determine the point of entry, identify which files were accessed or exfiltrated, and assess the extent of the damage. They should maintain a strict chain of custody to ensure that their findings can hold up if the incident leads to a lawsuit.

Once the immediate threat is neutralized, the matter may shift into an ediscovery phase if the company is sued by affected customers or investigated by regulators. The legal team must then use ediscovery workflows to identify and produce the internal communications regarding the breach. In this way, digital forensics provides what happened, while ediscovery manages the legal fallout.

Considerations for Law Firms, Corporations, and Government

The decision to utilize a forensic expert versus a standard ediscovery workflow depends heavily on the specific needs of the organization and the nature of the matter.

Law Firms: Strategic Choice

For law firms, the decision-making process often begins with the case theory itself: can the facts be established through active communications, or does the success of the matter hinge on proving intent through actions that have been hidden or erased? Attorneys must ask whether their current theory can be proven with only accessible files, or if the case depends on recovering lost evidence that requires specialized forensics tools to reach.

This choice is also a matter of professional responsibility. In an era of heightened technical competence requirements, attorneys must evaluate if they are risking data integrity by handling electronic devices without expert assistance. In high-stakes matters where the authenticity of digital evidence is likely to be challenged, the involvement of digital forensics experts can ensure that the data collection process is scientifically sound and beyond reproach.

Corporations: Bridging Silos

In the corporate world, the boundary between a routine cybersecurity response and a legal discovery obligation is often paper-thin. When a company experiences a data breach or an internal threat, the legal department must ask exactly where their technical security response ends and their legal discovery obligation begins.

If the security team is currently using forensic methods to find a vulnerability, will the data they gather hold up under the scrutiny of future litigation? Corporate leaders should think about whether they have the right protocols in place to transition from a quick security fix to a defensible ediscovery workflow without creating gaps in the chain of custody or losing vital metadata.

State and Local Government: Transparency and Resources

State and local agencies must constantly balance the public’s right to transparency with the reality of finite taxpayer resources. When facing a massive records request or a civil suit, the primary question is whether the burden and expense of a forensic deep-dive is proportional to the needs of the request. Is a reasonable search of active metadata sufficient to fulfill the agency's obligations, or does this specific matter require a level of scientific validation that only forensics can provide?

Because of limited budgets, government practitioners often focus on using scalable technology to prove that a good-faith search was conducted. They must ask if the search process is defensible enough to withstand a challenge in court, even if every single deleted fragment wasn't recovered. Unless a matter involves high-level criminal allegations or a high-profile civil rights claim, the focus is often on prioritizing active digital evidence and ensuring that the public's right to information is handled efficiently and within the limits of public resources.

Federal Agencies: Heightened Standards

At the federal level, expectations for data integrity and chain-of-custody are at their peak. Whether it is a regulatory investigation by the SEC or a criminal matter handled by the DOJ, federal agencies require a rigorous, documented process.

The central question for federal teams is whether their imaging and collection process meets the specific, documented validation requirements of federal oversight bodies. Does the workflow provide a mathematically verifiable account of the data's state from the moment of seizure? These agencies must think about how forensic findings are integrated into their broader review environment to manage massive volumes of ESI while ensuring that the digital fingerprint of every file remains intact throughout a multi-year investigation.

How Modern Ediscovery Platforms Support Forensic Data

It is a common misconception that legal teams must choose between using forensics tools or an ediscovery platform. In reality, the most successful investigations use them in tandem.

Modern ediscovery platforms are not designed to perform the initial bit-stream imaging of a hard drive—that remains the domain of the forensic specialist. However, once the digital forensics experts have carved the data and recovered deleted files, those outputs must be reviewed by attorneys for relevance and privilege.

Today, many legal teams opt for cloud-based ediscovery software, which allows them to keep all their data in-house and accessible from anywhere. It also comes with tools and features that allow attorneys to see data visually to display communication patterns, redact sensitive information, collaborate with others in real time, apply tags to privileged and relevant documents, and more.

A sophisticated ediscovery platform provides the environment where forensic outputs become legally actionable. It allows legal teams to:

Ingest Complex Data. Bring in forensic images or exports of system logs alongside standard Office 365 or Gmail data.
Analyze Timelines. Use the recovered metadata to build a comprehensive timeline of events, showing, for example, that an employee plugged in a personal hard drive minutes after receiving a termination notice.
Apply Advanced Analytics. Use AI and machine learning to find patterns in forensic data that might be invisible to a manual reviewer.
Support Defensibility. By housing all data in a single, secure environment, legal teams can maintain a clear audit trail of who accessed which file and when, further bolstering data integrity.

Conclusion

The choice between ediscovery and digital forensics is not an either/or proposition, but a question of scope and purpose. Ediscovery provides the framework for legal production and large-scale document review, while digital forensics provides the surgical precision needed to uncover hidden truths and verify the authenticity of digital evidence.

By understanding the unique strengths of each discipline—and how to integrate them into a single, cohesive strategy—legal professionals can move through investigations with greater confidence, lower risk, and a clearer path to the facts.

How London & Naor P.C. Leveraged Everlaw to Deliver Big Results with a Small Team

2026-04-26T08:35:44Z

How London & Naor P.C. Leveraged Everlaw to Deliver Big Results with a Small Team

by Justin Smith

Reading Time — 2 minutes

March 11, 2026

In the high-stakes world of civil litigation and white-collar defense, there is a long-standing myth that big results require big headcounts. The prevailing wisdom suggests that to manage terabytes of data or navigate complex litigation, a firm must deploy an army of associates. But for London & Naor P.C., a boutique powerhouse based in Oakland, California, the goal isn't to be the biggest—it’s to be the smartest.

Specializing in civil litigation, internal investigations, and white-collar defense, the firm serves a diverse client base that spans individuals, companies, and public entities. Their attorneys have decades of combined experience in government and private practice, and draw upon their know-how and technology to deliver high-quality legal services.

Shareholder and co-founder Ellen London brings an unusual combination of big‑organization and small‑firm experience to the practice, having spent roughly a decade as a civil‑side federal prosecutor in Manhattan and San Francisco before moving into private practice.

“My 10 years of practice showed me that just a couple of lawyers on a case can do a tremendous amount of work,” London said. “You don’t always need a large team on something to get results.”

The firm’s guiding principles emphasize empathy, practicality, and a deep connection with clients, which supports exceptional service from a lean and efficient platform.

Everlaw’s Force Multiplier Effect

This specific focus has helped Everlaw become an indispensable tool for the firm when it comes to managing complex cases with a small team.

“Using a technology like Everlaw acts as a force multiplier for us,” London said. “It allows us to efficiently ingest large quantities of data, search through it easily, and create productions without slowing down.”

This ability to get more work done relative to the size of their team has had a direct impact on London & Naor’s bottom line, helping them organize their documents quickly—whether that be creating binders for witness preparation or getting productions out the door in a timely manner.

“We had a very large, sensitive matter for a big client,” London said. “They were concerned that due to the size of our team and the amount of documents needing review, we weren’t going to be able to turn things around in time. And we were able to tell them that, thanks to Everlaw, we’re able to handle those large matters with the best of them.”

In fact, when prospective clients raise concerns about both team size and document volume, Everlaw is often part of the firm’s answer.

“If a client is curious about how we’ll approach a certain matter, we tell them: we know we’re small, but we have this many decades of experience, and we’ve handled very large matters,” London said. “One of the ways we keep things efficient and cost‑effective is that we’ve invested in a document platform that allows us to ingest, review, and produce documents extremely efficiently.”

Enhancing Confidence and Client Trust

Everlaw has played an important role in strengthening London & Naor’s ability to instill confidence in both their team and clients.

“I feel confident that we can handle cases with large volumes of documents effectively, and I can communicate that confidently to potential clients,” London said. “That confidence is critical in litigation.” This assurance builds client trust and helps the firm compete effectively when fighting for business.

London & Naor’s commitment to Everlaw has been a primary part of their firm’s technological journey. It’s helped them consistently deliver sophisticated, efficient, and reliable legal services, reinforcing a hard-earned reputation for excellence.

“Investing in Everlaw has never been something we wanted to cut, and we continually ensure it receives the investment necessary to stay ahead of the curve,” London emphasized.

Setting the Standard for Modern Boutique Firms

In an industry where change is the only constant, London & Naor proves that being a boutique firm is no longer a limitation—it’s a competitive edge. By pairing decades of elite litigation experience with a platform that eliminates downtime, they have successfully leveled the playing field against the largest firms in the country.

As they continue to navigate the evolving landscape of digital data and high-stakes defense, London & Naor stands as a model for the future: a firm where the quality of the insights, supported by the right tools, always outweighs the quantity of the staff.

London & Naor P.C. + Everlaw

2026-04-26T08:35:44Z

London & Naor P.C. + Everlaw

Judge Samuel Thumma on Generative AI, Closing the Justice Gap, and Keeping Humans in the Loop

2026-04-26T08:35:44Z

Judge Samuel Thumma on Generative AI, Closing the Justice Gap, and Keeping Humans in the Loop

by Justin Smith

Reading Time — 16 minutes

March 10, 2026

The legal profession stands at a profound inflection point. The arrival of generative AI has moved beyond theoretical curiosity, challenging long-held standards of attorney competence and the very mechanics of ediscovery.

As a member of the Arizona Supreme Court’s AI Steering Committee and a leader within the ABA Task Force on Law and Artificial Intelligence, Judge Samuel Thumma is at the center of this transition. He views this moment not merely as a technical shift, but as a once-in-a-generation opportunity to modernize a profession that is historically slow to change.

Judge Thumma’s perspective is informed by a distinguished career that bridges the gap between traditional legal pillars and the digital future. After working as an attorney at firms like Arnold & Porter and Perkins Coie, he has served as a judge on the Arizona Court of Appeals, Division One, in Phoenix since 2012, with terms as Chief Judge and Vice Chief Judge during that time. Throughout his tenure, he has become one of the judiciary’s most prominent voices on the intersection of law and technology, consistently advocating for a human-in-the-loop approach to innovation that preserves the integrity of the social contract.

Judge Thumma sat down with Everlaw to discuss the evolving landscape of modern legal practice. Our conversation explores the shifting responsibilities of practitioners in an automated world, how the legal community can leverage new tools to address the persistent challenges of the justice gap, and more.

Judge Samuel Thumma (Ariz. Ct. App. Div. 1)

You originally began your academic journey in veterinary medicine and agricultural journalism before moving into the law. Looking back, how did that background shape your approach to the bench, particularly when it comes to translating complex technical issues for the public?

I grew up on a farm. We grew corn and soybeans, and had a small beef cattle herd. This was in northwest Iowa out of a little tiny town called Laurens, Iowa, maybe 1,500 people. It does have the distinction of having a Disney movie made after it called The Straight Story, which was nominated for an Academy Award. But it was a very small Midwestern town, with 64 people in my high school class.

Even in a town of our size, we always had a veterinarian, and I found myself drawn to the practice of veterinary medicine. So I went on to Iowa State University, which was sort of a logical place to study to become a veterinarian.

I ran head on into organic chemistry and zoology in my sophomore year of college, and we didn't get along very well, which led to me changing my major, and really caused me to struggle for much of the year.

I was fortunate enough to be awarded a Truman Scholarship, which at the time gave me funding for two more years of undergraduate and then two years of graduate work. Harry Truman was the last president not to go to college, and Congress set up a fund in his name that still remains.

I was also very interested in agriculture. Iowa State offers a Bachelor of Science degree in agricultural journalism, which means you take a quarter of your credits in the Journalism school, a quarter of your credits in agriculture, and then a broader set of classes outside of that.

Once I had my degree, I needed to figure out what I wanted to do. I took some policy-level agricultural economics classes at Iowa State, and thought about going to graduate school for agricultural economics, but it didn't really offer the opportunities that I wanted to have at that time. So I ended up taking a year off through a U.S. Department of Agriculture exchange program in Australia called the IFYE program, which was more of a cultural exchange than an academic one, before going to the University of Iowa's College of Law.

Without that Truman Scholarship, I would not have become a lawyer, and could not have afforded law school.

My first goal was to not flunk out. The likelihood was that after graduating, I would go back home. We had a couple of lawyers in my town who were pillars of the community and terrific lawyers, one of whom our family used until he retired, and he was just a great, great lawyer.

But then I did okay in law school and had some opportunities to do other things, and ended up clerking for a couple judicial officers. I worked in private practice in Washington, D.C. at a firm called Arnold & Porter, and was dating my now wife of nearly 34 years, who was also a law school classmate, who had summered in Atlanta and Phoenix and liked Phoenix better of the two opportunities. So, that's why I've been in Phoenix for an awfully long time and loving it, but if you told me that my second year in law school, I would have laughed at you. That was not on my radar, but it's worked out well.

You’ve advocated for judges being active managers of the discovery process, not just passive observers. What is something you’re seeing from the bench that judges can do to take a more active role in discovery?

First, I want this to be a critique of me and the things that I can do better. I'm on the appellate court now and have been for almost 15 years, and was a trial judge before that for five years on two rotations that have nothing to do with civil litigation, or largely don't. One of those was juvenile, which is a major rotation here in the Maricopa County Superior Court, for three years, and then criminal for two years, where you're a genuine trial machine. I presided over maybe 35 felony jury trials during that two year period, ranging from aggravated assault to first-degree murder.

At that time at least, the disclosure and discovery in that realm was largely dealing with things like police reports, bales of marijuana, bricks of cocaine, guns, and things like that. So not the kind of high management things that you're talking about here.

In the civil realm, however, where I did my practice, the court philosophy in the last generation or two has really changed from, "Hey, we're the courts. We're here. We're open. You guys take all the time that you need to prepare your case, and then we'll try it when you're ready," to a more active management aspect where deadlines have meanings.

I also think there's a huge access to justice component to that because, especially in civil litigation, litigants are likely paying somebody by the hour to represent them. And from the court perspective as well as the advocate's perspective, every additional day that a case remains pending, there's an added cost to it.

That can be hard to quantify for the court. With a criminal trial, for example, you really appreciate that. Every additional day that a trial is delayed and someone who has not yet been found guilty is being held in custody, that's a big, big cost.

My view is always that, from the court perspective, when disclosure and discovery works the best, it’s comparatively invisible to the court until you get to trial. And that doesn't mean deadlines shouldn't have meaning, or that you shouldn't have court management of those deadlines. You need to be a careful listener when there are unique needs for a case, when deadlines need to be extended, and when accommodations need to be made, but not every case that fits that category.

There are general standards that we hope to meet, which I consistently see on our appellate court. We try to hit our marks with respect to resolving appeals, and recognizing that the standard is justice delayed is justice denied.

We need to keep that in mind as we do our best to move cases along to get prompt and hopefully fair resolutions for the parties that appear in front of us.

Ediscovery has long been one the most expensive parts of litigation. With generative AI lowering the cost of reviewing large datasets, do you think this will lead to more cases reaching trial, or will it just create a new arms race in pre-trial motions and an attempt to indefinitely delay trial?

Let me carve out the attempt to delay part of this, because I think it has the potential to result in a lot more pretrial motion practice.

My area of expertise was civil defense work. In an era where people wanted to be trial lawyers, I was never a trial lawyer. I was a litigator. My clients had not asked to be a party to the litigation. It was joined, and if I could allow my clients to just go home, life was better. So, we did a bunch of pretrial motion work there and had some successes.

My thought was if we go to trial, one of two things is going to happen, neither of which will be good for my clients. They’re either going to have to pay me a lot of money, or pay me and the other side a lot of money. And then depending on the ultimate result at trial, there’s a whole bunch of appeal work after that.

"I'm optimistic about generative AI generally in the sense that it can help enhance access to justice and help the courts figure out how we can do things better."

Share this quote:

So, I think generative AI absolutely has the potential to help on the trial side, but also with summarizing and collating and making sense out of disparate documents that span large amounts of time. When I was last practicing, a logical chronology was about as good as you could get, and now we're so much further beyond that. I do think there's an opportunity for more motion practice there. I think we are anecdotally seeing more motion work by self-represented litigants. And my hope is that's positive. Undoubtedly, at times it is and at times it is not, and that's where we need to fish through things.

As far as the trial rate, that's a really good question. I don't have a prediction or crystal ball on that. In my mind, if you can resolve matters early, even before they hit the courtroom and the parties are okay with that, that's better. But I just don't know, and time will tell.

You’ve written extensively about the potential for generative AI to help increase access to justice. What is something courts can do right now to leverage generative AI in this way, and how can they balance the potential for it to be misused?

Let me start with a couple of examples on how generative AI can help, particularly with self-represented parties.

One, I've been very critical of what I call dumb chatbots, which are the chatbots that were around five years ago that I always found frustrating. Courts were using them, and while they were using them for good reasons, I don't think they were very effective because for any question of any complexity, it was just a loop. You didn't really spin out of it.

I'm told by people that I trust and think highly of that these days, generative AI-driven chatbots are actually doing some good things. Nevada has been using a court-based chatbot, for example.

I'm on our AI steering committee for our state's Supreme Court, and I chair the access to justice work group for that. At our next meeting, we'll have some examples of chatbots that folks think are really helping self-represented litigants.

All the states that I know of have a process where somebody can be committed for mental health treatment when they're a danger to themselves or others, or have chronic mental health challenges. In Arizona, that commitment order can be for up to 365 days, half of which can be in custody. And while that's a civil proceeding, when you restrict someone's custody and liberty, that's a big deal.

In Indiana, those orders can only last 90 days. The Court of Appeals hears most of them. Their Supreme Court put some leadership in place to say, "How can we get those appeals to the appellate court so they can be resolved faster?"

In other words, if you have an appeal for a 90-day commitment order that's resolved six months after it was issued, and the court ends up ruling you never should have been committed in the first place, that's a pretty hollow victory. So there's a pilot program in Marion County, Indiana, where Indianapolis is located, where they have generative AI create a transcript of the hearing within hours of it concluding, so that those appeals can get processed quickly.

Judge Leanna Weissmann, who's a judge on the Indiana Court of Appeals, tells me that these days, with that pilot, they're getting commitment orders through final decision on appeal in 10 to 14 days, which is absolutely lightning fast.

And while I don't know what the results are on those appeals, I'm guessing if it's like in Arizona, a lot of those are affirmed. It’s great to get an answer so early in this 90-day commitment window, and I'm excited about that. And again, it's someone who is represented by counsel, by definition, but they're also kind of a ward of the state in that circumstance.

I'm very optimistic about both of those. And I'm optimistic about generative AI generally in the sense that it can help enhance access to justice and help the courts figure out how we can do things better, but I'm quick to concede that there's mischief that can happen.

I’m concerned about a scenario that many legal scholars have also raised. Imagine someone using generative AI to churn out housing complaints for tenants without a proper legal or factual basis. For a very small fee, they could file these en masse and hope for default judgments. This type of automated litigation would seriously twist the justice system.

Now, I don't know of that happening, but there absolutely are downside risks to generative AI and access to justice. I'm hopeful that the world and court systems can put things in place that will help self-represented litigants, but there are forces that could use this technology to harm them as well, and I worry about that.

You wrote an op-ed for The Hill in 2023 titled “We Have a Once-in-a-Lifetime Opportunity to Improve Access to Justice — Let’s Not Squander It” about how a combination of new technology and standards had the potential to improve access to justice, and how Arizona’s courts were helping lead the charge. Nearly three years removed from that piece, do you think improvements have been made? Where do you see room for improvement?

Let me put this in context. When COVID hit, a bunch of court systems shut down, which resulted in backlogs that are still haunting courts. Nobody likes backlog if they're thinking about court management and administration. And every judge that I talk to says they're busy, and we're all trying to work hard to do what we can to resolve the cases in front of us.

But Arizona's courts, thanks to the leadership of our then Chief Justice Bob Brutinel and now Chief Justice Ann Scott Timmer, were pretty open to innovation during COVID, and that was part of what I wrote about in that piece. It accelerated things by a decade or maybe more that we should have been thinking about long and hard, but, of course, we're slow to change. We're based on precedent, and we don't always want to lean forward. But we did a ton of work on remote appearances, and using technology instead of requiring somebody to show up in court.

"It used to be that if you knew the facts and the documents, you were indispensable. That's long since passed. ESI then became the thing, then TAR when you knew how to use it. And now I think it's generative AI."

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To point out a couple of examples, Colorado City is in Mojave County, which is a city of about 5,000 people in the far northwest corner of Arizona on the north rim of the Grand Canyon. To get to the nearest of the three Superior Court general jurisdiction courthouses in Mojave County, residents need to drive four-and-a-half hours one way through two other states to get to the court. Maybe since time began, we should have been doing remote appearances there, but we did during COVID, and it was terrific.

In eviction cases in Maricopa County, where Phoenix is located, there are 26 or 27 justice courts where eviction actions happen. There is at least one of those that has no public transportation to it.

And unlike the counties I grew up in Iowa, which are 36 miles by 36 miles, Maricopa County is huge, 100 or more miles north-south. So failure to appear rates, when personal appearances were required in those hearings, approached 40%. Two in five tenants just didn't show, and I'm pretty sure they lost.

When we moved to allow phone and remote appearances during COVID in March of 2020, failure to appear rates went down almost immediately to about 25%, just by that one change.

A group that I co-chaired called the Plan B Workgroup ultimately made recommendations on remote and in-person hearings in Arizona for all trial court hearing types in both general and limited jurisdiction courts. The Supreme Court adopted those, then implemented them through administrative orders throughout the state. And I think they've worked fairly well, but I wanted us to find out more about whether they really were. So we did surveys of the judicial branch and members of the State Bar of Arizona in 2021. And then we repeated that survey almost verbatim in 2023. And then we just finished another round, which is what I reported out in 2025.

I have three major takeaways from those results. One is that there's a hunger for more training and assistance in how to use technology, both from the bench and the bar. And we need to listen to that. We need to provide that kind of training.

Two, there's a hunger for better equipment. While people are generally good with the advantages of remote appearances, there's a definite need for better technology to assist with those hearings.

The third thing, which I thought was interesting, was in response to one of the questions we asked which was, "What improvement should we make going forward?" One of the options was never using technology to do anything. I'm exaggerating a little bit, but let's go back to how things were in January of 2020 before all this stuff happened.

In the first survey in 2021, something like 7.2% of the respondents chose that option. In 2023 that rose to 7.8%. And in 2025, I think it went back to 7.5%. And the takeaway for me is that I will take a high single digit percentage that's consistent and stable of folks that want go back to how things were unchanged, and to have everybody go to the courthouse and everybody find parking and everybody find transportation, because that suggests to me that 92% of the people are good with the innovation that we have. Now, there are a whole bunch of permutations for that. It's far from perfect, and we do need to do more training and education, and technology is expensive. But it shows that people can change, including old judges like me.

You’ve also mentioned the “bright line test” when talking about AI, that if you wouldn't let a clerk do it, don't let AI do it. As generative AI becomes more sophisticated and prevalent in the legal profession, do you see that line or standard moving, or do you think it should be a permanent boundary for the bench?

I worry that it is moving. And just to share, I will step down from the bench at the end of August of this year. I'll do some other things with the courts after that, but my time horizon is pretty short going forward. I'm not worried that generative AI is going to replace me in no small part because of that. I think even if I had 10 years in front of me and generative AI could replace some things I'm doing, I'd be okay with that.

My clerks aren’t using generative AI unless it's behind a password-protected barrier. And I've done the same thing, not for case-based work, but for other articles that I've written. And at times, I've found a needle in a haystack, and at times, it's a big swing and a miss.

And this did not originate with me, but there needs to be a human in the loop. And more specifically, where I get to my worry, it needs to be the right human in the loop.

In our court, we've had hallucinated cases. You go to look for them, you can't find them, and they stand for propositions that are foreign to me. I've been a member of the State Bar since 1992, and I've stumbled over a lot of things, and so I know when something doesn't sound quite right that it's a tell to dig deeper. We've seen hallucinated cases that stand for propositions that absolutely exist, and that's less bad than a made-up proposition, but it's still not good because you want to check and make sure that the right authority is supporting the right proposition.

"This is a great time to be a young lawyer if you lean forward. Judges also need to understand the technology, and not just put their head in the sand and say they’re never going to use it."

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But what I struggle with, and it's both an opportunity and a danger for new law grads, is if they know technology, they can become indispensable. I teach evidence as an adjunct at Arizona State University, and I always encourage students to learn as much as they can about technology.

It used to be that if you knew the facts and the documents, you were indispensable. That's long since passed. ESI then became the thing, then TAR when you knew how to use it. And now I think it's generative AI. But when you're right out of law school, it is fair that you don't have that depth of knowledge. You haven't stumbled over those things. Your ability to predict what the law should be, which is really what you do with research, is more limited.

So in that sense, just turning somebody loose and saying, "Hey, go use generative AI and prosper," that creates a big risk. And it certainly does for self-represented litigants who don't have that background in training, or don't have the mentorship, and often are working in times of personal crisis and are strangers to the law. The law is complicated and complex and uses concepts and terms that are not understood by most people, so how we wrestle through that is going to be a challenge for sure.

You recently co-authored a paper in Volume 26 of The Sedona Conference Journal titled “Navigating AI in the Judiciary: New Guidelines for Judges and Their Chambers.” Why did you and your co-authors feel the need to create these guidelines, and what are you hoping they’ll achieve?

I'll speak for myself as one voice in part of an, excluding me, all-star choir. And from my perspective, I wanted to be a part of this because of the informal feedback I've gotten when I've spoken to judicial groups about generative AI.

I'll start by asking two questions. One is, "How many people have even tried a generative AI platform?" And at most maybe about half of hands go in the air.

What I'll do is I'll say, "I'm going to promise you three things, and then we're going to do a live demo. One is that when we do this live demo, the FBI isn't going to come storming in, asking, ‘What are you guys doing? Are you using generative AI?’ Two is the security people aren't going to open the door and wonder what's going on. And third is the sun's going to rise in the east tomorrow.”

Then we’ll do a generative AI test, starting with something small like, “What's the best risotto recipe?”

I'm not looking for folks to share confidential or private information. And as soon as they get started, you can feel the blood pressure in the room decline. They understand that this is a powerful technology that has opportunities and risks, but it's also not mystical in the sense that you can't put your fingers to the keyboard and use it.

Some of that article was to get people to say, "This can be done. You can do this. You need to do it thoughtfully, but you can do it." And the second question that I've asked more recently is, "How many people have a use policy in their courts for how you can use generative AI and/or have had training before here on how to use it?" And never have I had more than one in ten hands go up in the air. We have a use policy in Arizona, as do a lot of other courts, but how often that's being followed is a different question.

That paper was to provide something that was in the mid-range. Not at 500,000 feet, because there's a lot of platitudes about generative AI that don't really help, and not at ground level because you can't do that for all the courts around the country. We wanted to get something that tried to normalize the thought that generative AI really can be used for the forces of good in judicial chambers, and to offer some things that judges might want to think about.

To close us out, do you have any advice or tips for this next generation of judges and attorneys who are going to be dealing with generative AI, potentially in their daily practice from here on out?

The number one thing I tell people is get to know it. Get to know what generative AI is and what it isn't. Understand some of the terminology. If you don't know what a large language model is, you're going to struggle with what generative AI is and can be. Understand the technology a little bit, and understand what platforms are out there.

As a court system, we work almost exclusively with text. There are also platforms that create voice messages, videos, pictures, and things like that. People should get to know what's out there. Get to know what the upside and the downside is of these things. Understand the ethical environment that we have both as lawyers and judges that you need to comply with. We can't go perambulating. We can't go walking around the scene to figure out what's going on. That's not what judges could or should be doing.

The National Center for State Courts has a sandbox where you can play around with different things, and then make a decision that's right for you. I've told people, "Look, if you learn this stuff, if you tried it, and you say, ‘Hey, that's not for me,’” I respect that.

We talked a little bit about being indispensable as a young lawyer. This is a great time to be a young lawyer if you lean forward. Judges also need to understand the technology, and not just put their head in the sand and say they’re never going to use it. I want to see what courts can do to better manage the courts.

Anecdotally, I got some data almost three years ago now from the justice courts in Tucson about appearance rates. My friend, Judge Ron Newman, sent it to me by date. Well, if you have it by date, you can go by day of the week. And it turns out your appearance rates on Thursday are about 2%, 2.5%, maybe 3% higher than they are on a Monday. Maybe we as a court should listen to that and say, "Why don't we set more of these on Thursdays?"

We can do things with data, using generative AI, and we can tease out things that will improve the court system. For example, can we reduce or maybe eliminate bias in the data that we collect? We collect a ton of data. It's imperfect, no doubt, because it's the product of humans. But over time, you can find some trends. Are we looking at the right thing, for example, on treatment courts? Is recidivism the right thing to look at for a drug treatment court? I don't know. But we can look at things through a completely new lens to try to better understand what courts are doing. And I absolutely think that's true for practitioners as well.

You've got to recognize these boundaries, no doubt. And the practical limit of how to use generative AI is bound only by the imagination of creative folks. But for the same reason that the COVID pandemic required us to look at remote appearances, this new technology, if you can look at it as judging 2.0, has the ability to help us do things differently.

Advancing Access to Justice with $6 Million in Everlaw Technology

2026-04-26T08:35:44Z

Advancing Access to Justice with $6 Million in Everlaw Technology

by Petra Pasternak

Reading Time — 1 minute

March 9, 2026

Everlaw is committed to putting its advanced ediscovery technology to work for positive change. Through the Everlaw for Good program – which makes our solution available to mission-driven organizations – we recently hit a major milestone, surpassing $6 million in total donated technology and expanded support for legal and other professionals working to level the playing field for justice.

Launched in 2017, Everlaw for Good has seen 74% year-over-year growth for the last two years. The program is helping nonprofits, legal aid organizations, pro bono teams, journalists, and educators navigate the technical challenge of scouring the mountains of data involved in today’s litigation and investigations.

In the last year alone, the program supported more than 675 active cases across 235 organizations, while donating $2.5 million worth of product. These developments represent a growing need for advanced tools – including AI – that help under-resourced teams get better results for the communities they serve.

According to Everlaw’s recent survey on AI and the justice gap, legal aid organizations are adopting AI at roughly twice the rate of the broader legal profession, and 88% of legal aid professionals say they are optimistic about AI’s potential to help narrow the justice gap. The need is urgent: an estimated 92% of the civil legal problems experienced by low-income Americans receive no or inadequate legal help.

“Mission-driven organizations are increasingly handling complex investigations and litigation with limited resources,” says Joanne Sprague, Head of Everlaw for Good. “Expanding access to powerful, easy-to-use technology helps level the playing field.”

Sprague says that the need for an ediscovery solution that can shine a light into dark corners and sift through complex troves of data is only growing, and Everlaw for Good intends to continue assisting mission-driven organizations in their efforts to make the world a better and more equitable place.

Learn more about Everlaw for Good and fill out our application online.

Right Discovery + Everlaw

2026-04-26T08:35:44Z

Right Discovery + Everlaw

What Is ESI? A Practical Guide for Legal Teams

2026-04-26T08:35:44Z

What Is ESI? A Practical Guide for Legal Teams

by Justin Smith

Reading Time — 6 minutes

March 4, 2026

The modern discovery process no longer starts with a physical search; it begins with a rush of digital data. In a single minute, the global workforce generates millions of emails, Slack messages, and cloud-based file edits. This relentless surge of data has fundamentally shifted the legal landscape, moving the smoking gun from the file cabinet to the cloud.

Today, the challenge for legal teams is not just finding the needle in the haystack—it is managing a haystack that grows by several gigabytes every hour. To navigate this complexity, cooperation between parties and a mastery of electronically stored information (ESI) are no longer optional; they are the bedrock of a defensible legal strategy.

ESI is any electronic information that is created, manipulated, communicated, stored, and best utilized in a digital format. As organizations continue moving their operations almost entirely to digital-first environments, ESI has become the heart of modern litigation and investigations. Understanding its nuances is a fundamental requirement for legal professionals to fulfill their duty of competence and handle discovery requests with ease.

Key Takeaways for Legal Teams

The Data Deluge. ESI includes everything from emails and PDFs to ephemeral chat reactions, Internet of Things sensor data, and social media footprints.
Cooperation Is Efficiency. Early collaboration on ESI protocols prevents discovery about discovery, reducing costs and the need for court intervention.
The Power of Metadata. Unlike paper documents, ESI contains data about data, providing hidden context like authorship, timestamps, and GPS coordinates.
Strict Defensibility. Failure to preserve relevant ESI once litigation is reasonably anticipated can lead to severe sanctions, including adverse inference instructions.
ESI Protocols Save Time. Proactive planning through ESI protocols during the meet and confer phase prevents technical disputes and keeps costs predictable.

What Does ESI Mean in Practice?

While the term might sound technical, the legal definition of ESI is intentionally broad to keep pace with evolving technology.

While the Federal Rules of Civil Procedure (FRCP) don’t explicitly define ESI, FRCP 34(a)(1)(A) governs the production of documents, and states that a party may serve a request to produce “any designated documents or electronically stored information—including writings, drawings, graphs, charts, photographs, sound recordings, images, and other data or data compilations—stored in any medium from which information can be obtained either directly or, if necessary, after translation by the responding party into a reasonably usable form.”

In practice, this means that if information exists on a chip, a hard drive, or in the cloud, it is classified as ESI. For legal teams, the transition from physical paper to digital data has fundamentally transformed the nature of evidence, driven by both its overwhelming volume and its inherent persistence. While a single gigabyte of data can contain as many as 75,000 pages of text, modern discovery often spans terabytes, making automated review tools a necessity rather than a luxury. Moreover, digital information is notoriously difficult to permanently erase; even when a user clears their archives, ESI often leaves a lasting trail in slack space, system backups, or server logs, providing a level of evidentiary longevity that traditional paper files cannot match.

Furthermore, legal teams must distinguish between the content (the text of an email) and the metadata (the hidden information about that email). In many cases, the metadata—such as proving a document was accessed after a specific date—is more valuable than the document’s content itself.

ESI in Litigation

In the context of the modern litigation process, ESI is the primary driver of the discovery phase.

Under FRCP 26(f), parties are required to meet and confer early in the case to discuss the preservation and production of ESI. This conference is where legal teams must address the technical realities of the case, such as which data sources are relevant, how they will be searched, and what formats will be used for production. Because ESI is so pervasive, these discussions often dictate the timeline and budget of the entire legal matter.

ESI has also introduced the critical concept of proportionality, which has become a central discussion in the ediscovery process. Given that the volume of ESI can be astronomical, legal teams must be prepared to argue in court why certain data sources—like legacy backup tapes or fragmented metadata—are either central to the case or too costly to retrieve. Successfully navigating ESI in litigation requires a balance between aggressive advocacy for relevant facts and a pragmatic approach to the technical limitations of digital storage.

Common Types of Electronically Stored Information

As technology evolves, the list of ESI types grows. Legal teams must be prepared to identify and preserve data and relevant information across various categories.

1. Traditional Communication and Documents

Email and Attachments. Still the primary source of evidence. This includes the body of the email, header information (To/From/CC), and any attached files.
Business Documents. Electronic documents such as word documents, PDFs, presentations, and spreadsheets.
Databases. Structured data from CRM systems (like Salesforce) or financial software.

2. Modern Collaboration Tools

Chat and Instant Messaging. Platforms like Slack, Microsoft Teams, and WhatsApp. These are often ephemeral or highly informal, creating unique challenges for preservation.
Video Conferencing. Recordings and transcripts from Zoom, Webex, or Teams meetings.
Modern Attachments (Linked Content). A growing area of dispute involves whether hyperlinked files—files shared via a Google Drive or SharePoint link rather than a traditional attachment—should be treated as modern attachments. Courts are increasingly treating these links as part of the document itself.

Mobile Device Data. SMS/MMS text messages, GPS location history, call logs, voicemail, and application-specific data.
Social Media. Public posts, private messages, and likes from platforms like LinkedIn, X (formerly Twitter), or Facebook.

4. Emerging Data Sources

Cloud-Stored Files. Data residing in Google Drive, Dropbox, or iCloud.
Internet of Things. Data from smart devices, wearable fitness trackers, or connected vehicles.

The volume and variety of these data types matter legally because they dictate the search strategies and technical tools required for a defensible discovery process. Collecting a Slack thread is vastly different from exporting an Outlook PST file; failing to account for these differences can lead to data gaps that opposing counsel may exploit.

Why ESI Matters in Litigation and Investigations

ESI is the single greatest factor influencing the cost, risk, and timeline of a legal matter.

1. Driving Cost and Complexity

The explosion of data means that manual review is no longer feasible. Organizations must invest in sophisticated ediscovery software to process, deduplicate, and analyze ESI. Without these tools, the cost of paying attorneys to review millions of documents would be prohibitive.

2. Defensibility and Sanctions

The duty of preservation of ESI begins as soon as litigation is reasonably anticipated. If a party fails to stop the routine deletion of emails or allows a key custodian to wipe their phone, they may face spoliation sanctions. Courts can issue adverse inference instructions, telling a jury to assume the lost evidence was harmful to the party that lost it.

3. Regulatory and Government Investigations

In the context of a Department of Justice or Securities and Exchange Commission investigation, the ability to produce specific ESI quickly is a sign of cooperation. Conversely, an inability to manage ESI can lead to increased scrutiny and harsher penalties.

4. The Privacy Paradox

As ESI is collected, it often contains sensitive or personally identifiable information, or data protected by regulations like GDPR or CCPA. Legal teams must balance their discovery obligations with privacy mandates, often requiring sophisticated redaction and data-minimization techniques before production.

How ESI Fits Into the Ediscovery Process

ESI is the raw material that travels through the Electronic Discovery Reference Model. Understanding this journey is essential for maintaining the chain of custody.

Identification. Determining which ESI is relevant and who the custodians (the people in control of that data) are.
Preservation. Issuing a legal hold or litigation hold to ensure that ESI is not altered or deleted.
Collection. Transferring ESI from its original location to a secure ediscovery platform. This must be done in a way that preserves metadata.
Processing. Reducing the data volume by removing duplicates (deduplication) and filtering by date or keyword.
Review and Analysis. Evaluating the ESI for relevance, privilege, and key themes.
Production. Delivering the ESI to the requesting party in the agreed-upon form of production (usually as load files that include text, images, and metadata).

Managing ESI well requires proactive planning. Waiting until a production deadline to realize that your data is in an unreadable format is a recipe for disaster.

From Understanding ESI to Defining an ESI Protocol

Understanding ESI is the foundation for formal agreements. Once a legal team understands the landscape of their ESI, the next step is to formalize how that data will be handled in a specific case. This is done through an ESI protocol.

An ESI protocol is a written agreement—often turned into a court order—that governs the technical details of discovery. It covers things like:

Which metadata fields will be produced.
How threaded conversations (like email chains) will be handled.
The file formats for production (e.g., Native files vs. TIFF images).
Procedures for handling inadvertently produced privileged information (Clawback agreements).

ESI protocols exist to provide a roadmap for the entire discovery process. By reaching an agreement early, parties can avoid discovery about discovery—expensive side-litigation over how the data was searched or produced.

Beyond Compliance: The Strategic Future of ESI

Mastering ESI is no longer a matter of technical compliance; it is the strategic differentiator that defines the modern litigator.

As the digital landscape continues to fragment into increasingly complex formats, the ability to harness this information will separate the teams that are buried by data from those that are empowered by it. The future of discovery lies in moving beyond mere collection toward a state where advanced analytical tools and generative AI act as the bridge between a mountain of raw data and a clear, actionable narrative.

By embracing these technological shifts, legal professionals don’t just solve the problem of discovery volume; they unlock a new standard of precision that fundamentally elevates the pursuit of truth in the digital age.

Adio + Everlaw

2026-04-26T08:35:44Z

Adio + Everlaw

Professional Services, Enhanced: How Adio Streamlines Litigation with Everlaw

2026-04-26T08:35:44Z

Professional Services, Enhanced: How Adio Streamlines Litigation with Everlaw

by Petra Pasternak

Reading Time — 3 minutes

March 3, 2026

Generative AI helps legal teams surface insights from massive datasets faster — but its impact goes beyond that, reshaping how service providers collaborate with clients and deliver value.

For litigation support company Adio, Everlaw enables closer, more strategic partnerships, says Managing Director Ben Kennedy.

Based in Australia, Adio provides ediscovery and trial solutions to law firms and corporate legal departments across investigations, complex discovery matters, and industries such as insurance, construction, and regulator requests. And it has been committed to exploring the potential of AI.

“We’re very familiar with AI workflows,” Kennedy says. “Bringing clients along with us and exploring this technology is something that we felt was an imperative. We’ve seen this technology in other industries, and we really wanted to evaluate how it would impact the way that we and our clients work.”

Kennedy, who has spent nearly 25 years in the litigation support space and 14 working with Everlaw, says the company’s exclusive focus on the platform allows it to respond quickly to client needs and maximize the impact of advanced AI tools.

“We specialize only in offering Everlaw,” he says. “That gives us a service advantage in getting the most out of the platform across all types of matters.”

An Intuitive GenAI Tool to Deliver Value Faster

Adio’s embrace of emerging technologies definitely applies to Everlaw^AI Deep Dive. Kennedy says Deep Dive is a major boost for discovery at all levels of complexity. Legal teams are excited to use it, finding that they can get to critical documents in large data sets much faster.

Adoption is much easier with Deep Dive, which lets teams ask natural-language questions about their case data, then review citations for direct verification. And a faster learning curve means that results, and efficiencies, are realized sooner.

“There’s immense value in using Everlaw and the Deep Dive feature,” Kennedy says. “We’ve calculated savings of many hours per search in preparing and reviewing search results.”

The beauty of Deep Dive’s capabilities is that there is value to be found across the case lifecycle.

“From the outset during discovery or an investigation, Deep Dive can help you understand your case better and give you some direction,” Kennedy says.

It also helps closer to trial and in between. “We’ve seen Deep Dive used at the later stages of a case, where senior lawyers or barristers are asking new questions about particular themes within the dataset, and we’re able to answer those questions more quickly than we could in the past.”

Built-In Structural Safeguards Boost Confidence

Speed and usability are important, but quality matters as well. Legal professionals remain concerned about the reliability of AI outputs. Kennedy says Everlaw’s rigorous approach to security and validation helps Adio put minds at ease.

Deep Dive is designed with strict security and privacy safeguards, ensuring no client data is stored or retained by the language model. Everlaw also emphasizes accuracy and transparency, providing citation-backed answers and admitting when sufficient information isn’t available.

Adio doubles down on that, putting the human in the loop to help review outputs.

“We put a really robust process in place around checking how the searches are constructed, where they are getting the intended result, and being clear on when they’re not getting the intended result,” he says. “Everlaw does a great job of presenting results within the document itself. The words that are used are important. We help to validate that the prompts or questions are getting the results that they need to get.”

Adio + Everlaw: Better for Business

Everlaw’s commitment to supporting the broader Australian legal market is a primary driver of their joint success. By having a partner that is responsive to requests, Adio can step in and support clients at the moment services are required, ensuring they are always better off.

It’s also a path to success for Adio as a business. Partnering with Evelaw has helped Adio deepen client relationships, Kennedy says.

“Deep Dive is enabling us to work more closely with our clients,” he says. “It allows us to understand the client’s questions about their data, their focus, and provide them a mechanism for either getting those answers themselves or helping to bring the documents of interest up to the fore for them to evaluate.”

Moreover, the everlaw partnership has helped Adio win new business.

“Everlaw has been very supportive to the Adio business. They’ve introduced us to numerous new clients and identified where a service provider can really make a difference to the law firm,” Kennedy says. “We value that partnership.”

Join Us for Everlaw Summit ‘26, October 27-29

2026-04-26T08:35:44Z

Join Us for Everlaw Summit ‘26, October 27-29

by Casey Sullivan

Reading Time — 1 minute

February 24, 2026

Everlaw Summit is back for another year! Everlaw’s flagship customer event returns this October 27th to 29th in the Palace Hotel in San Francisco.

Promising three days of education, connection, and inspiration, Summit ‘26 comes at a pivotal time for the legal profession, as new technologies open up potentially radical shifts in traditional approaches to litigation. As practitioners embrace strategy-first approaches from the earliest moments of a matter, enabled by technologies like Everlaw^AI Deep Dive, and move to rapidly meet their discovery obligations with tools like Coding Suggestions, Everlaw Summit is where leaders can see these changes take place first hand – and experience the next wave of opportunities to come.

Over three days Everlaw Summit will offer a mix of education sessions, hands-on product training, thought leadership, and networking.

Everlaw Summit ‘26 programming will include:

A full day of Everlaw product certification on October 27th
A can’t-miss keynote from Everlaw Founder and CEO AJ Shankar
Breakout sessions featuring insights from industry leaders, workflow guidance, and opportunities to engage directly with Everlaw specialists and peers
Up to seven hours of CLE credit for attendees
Summit After Dark evening soiree on October 28th
Daily networking, user education, and product feedback activities

The full Summit agenda, speakers list, and programming updates will be announced on the Everlaw Summit website in future.

Attendees enjoy Summit After Dark at Everlaw Summit '25, hosted at the Exploratorium Museum.

Speak at Everlaw Summit

Everlaw Summit is the perfect venue to highlight your expertise and help educate the legal community. With nearly 100 speakers from across the profession – including members of the judiciary, leaders at government agencies, academics, and more – Summit sessions cover everything from day-to-day workflows to the largest trends shaping the law and society.

Interested speakers can propose potential session topics here.

Casey Newton, co-host of the Hard Fork podcast, and Nilay Patel, founder of The Verge, speak with Professor Rebecca Delfino and Michigan Chief Justice Bridget McCormack at Summit '25

Register Early to Save

Registration opens February 24th. Regular admission is available for $899, covering your three-day conference pass, daily breakfast and lunch, Summit After Dark, and networking receptions. All product certification tracks are available for an additional $400. Discounts are available for public sector employees, members of Everlaw for Good, and groups of five or more.

Those who register early can save big. Summit’s Early Bird pricing discount runs until May 1st, offering $400 off registration – the biggest discount offered all year.

Learn more and register here.

Casey Sullivan is an attorney and writer based out of San Francisco, where he leads Everlaw’s content team. His writing on ediscovery and litigation has been read by thousands and cited by federal courts. See more articles from this author.

Hallett & Perrin Transforms Their Ediscovery Workflows with Everlaw

2026-04-26T08:35:44Z

Hallett & Perrin Transforms Their Ediscovery Workflows with Everlaw

by Justin Smith

Reading Time — 3 minutes

February 18, 2026

Hallett & Perrin is a Dallas-based law firm known for focused, effective representation across a wide range of legal matters. The firm handles class action litigation, business litigation, corporate securities work, and employment litigation. Its expertise also includes the Employee Retirement Income Security Act of 1974 (ERISA) and benefits litigation, labor disputes, trusts and estates, and other business disputes. This breadth of practice areas allows the firm to meet varied client needs while maintaining a high standard of efficiency and precision.

The litigation department relies on a close-knit team, including two paralegals and a group of legal assistants who work together to deliver strong results. Alisha Vance, a seasoned paralegal with more than 30 years of experience, plays a key role in the firm’s litigation efforts.

“I’ve been working with ediscovery before the ‘e’ was added to discovery,” Vance said when recalling how discovery work has changed over time. “The initial cases I worked on were all paper-based, and we progressed to using separate programs—one for imaging and another for data—making the process cumbersome and inefficient.”

Through her work with these outdated tools, Vance has seen firsthand the impact capable technology can have on the discovery process.

Challenges with Traditional Ediscovery Tools

Before adopting Everlaw, Hallett & Perrin struggled with traditional ediscovery tools. They had multiple systems that were disconnected, which slowed down key workflows and delayed access to important information.

When it came time to change the discovery process, Vance’s expertise played a key role in the search for a new tool.

“I've always been one of the people who participated in and looked for ways to continue using and expanding the efficiencies that we could bring to projects by using any tool, whether it’s old or new,” Vance said.

Prior tools made it hard to quickly analyze data, find insights, and build effective legal strategies. Vance described the difference after the move to Everlaw as night and day, noting that the platform let the team identify critical information fast. That clarity helped them understand key events sooner and take a more strategic approach to litigation.

“Everlaw has allowed us to shed a tremendous amount of light, very quickly, on the data we gather from our clients to bolster our understanding of key events,” Vance said. “From there, we can move into more specific ways to be defensive or forward-thinking in claims.”

Efficient Ediscovery Implementation with Everlaw

Hallett & Perrin’s adoption of Everlaw marked a turning point in its approach to ediscovery. Vance helped with the transition, recognizing the need for a tool that could streamline work and deliver faster results.

“The firm and the associates, as well as the partners, were eager to find a better tool,” Vance said. “Once we met with and understood how Everlaw could change the practices and the workflows, we signed up a case as soon as possible and from there had good success.”

The firm quickly integrated Everlaw into its processes, using it on as many cases as budgets allowed. Everlaw’s features, including early case assessment projects, proved invaluable.

Search term reports added to that efficiency. The team could show exactly how searches were built, share results with clients, and provide necessary information to opposing counsel. These tools sped up document review and supported the firm’s ability to build compelling case narratives.

“With Everlaw, we’ve saved weeks to months in reaching early case assessments and efficiently identifying key documents based on date ranges and critical events. It helps us build a narrative that clients want to put forward in their claims by providing additional support from the data that we find and can quickly get to,” Vance added.

Empowering Teams with Data and Collaboration

Everlaw has changed how Hallett & Perrin’s teams collaborate and analyze data, allowing more people across the firm to engage in discovery. Bringing different viewpoints into the process strengthens the firm’s ability to support its clients.

“Everlaw broadens the participation in the initial phases of case data analysis, enabling diverse perspectives that enhance understanding and interpretation of the data,” Vance said.

The platform’s Storybuilder feature has been especially helpful. It provides a collaborative space for organizing and annotating case materials, even for smaller matters that primarily involve PDFs. This flexibility helped the firm move away from traditional shared drive folders to a system that is easier to use, more dynamic, and better for teamwork.

The training and support from Everlaw, which is provided to clients at no added cost, has also made a difference in Hallett & Perrin’s quick adoption of the platform.

“I’m really impressed with Everlaw’s training and support and how it works to broaden the base of people who can do things that have been exclusively given to smaller sets of workers,” Vance said.

With more team members gaining the skills to use Everlaw’s tools, the firm has built more inclusive and efficient workflows, saving time, improving collaboration, and delivering greater value to clients.

Creating an Integrated Ediscovery Process

By moving away from the cumbersome and inefficient paper-based workflows of the past, Hallett & Perrin has done more than just update its software; it has fundamentally empowered its people.

As Hallett & Perrin continues to integrate Everlaw across its practice, they aren’t just keeping pace with the industry—they are defining what a high-precision, tech-forward litigation firm looks like today.

“Everlaw has proven to me that I'm able, competent, responsible, and ethical in the choices that I make,” Vance said. “I believe I’m a more effective professional because I can arrive at answers faster and more efficiently, and those answers then become part of the lifecycle of a case.”

Hallett & Perrin + Everlaw

2026-04-26T08:35:44Z

Hallett & Perrin + Everlaw

Moving From Data Overload to Actionable Insights with Right Discovery

2026-04-26T08:35:44Z

Moving From Data Overload to Actionable Insights with Right Discovery

by Petra Pasternak

Reading Time — 2 minutes

February 17, 2026

For the professionals who help law firms and corporate legal departments through the toughest ediscovery challenges, this fast-moving era of generative AI is an exercise in turning possibility into reality.

“What’s been amazing about this past year is that AI has been adopted a lot faster,” says Kevin Clark, CEO of leading ediscovery managed services provider Right Discovery. Everybody’s testing it, trying to figure out how it can be used in their practice, whether it’s a law firm or corporation.”

Right Discovery assists clients with the full range of ediscovery services, from collection and processing, all the way to trial. Its tech consultants help with management review, depositions, and trial preparation. Partnering with Everlaw helps Right Discovery’s consultants solve the three biggest headaches in modern litigation: technological risk, exploding data volumes, and operational efficiency.

The result: Clients enjoy a simpler experience with fewer handoffs, fewer vendors to manage, and greater consistency across matters.

“Everlaw provides a quick, easy, and efficient unified approach for both law firms and corporations,” Clark says.

Driving Higher Quality Document Review with Built-In GenAI

The legal industry is usually slow to adopt new technology. But Clark says his clients have readily embraced Everlaw AI. In part that’s because intuitive and powerful features like Deep Dive and Coding Suggestions are built directly into the platform, where clients are already working with data. Seamless integration makes it easy for professionals at law firms and on corporate teams to experiment with new capabilities in a secure environment.

“It has been easier to get our clients to try out Everlaw AI because it is built into the software,” Clark says. “They already enjoy a lot of Everlaw’s technological advances and as Everlaw AI has been rolled out, it's been exciting to see how it’s evolved.”

As an example, he discusses a client who’s running a large matter through Everlaw AI. He notes that his team is working with Everlaw to customize workflows to deal with the volume of data.

“Generative AI has made a meaningful difference,” Clark says. “Our clients have been able to cut costs and have more efficient and higher quality reviews.”

Minimizing the Irrelevant in Huge Data Sets

Business data is increasing exponentially. The legacy systems a law firm or corporation has in place weren’t built for today’s volumes, leaving many teams struggling to keep pace.

Right Discovery helps clients manage massive quantities of data and focus on the right slices of information. Whatever combination of emails, Microsoft Office documents, social media, and videos a case involves, Everlaw’s powerful ECA database, filters, and search capabilities – augmented with GenAI features – quickly separates the wheat from the chaff.

“We have terabytes of data that we bring in and have to cut down,” Clark says. “One thing we really like about Everlaw is the ability to easily minimize a lot of the waste.”

Partnering to Build Better Efficiencies

Clark says that Right Discovery working with the Everlaw team through the Partner Program is all about blending the right technology with the right strategy to solve complex challenges – and rethinking what’s possible for the client.

“We’ve been able to work together to create customized workflows,” he says. “We’ve definitely been able to do some very unique and interesting things to meet our clients’ needs.”

And the program helps not only the client, but Right Discovery as well, he adds. “We’ve been able to identify potential clients and bring Everlaw to them to provide services when they don’t have the resources they need.”

The close collaboration, he says, has proven the value of Everlaw’s GenAI features and helped clients be more efficient and more effective.

“We look forward to continuing to grow the partnership,” Clark says. “It's a win win.”

Industry Observers Predict GenAI Will Disrupt Client-Firm Relationships and Billing Models

2026-04-26T08:35:44Z

Industry Observers Predict GenAI Will Disrupt Client-Firm Relationships and Billing Models

Media coverage draws on insights from latest Everlaw/ACC in-house survey

by Petra Pasternak

Reading Time — 6 minutes

February 10, 2026

Everlaw’s latest corporate in-house report drew attention to the rapidly rising adoption of generative AI – and the impact on the business of law. The survey of 657 in-house legal professionals across 30 countries, co-developed with the Association of Corporate Counsel, found that adoption of GenAI had more than doubled, to 52%, year over year.

Part one, Generative AI’s Growing Strategic Value for Corporate Law Departments, found that GenAI is helping legal professionals work faster, communicate more effectively, and deliver better client service. And one-third of in-house teams are already seeing measurable cost savings. This is naturally changing the amount and types of work that in-house teams choose to outsource. Many in-house professionals now predict a recalibration in how outside counsel deploy GenAI, and how legal services will be priced.

The second part of the survey, The Role of GenAI in Proving Corporate Law Department Value, examined the ways in which GenAI is improving how in-house teams articulate business value and redefine their status from cost center to business driver. The leading benefit identified in the research was that teams are more quickly delivering legal support and matter resolution.

The legal industry is undergoing a technological transformation at a pace once thought impossible.

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Both installments drew media attention across the legal industry from more than two dozen publications – including Bloomberg Law, Law.com, Law360, Canadian Lawyer, and The National Law Journal. The adoption surge led much of the coverage.

“The legal industry is undergoing a technological transformation at a pace once thought impossible,” Ma Fatima wrote in the JDJournal. “While only a small number of teams experimented with AI in prior years, the findings show that 2025 marks a turning point – the year when GenAI became an essential component of modern legal work rather than a novel experiment.”

Despite the many upbeat findings in the survey, the report also identified tensions that will continue to play out in 2026 and beyond. These tensions are not around the tech itself, or the workflows it will inhabit, but in what it means for relationships between in-house teams and their outside counsel.

ACC President and CEO Veta Richardson told Canadian Lawyer's Jessica Mach that accelerating adoption has been accompanied by greater optimism about and trust in AI technologies. But she also said that GenAI will fuel in-house desires to challenge how legal services are delivered and billed.

“This reflects a growing willingness among in-house teams to challenge traditional models and explore new approaches,” she said.

The Value Is There While Key Metrics Lag

Before GenAI can significantly affect how legal work is scoped and outsourced, teams will need to understand exactly how well it’s working, and what benefits it is delivering. So far, teams that have adopted GenAI have not been great at articulating those benefits.

It’s going to take a little bit longer for the metrics to actually catch up with the appreciation of the impact.

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Writing for Law.com’s LegalTech News, Ella Sherman noted that “the lack of outcome-based performance metrics makes it more difficult for in-house teams to track the impact of their growing gen AI adoption. Only 28% of respondents track time to resolution for legal matters, 12% track outside counsel performance metrics, and 12% track technology adoption return on investment.”

She spoke to Everlaw Senior Strategic Discovery Advisor Chuck Kellner, who told her, “It’s going to take a little bit longer for the metrics to actually catch up with the appreciation of the impact just because it’s been so short of time that we’ve had to actually operate these tools.”

Closing the Transparency Gap

A lively writeup from Above the Law’s Stephen Embry also looked at the lack of transparency and the failure of AI-driven savings to materialize:

“Fifty-nine percent of in-house professionals remain unaware of whether their law firms are using [GenAI] on their legal matters,” he wrote. “And even more startling: as of now, 80% — yes, 80%! — of those surveyed are not requiring or even encouraging outside counsel to use GenAI. Even more telling: Of those firms who are using GenAI, 59% of in-house counsel say they have seen no noticeable changes in what is being billed.”

Writing for ACC Docket, Blake E. Garcia and Mauro Whiteman also focused on the transparency gap, and underline key risks of letting it persist, writing:

“The absence of visibility creates three risks:

Value blindness: Clients cannot assess whether GenAI is making their legal services faster or cheaper.
Pricing assumptions: A lack of information on how law firms are using AI risks creating unrealistic expectations from clients on how AI may or may not reduce legal costs.
Trust deficit: Without clear disclosure, clients may worry about quality, security, or ethical implications of AI-generated work product.

“For a profession built on fiduciary duty and client confidence, this lack of transparency is not sustainable.”

In-House Leaders Can Press Their Advantage

Christine DeRosa, covering the report for Law360, noted that “most in-house legal departments have yet to see tangible savings from their outside counsel’s use of generative AI, with 59% of respondents reporting that they haven’t seen noticeable savings yet.”

Everlaw CLO Gloria Lee indicated that this will have to change, telling DeRosa, “One thing every general counsel says about their outside counsel is they want greater value.”

So it will almost certainly fall to corporate legal leaders to make the first move. Fortunately for them, corporate legal teams not only have more reason to close the transparency gap and revisit costs, they also seem to have the negotiating advantage. In a broad survey of AI in the legal industry in early January, Law360’s Michele Gorman zeroed in on the finding that more in-house teams – nearly two-thirds – say that GenAI will allow them to rely less on outside counsel. Gorman’s article speculates that further AI developments will deliver ever-greater efficiencies and in-house capabilities to corporate teams, making them less dependent on outside expertise.

For a profession built on fiduciary duty and client confidence, this lack of transparency is not sustainable.

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The first step to using that leverage to control costs is to simply understand where new technology is being applied, and how much it is improving outcomes. In an article on the report titled, In-house Teams Are Quickly Adopting Gen AI. They Don’t Know if Their Outside Counsel Are Doing the Same, Law.com’s Benjamin Joyner led with the transparency gap, and seemed to put the blame on in-house teams: “In-house lawyers are using generative artificial intelligence in their legal practice at a dramatically higher rate than a year ago,” he wrote, “but they have yet to exert much pressure on their outside counsel to do the same.”

Everlaw’s Gloria Lee told Joyner that corporate departments may have to fully figure out GenAI themselves before laying down the law with their outside firms. “Most in-house teams are still defining their own GenAI policies, so they may be reluctant to dictate how outside counsel should use it,” she said.

That’s the start of the conversation, and it would seem that corporate leaders can then drive past baselines of usage and outcome to either pursue more favorable pricing structures with their outside firms, or move more work back in-house. Talking about the research with Bloomberg Law’s Isabel Gottleib, Veta Richardson said corporate teams, not outside firms, will drive the shift in the pricing of legal services.

“Clients have a lot more options now in terms of how they assure that the services their organizations need are provided,” Richardson told Bloomberg Law, which also notes that legal departments will use their growing GenAI rollouts to handle internally tasks that previously went to outside firms.

The Billable Hour in the Crosshairs

We’re going to see GenAI’s impact on the billable hour play out over the longer term. The fact that only 13% of corporate teams said GenAI was leading outside firms to bill fewer hours, and only 20% were seeing faster turn-around also caught the eye of GeekLawBlog’s Greg Lambert:

“One major reason is that law firms remain where they always were: a patchwork of experiments instead of a unified transformation,” Lambert writes. “The business model based on time-spent (billable hours) is deeply embedded.”

Along similar lines, Bloomberg Law’s Isabel Gottlieb quotes Weston Wicks, senior director on Gartner Inc.’s legal and compliance team: “Law firms don’t know how to charge clients for using AI tools, and clients don’t know how to figure out, ’If we request a reduction in fees because these tools are available, how do we do that?” Wicks tells the publication.

That said, the report indicates that GenAI has the staying power to upset that dynamic. Above The Law’s Jeremy Barker points out that it’s typical for AI to signal “big changes on the horizon, with incremental movement in the current day-to-day.” Writing in Stat(s) Of the Week: GenAI And the Billable Hour, Barker highlights that most organizations (61%) are “somewhat” or “very” likely to push back on law firm pricing models.

Though most say they are not aware about their law firms’ use of GenAI on legal matters and are not actively encouraging adoption, their own use of the technology is allowing in-house teams to take on more work themselves, Barker writes. “Momentum is building against the billable hour,” he quotes Everlaw blog. “Firms that connect GenAI-enabled efficiency to fair, transparent pricing will differentiate themselves as modern, client-first partners.”

Clients have a lot more options now in terms of how they assure that the services their organizations need are provided.

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Next Up: More GenAI, and More Sensitive Conversations

In The National Law Journal’s predictions for 2026, three attorneys foresee that in-house teams will take the lead on AI-driven change. Specifically, the writers note that corporate legal departments have new leverage: “The power shift implications are stark: 64% of in-house teams now expect to depend less on outside counsel because of AI capabilities they’re building internally.”

This means that outside firms and in-house departments are going to have to confront the issues, and soon. While corporate teams may seem to hold better cards, there’s also value in outside firms showing the initiative and starting the conversation on their own terms. Check out how this might play out in a recent Everlaw blog post: Setting Expectations for GenAI Usage and Pricing with Outside Counsel.

Looking at the research, and the industry-wide reactions to the data, it’s possible that the real transformation of this GenAI era for the legal industry will be less around the technology itself, and more about the relationships it changes.

From Mobile Data to Generative AI: Your Guide to Navigating the New Era of Ediscovery

2026-04-26T08:35:44Z

From Mobile Data to Generative AI: Your Guide to Navigating the New Era of Ediscovery

by Justin Smith

Reading Time — 2 minutes

February 5, 2026

In today's complex digital environment, the volume, variety, and velocity of electronically stored information (ESI) have exploded. Legal teams are constantly navigating new data sources, evolving regulations, and the rapid adoption of new technologies like generative AI.

To help you cut through the noise and approach discovery with confidence and defensibility, this ediscovery guide covers every critical phase of the ediscovery lifecycle—from initial preservation to final review and production. It is designed to be your essential reference for mastering the modern digital legal landscape.

Why This Guide Is Essential for Your Team

This guide is more than a list of steps; it's a strategic playbook built for the challenges of litigation, investigations, and regulatory matters in the cloud era. Here are some key areas the guide addresses.

Understanding the Fundamentals

This ediscovery guide provides clear, concise definitions for all the crucial terminology you need to know, from ESI to Technology-Assisted Review (TAR), establishing a common language for your teams. Getting familiar with these fundamentals is critical for reducing miscommunication and building a foundation for more advanced discovery strategies.

Defensible Data Preservation

Effective litigation readiness begins with understanding the best practices for data preservation and legal holds. Beyond simple procedural advice, this chapter illustrates how failing to adhere to these preservation obligations can lead to severe sanctions under FRCP Rule 37(e). Legal teams can ensure their preservation efforts are defensible and minimize the risk of spoliation claims while protecting the integrity of the evidence throughout the matter.

The Power of Early Assessment

Harnessing the strategic benefits of Early Case Assessment allows legal professionals to drastically reduce data volumes and predict potential litigation costs long before full-scale review begins. Shape an informed overall case strategy by identifying key themes and risks early in the process, supported by technology you can leverage to gain early insights. Implementing these assessment strategies ensures that legal teams can make data-driven decisions about whether to settle or proceed, ultimately saving significant time and resources.

Optimizing Document Review

Since document review historically accounts for the vast majority of discovery costs, optimizing this phase is essential for any budget-conscious legal department. Learn how to leverage advanced analytics for quality control and maximize review efficiency through the use of tools like TAR. By adopting these methodologies, teams can increase their accuracy and speed, ensuring that critical documents are identified quickly and consistently.

Navigating the Modern Data Maze

Traditional discovery methods often fall short when dealing with the complexities of the new data landscape. Discover specific, actionable guidance on managing difficult data types, including mobile device data, collaboration apps like Slack or Teams, and the nuances of hyperlinked files. Understanding how to collect and produce these non-traditional data sources is no longer optional; it is a requirement for modern legal practice.

The Transformative Role of Generative AI

It is vital to understand how generative AI is revolutionizing the ediscovery industry by automating traditionally manual tasks like document summarization, coding suggestions, and privilege logging. The guide compares generative AI to traditional TAR, highlighting a trend toward complementary approaches that leverage generative AI's speed with TAR's proven consistency and judicial acceptance. By integrating these technologies, organizations can stay at the forefront of innovation while maintaining the high standard of defensibility required in court.

Future-Proof Your Ediscovery Strategy

Ediscovery is defined by constant change. It’s important that your team continues looking ahead to ensure they’re prepared for the future by remaining educated on key trends that will impact the industry, such as the increasing scope of ediscovery use cases beyond litigation, the ongoing proliferation of emerging data sources, and the greater emphasis on data privacy and cross-border transfers.

How to Integrate Generative AI into Litigation Workflows

2026-04-26T08:35:44Z

How to Integrate Generative AI into Litigation Workflows

Everlaw AI is redefining how ediscovery is done

by Petra Pasternak

Reading Time — 4 minutes

February 4, 2026

Generative AI is changing how legal professionals engage with data, and accelerating time to insight across the full lifecycle of a matter. Where data-heavy matters once may have needed weeks, even months, before ingestion led to actionable intelligence, teams are now able to identify relevant, meaningful information in hours.

GenAI is becoming an essential tool, but every tool has a learning curve. Everlaw makes GenAI easier to adopt by embedding AI capabilities directly into the workflows attorneys already use. Insights carry seamlessly from one phase of a case to the next — no need to switch tools or rebuild context.

From Deep Dive, which surfaces insights through natural language questions, to Coding Suggestions, which accelerates first-pass review, and Writing Assistant, which supports analysis and drafting, Everlaw^AI's GenAI features empower legal teams to reduce review burden and refocus attention on higher-value priorities: strategy, judgment, and outcomes.

Integrating Deep Dive Across the Litigation Lifecycle

The introduction of Deep Dive represents a shift in how legal teams approach document review.

This generative AI tool lets anyone – from litigation support professionals to attorneys – engage directly with the data corpus, ask substantive, natural language questions, and then verify answers with cited source documents. Within minutes, Deep Dive can surface insights that might have taken days or weeks to uncover using traditional methods.

This fundamentally changes how discovery begins. Instead of reviewing documents to understand the case, teams can first understand the case, and then review with purpose.

When Julie K. Brown, Director of Practice Technology at Vorys introduces Deep Dive to new teams, she starts by asking: “Are you ready to see some magic?” She says that after they see the results, the attorneys are “just in awe.”

“The answers are spot on,” Brown says. “If attorneys like something, they’re going to go tell all their friends. Most of the time attorneys are coming to us saying, ‘Can you add my case to Deep Dive?’”

Deep Dive Delivers

Use Deep Dive to:

Talk to your data: Surface insights based on open‑ended, natural language questions about the case – just as you might ask a colleague.
Work Fast: Analyze databases with thousands or millions of documents in minutes.
Trust the results: Generate an answer that is grounded in your documents, not the open web, using retrieval‑augmented generation (RAG).
Verify the results: Deep Dive shows its work so that teams can easily validate the output.
Unify your workflows: Use a single, combined AI toolkit, including Coding Suggestions, Communication Visualizer, and Storybuilder through every step of discovery.

Deep Dive is especially valuable during early case assessment, where speed and clarity matter most. The tool helps identify key facts, themes, and parties before review has even begun. This helps teams filter down to just the documents most likely to contain relevant information and test hypotheses as they begin to frame their case strategy.

They can then open specific documents and use GenAI-powered Review Assistant tools that provide summary, topic extraction, sentiment analysis, and custom extraction capabilities to explore those communications in detail and pull out repeat patterns of concern.

Later in the lifecycle, Deep Dive becomes a powerful tool for deposition preparation and trial support, allowing attorneys to quickly surface what a witness said about a specific topic without manually hunting through documents.

Accelerating Document Categorization with Coding Suggestions

Using Coding Suggestions (part of the Everlaw^AI Review Assistant) to quickly find and prioritize relevant documents can transform litigation and investigation workflows. In real-world matters, Coding Suggestions has shown it can perform at accuracy levels that match or exceed those of human reviewers, significantly speeding up the manual review process.

While tools like Deep Dive, Search, and Communication Visualizer are used to understand the case and pull out the most important documents and communication patterns early on, Coding Suggestions lets teams review and code those documents more efficiently than traditional methods allow.

Coding Suggestions Accelerates Review

Coding Suggestions’ powerful GenAI capabilities allow it to:

Learn from humans: Like a colleague, Coding Suggestions anchors its output in human instruction about the case and the goal of the review.
Auto-categorize documents: It analyzes terabytes of data based on codes for everything from confidentiality and relevance to specific case issues.
Explain itself: It provides reasons for why it made each suggestion, with a clickable link to the relevant snippets in the document so teams can quickly check the reasoning.
Scale work: Coding Suggestions will apply a uniform, consistent analysis over a document set based on input and instruction. Because the prompt-based model requires no training, it is effective over any set – whether it is 10 or 1 million documents.
Quality control: It can help verify existing work and surface new insights.

The tool flags relevant documents and explains its reasoning with links to citations, making verification by human reviewers built into the process. What’s more, Coding Suggestions can scale the logic from one document to hundreds or thousands – in effect automating the process with consistency and precision.

The litigation team at global law firm Bracewell has used Coding Suggestions for first-pass document review. Partner David Shargel says it frees up time for the work lawyers do best.

“The first-level review of a huge tranche of documents that might’ve taken months three years ago now takes a few hours,” Shargel says. “What’s really cool is that, as lawyers, we can now take the time we would’ve otherwise spent reviewing hundreds of thousands or millions of documents to be creative in crafting arguments and presenting evidence.”

After reviewing with Coding Suggestions, the case team can take the document set into Storybuilder and use Writing Assistant to build timelines, summaries, and arguments anchored in those documents.

Turning Evidence Into a Persuasive Story with Writing Assistant

Storybuilder is a collaborative space where multiple teams can work together in real time, organizing documents and tracking evidence. Storybuilder’s built-in Writing Assistant brings the brainstorming and drafting power of GenAI to a specific matter. Writing Assistant gives legal teams a head start on writing narratives and summaries, analyzing depositions, and helping to hone arguments.

Writing Assistant Helps Tell the Story

Use Writing Assistant as a “thought partner” to:

Outline/Draft: It can organize and synthesize insights across the data set into evidence‑centered research and writing, always with citations to source documents.
Search: It can pull in new documents to surface additional supporting evidence or information.
Brainstorm: It can help explore different approaches to rewrite drafts from different angles.
Rewrite: It can rewrite drafts to adjust for tone, format, or length.

GenAI-powered Writing Assistant helps draft time-consuming analytical work such as timelines, factual backgrounds, deposition analysis, and other work quickly and with citations to documents that can quickly be verified. And when deposition transcripts come in, Writing Assistant can expedite time-consuming analysis by helping to identify inconsistencies in testimony.

Writing Assistant also lets teams shape and reframe arguments. And because it limits its output to case documents, its research and writing stay tied to the actual evidence, not generic model knowledge. Human reviewers provide their judgment and style to reach the final draft.

“Writing Assistant is not just a tool for quick output, but a primary thought partner as you craft your arguments, and an editing tool to refine your story,” says Everlaw Chief Legal Officer Gloria Lee. “Often the best learning comes from the initial hard work of pulling together an argument, something you can only do by engaging directly with the substance of a case.”

Discover the Power of Everlaw^AI

Everlaw^AI tools put the human legal professional front and center. Lawyers and their case teams write the prompts and instructions, review outputs, and apply their expertise to steer the work. In keeping a human-in-the-loop, Everlaw^AI enables teams to work more effectively and in novel ways, while maintaining the judgement and decision making required by ethical practice.

By combining GenAI and core Everlaw features, legal teams can speed up document review, avoid unnecessary work, and immediately focus on the substance of the case. This creates a more direct path to the insights needed for early, high‑stakes decisions — when strategy is being set — while dramatically reducing rote tasks.

If you haven’t used Everlaw^AI tools yet, you can pick a low-risk matter and start experimenting today, or reach out for a free walkthrough.

Everlaw<sup>AI</sup> Deep Dive Expands to the UK, EU, and Canada

2026-04-26T08:35:44Z

Everlaw^AI Deep Dive Expands to the UK, EU, and Canada

From fact-finding to final arguments, surface relevant insights across millions of documents—now available on a global scale

by Casey Sullivan

Reading Time — 2 minutes

February 3, 2026

Everlaw^AI Deep Dive has been hailed as a transformative technology in litigation since its release in the U.S. and Australian markets just two months ago.

Powered by a retrieval-augmented generation framework, Deep Dive forgoes the time-consuming document-level review that has traditionally characterised case development, allowing legal professionals to ask straightforward, natural-language questions and receive insights synthesised across their entire document corpus.

Starting today, Deep Dive’s availability expands to Everlaw’s instances in the United Kingdom, European Union, and Canada, bringing access to this game-changing feature across the globe.

Everlaw^AI Deep Dive allows legal professionals to ask questions of their case data using plain, conversational language.

For example, a litigation team investigating bad faith in a failed acquisition previously would have spent weeks iterating on keyword lists and filtering through noise to find relevant threads. Instead of manually synthesising disparate documents into a case theory, teams can now use Deep Dive to instantly bridge the gap between raw data and a coherent timeline.

Litigation teams can simply ask Deep Dive for evidence of bad faith, or any other related questions, and receive an overall summary from across their document set—without any size limitations—supported by a results table that cites specific evidence, rates its potential relevance to the question and includes direct quotations from the source material.

Paradigm-Shifting Litigation Technology Goes Global

Deep Dive operates on a simple idea, effectuated through groundbreaking generative AI technology: connect discovery, analysis and case building into one seamless workflow, so teams can move from question to evidence to work product without losing context.

Having been embraced by leading litigation teams in the U.S. and Australia, Deep Dive has now proven itself in international litigation as well.

Samuel Marrache, a Senior Associate (Barrister) at Hassans, has experimented with Deep Dive during the trial preparation process.

‘Deep Dive has revolutionised the way we prepare for complex trials. The powerful and near-instant question and answer format allows us to interrogate a large dataset in seconds and locate key documents which we can then rely on at trial,’ Marrache said. ‘Deep Dive’s ability to effectively trawl through thousands of documents and pinpoint sections of those documents which respond to our queries has also proven to be an invaluable tool during witness cross-examinations. We are looking forward to using Deep Dive from the start of our next matter.’

What Sets Deep Dive Apart

Unlike similar tools that can limit you to searching across a few thousand documents, Deep Dive operates effectively on a massive scale. It’s been proven effective across databases exceeding 10 million documents and terabytes of data.

Deep Dive’s scope is only surpassed by its simplicity. Interrogating your data is as easy as asking a question, allowing those without advanced technical expertise to quickly develop their understanding of a case and inform their overall narrative. Teams no longer have to wait for extensive document review to find out what evidence supports—or does not support—their position. With Deep Dive, true analysis and strategy can begin the moment your discovery data is uploaded and processed.

The tool is designed to reduce hallucinations by searching exclusively within your corpus and grounding every output in direct citations and fact-checked tables so litigators can build on evidence, not guesswork. When Deep Dive doesn’t find any supporting evidence to answer a question, the system is designed to explicitly indicate that limitation rather than generating unreliable responses.

Deep Dive’s capabilities provide an immediate advantage across the case lifecycle.

Early Case Assessment: Understanding the core facts of a new matter to flag risks and opportunities, and instantly testing hypotheses.
Production Review: Reviewing bulk productions and identifying potential production gaps.
Trial Readiness: Generating key facts and quotes to prepare for hearings, basing strategy on actual case content.

To try Deep Dive on your next matter, contact your Everlaw account team or sign up for a demo today.

Setting Expectations for GenAI Usage and Pricing with Outside Counsel

2026-04-26T08:35:44Z

Setting Expectations for GenAI Usage and Pricing with Outside Counsel

Tips for clients and law firms to bridge the transparency gap

by Petra Pasternak

Reading Time — 4 minutes

January 29, 2026

The GenAI story in 2025 was adoption. The recent survey of in-house legal professionals by the Association of Corporate Counsel and Everlaw confirmed what many leaders were already experiencing: Generative AI is increasingly more common in corporate law departments, although the technology’s inroads at law firms is less clear. The story in 2026 will be the conversations that lead to greater transparency, new baseline expectations, and a reconsideration of cost and value.

In corporate legal departments, comfort levels are rising, experimentation is giving way to fully adopted processes, and early efficiency gains are real.

This year, we’ll see expectations and best practices begin to evolve. In particular, the survey identified growing tensions in the relationship between clients and their outside counsel. A majority of respondents reported limited transparency into law firm GenAI use and uneven indications of cost savings. A debate is also percolating about how AI efficiency gains should affect pricing and delivery models.

GenAI raises new questions and adds urgency to existing ones. In the year ahead, both in-house teams and outside counsel can, and should, take steps to get ahead of the issues and shape a necessary conversation.

Where We’re At: Transparency, Value and the Billable Hour

Transparency is a key point of tension. Most in-house respondents report limited visibility into whether, and how, their law firms use GenAI on client matters. Just as importantly, many say their outside counsel have not yet passed through measurable cost savings from AI adoption. This transparency gap becomes more notable as in-house adoption of GenAI adoption accelerates.

In-house teams are seeing efficiency gains internally, particularly in drafting, contract work, and research. Those gains are already influencing decisions about which work stays in-house and which is outsourced. Over time, this dynamic is likely to sharpen questions about how outside counsel services are staffed, delivered, and priced.

On pricing, most in-house leaders recognize that hourly billing will remain a major part of the legal services landscape. But the survey suggests growing openness to complementary models — particularly where work is repeatable, data-intensive, or well-scoped. Many in-house teams say they are prepared to explore alternative delivery and pricing approaches, even if adoption is gradual and uneven.

“AI dilutes the time-equals-money calculus, and that is especially true for tasks like document review and other high-volume, repetitive work,” says Kelly Mickelson, head of legal ops at Mars Inc. “We believe that we’re going to have more leverage to push for alternative fee arrangements tied to outputs and outcomes, not hours.”

This is not the start of a sudden transformation, and it’s not a discussion triggered wholly by GenAI. But the new technology is adding momentum to long-running conversations about transparency and value. With this catalyst, parties on both sides of the discussion should expect deeper and more urgent efforts around shaping, if incrementally, expectations and best practices.

The In-House Move: Seek Structure and Clarity

In-house legal teams should see 2026 as the year to pursue structured progress. While every corporate team, law firm, and matter won’t move at the same pace, there are practical steps to take. One is to clarify expectations around transparency. Rather than rely on ad hoc conversations about GenAI (if even that), corporate teams can incorporate light-touch disclosure requirements into outside counsel guidelines, RFPs, or matter kickoffs regarding how GenAI is used, and how the outputs are incorporated and identified.

Such requirements can markedly improve visibility without being prescriptive or restrictive. In-house leaders can start by asking:

Whether GenAI is used; what tools, for what tasks
What safeguards and human oversight are involved in assessing outputs
How transparency in such outputs can be assured

These serve as conversation starters. The ACC offers a more developed list of 10 GenAI questions in-house teams should pose to their outside firms, including signals that should prompt further discussion. Over time, these baselines can support more informed conversations about staffing models, timelines, and costs.

In-house teams can also set more productive terms for eventual pricing discussions. Rather than framing GenAI as a demand for immediate discounts, legal departments may gain more traction by focusing on how AI-enabled efficiency changes the mix of work, the leverage model, or the predictability of outcomes. Pilot programs, such as fixed fees for defined workflows, capped fees, or blended models combining hourly and flat components, would offer a low-risk way to test alternatives.

Whatever in-house teams do, they must do it consistently. Applying similar expectations across matters and firms will signal that GenAI is part of a broader evolution in how legal services are evaluated. It’s a discussion about alignment of expertise, value and the continued role of human judgement, not just a ploy to shortchange outside firms.

The Outside Counsel Move: Get There First

Just as in-house teams should open explicit conversations around GenAI, outside counsel would be well advised to beat their clients to the punch. Firms should make their ongoing adoption of GenAI a part of the client conversation around value, efficiency, and timeliness.

Start by sharing:

Where GenAI fits into workflows
How risks are managed, including technological safeguards and human oversight
Which functions and processes continue to remain in human hands, and why
The roadmap for how GenAI rollouts will benefit client services in the future

These conversations can be had without revealing proprietary processes, but it does require intentional communication.

Firms can get ahead of the pricing discussion. In assessing GenAI’s impact on the profession, the Colorado Technology Law Journal observes that GenAI efficiency “translates to demands for alternative pricing models, including fixed fees and value-based billing. Because of this, law firms should consider moving away from billable hours for work done by AI and instead provide flat fees for using AI-driven review services, making it less expensive for the client and more efficient.”

The client expects GenAI to deliver change, so firms should put themselves in the driver’s seat. By openly sharing where firms are experimenting and the results they’re seeing would likely be welcome and lead to conversations that demonstrate a client-centric approach.

Conversation Will Lead to Clarity

The survey by the ACC and Everlaw defined 2025 as a moment of acceleration. Expect 2026 to begin a period of definition. GenAI is no longer just an experiment, and continued adoption will lead to new expectations and clear best practices.

The year ahead offers space for in-house teams and outside counsel alike to set their standards around transparency, value, and collaboration without forcing premature conclusions about where the market will land. Those who engage early, communicate clearly, and experiment thoughtfully will help shape what “good” looks like in the next phase of the client-law firm relationship.

For more on the growing adoption and gaps between in-house and outside counsel professionals that will drive GenAI discussions in 2026, read Generative AI’s Growing Strategic Value for Corporate Law Departments.

Hamilton Law Firm Cuts Work Time in Half and Competes with Big Firms Using Everlaw

2026-04-26T08:35:44Z

Hamilton Law Firm Cuts Work Time in Half and Competes with Big Firms Using Everlaw

by Justin Smith

Reading Time — 3 minutes

January 28, 2026

In the high-stakes world of employment law—where cases often involve senior executives and powerful corporations—the conventional wisdom is that size equals strength. When facing off against Big Law, smaller firms can feel intimidated by the armies of associates and document reviewers on the other side of the aisle. However, New Jersey-based Hamilton Law Firm is flipping that script.

Operating as a dynamic two-person team, Owner and Managing Attorney Ayesha Hamilton and Senior Paralegal Sydney Melendez handle everything from complex litigation to motion writing and client strategy. By leveraging the right technology, they don’t just survive against larger opponents, but thrive, cutting work time in half and delivering big-firm results with a personal touch.

The firm’s small size makes collaboration natural and constant, both between Hamilton and Melendez, and with their clients. Everlaw is integral to improving efficiency, and gives clients a meaningful role in building their cases.

"Using a system like Everlaw is incredibly helpful because we can share important documents directly with the client, allowing them to explain more about what’s happening within their company," Melendez said.

Streamlining Document Management in High-Stakes Cases

Hamilton Law Firm has embraced Everlaw to manage large volumes of discovery, a must when going up against bigger firms. The firm used to store files in shared drives and kept notes elsewhere, which made review slow and error-prone.

"Throughout my time here, we’ve gone up against several big firms, including big pharma firms,” Melendez said. “Everlaw has really helped us streamline the process of finding specific documents, which is crucial when competing with those larger organizations.”

Everlaw’s search capabilities have also been a game-changer, especially considering the fact that being able to quickly find key documents and evidence can make a huge difference in winning or losing a case.

"I can't stress enough how convenient Everlaw is,” Melendez said. “When reviewing 6,000 to 7,000 documents in a few months, being able to search for specific language in quotes saves us an incredible amount of time and effort. I just type the date, and it brings me directly to the correct spot in the document set. It's very helpful and saves a lot of time."

Uncovering Critical Evidence

Everlaw’s search capabilities became especially useful in a recent high-stakes matter against a major pharmaceutical firm. The team faced a "flat" production, in which opposing counsel had provided thousands of documents as simple images rather than searchable text files.

This presented a serious problem when Hamilton and Melendez recalled a specific email where the opposing parties discussed going to an after-work event. They knew the document existed and that it was crucial to their case strategy, but because the production was non-searchable, typing the keywords into the search bar yielded zero results.

Instead of resigning themselves to the manual review of thousands of documents to find the email, Melendez turned to Everlaw’s advanced metadata filters.

“We were able to narrow down the timeline and filter by the ‘To’ and ‘From’ fields in the metadata, which helped us find the document,” Melendez said. “It was super helpful because we didn’t have time to sit there and look through all those additional documents.”

Simplifying Workflows with Intuitive Features

The firm relies on Everlaw’s intuitive features to simplify complex workflows so they can move nimbly without sacrificing quality.

"I rave about Everlaw," Melendez said. "Previously, we reviewed everything by eye, which was exhausting. I love that even handwritten words can be found by searching for the actual word, which is great from a review standpoint. Everlaw just makes life so much easier."

Many of Hamilton Law Firm’s matters involve heavy email and text message data, which makes filters for date ranges, senders, and recipients essential. These data types are notoriously difficult to search through and can be time-consuming to process.

"I absolutely love searching primary date fields when working through emails,” Melendez said. “I use it all the time. These tools cut through messy productions, including flat PDFs, and help us quickly surface the most important information.”

Bypassing the manual, administrative bottlenecks that often plague smaller teams allows the firm to manage the same volume and complexity as their larger counterparts without missing a beat.

Scaling Ambition with the Right Partner

Hamilton Law Firm is proof that in the modern legal landscape, agility often beats volume. By treating technology as a force multiplier, the team has leveled the playing field, allowing them to stand toe-to-toe with the largest firms in the country.

With Everlaw handling the heavy lifting of data processing and review, Hamilton Law Firm can focus on what they do best: building winning strategies for their clients. As they continue to take on complex matters, they do so with the confidence that they have a partner in Everlaw that scales right alongside them.

"Everlaw is seamless,” Melendez said. “It cuts my workday in half. I would absolutely recommend it."

Hamilton Law + Everlaw

2026-04-26T08:35:44Z

Hamilton Law + Everlaw

The Top Ediscovery Certification Programs in 2026

2026-04-26T08:35:44Z

The Top Ediscovery Certification Programs in 2026

by Justin Smith

Reading Time — 5 minutes

January 27, 2026

Electronic discovery, or ediscovery as it is known, is one of the tenets of legal work today. The digital transformation of our world means that every text, email, Slack message, and Zoom call is potentially discoverable and fair game in court. Everyone from partners to paralegals are confronted with this data every single day.

The ability to comb through millions of documents to find the data that’s essential to your case is fast becoming an important skill for every type of legal professional. As the amount of potentially discoverable data grows, navigating the ediscovery process will only take on greater importance.

Ediscovery certification is a way to learn more about the discovery process generally, and legitimize your skills to become an ediscovery expert. Professionals can leverage it as a way to invest in their career while also deepening their knowledge of the industry.

What Is Ediscovery Certification?

Ediscovery certification validates the expertise and knowledge of legal professionals in managing electronic data within the legal framework. It encompasses a broad range of skills, from understanding legal requirements and litigation processes to mastering the technology used to handle digital evidence.

Those certified in ediscovery have demonstrated their ability to effectively manage ediscovery projects, ensuring that digital evidence is handled in a legally compliant and efficient manner.

Why Is Ediscovery Certification Important?

In today's digital age, the volume of electronic data generated and stored has exploded, making ediscovery a necessary component of legal proceedings. Ediscovery certification is crucial because it:

Ensures competency. Certification confirms that professionals possess the necessary skills and knowledge to navigate complex ediscovery challenges.
Promotes standardization. It helps standardize practices across the industry, leading to more consistent and reliable ediscovery processes.
Enhances credibility. Certified professionals are often seen as more credible, which can be a significant advantage in legal proceedings and within the professional community.
Advances careers. It provides individuals with a competitive edge in the job market, leading to better job opportunities and career growth.

What Are the Different Types of Ediscovery Certification?

Ediscovery certifications vary widely, catering to different expertise levels and professional needs. There are certifications that focus solely on the legal aspects of ediscovery, others that delve into the technology behind it, and still more that are concerned with the process of ediscovery itself.

Common types of certifications relevant to ediscovery professionals include:

Certified ediscovery specialists. Focuses on the legal and technical aspects of ediscovery.
Legal project management certification. Emphasizes the management of ediscovery projects.
Digital forensics certification. Concentrates on the technical side of ediscovery, including data collection and analysis.
Information governance certification. Covers how ediscovery processes fit within broader data management and compliance frameworks.

What Are the Top Ediscovery Certification Programs in 2026?

Here are some of the top ediscovery certification programs in 2026.

ACEDS

The Association of Certified E-Discovery Specialists (ACEDS) offers one of the most respected ediscovery certifications in the field. Their Certified E-Discovery Specialist (CEDS) certification is renowned for its comprehensive coverage of the legal and technical aspects of ediscovery.

The CEDS exam consists of 145 multiple choice questions, and is considered one of the more rigorous certification exams. It also comes with bonuses like a digital badge, two-year CEDS certification, one-year ACEDS membership, access to the ACEDS mentorship program, and more.

Everlaw Product Certification

The Everlaw Product Certification program is geared towards both legal professionals and IT specialists. You can receive certifications in a range of disciplines, from the Reviewer Certification, which includes document review and search fundamentals, to the Litigation Support Manager Certification, which is perfect for Everlaw power users looking to get the most out of the platform.

Courses are separated out by modules, breaking the information out into manageable pieces. Each track also includes access to things like on-demand office hours, learning content, maintenance exams, and webinars to help along the way.

Everlaw is one of the leaders in the ediscovery training and certification space for its emphasis on using technology to streamline the ediscovery process. A certification credential from the Everlaw Product Certification program helps you prove the knowledge gained in the Everlaw platform. Here’s an overview of each type of certification offered:

Reviewer Certification

The Reviewer Certification covers document review and search fundamentals. It’s great for beginners and professionals who are conducting document review on the Everlaw platform.

Storybuilder Certification

The topics included in the Storybuilder Certification include timeline, collaborative drafting, and deposition workflows. It’s worthwhile for beginners and legal professionals who are collaboratively building their case narrative in Everlaw.

Data Operations Certification

The Data Operations Certification concerns data uploads and production. It’s useful for those looking to conduct their own uploads and productions, and professionals who are responsible for their team’s data operations.

Everlaw AI Certification

The Everlaw AI Certification covers Everlaw features like clustering, predictive coding, and all of Everlaw’s generative AI feature set. It’s best for intermediate and advanced Everlaw users who are familiar with TAR and predictive coding workflows.

This certification can also help you gain experience in Everlaw’s AI tools, which will become especially important as this technology continues to impact the profession.

Managing Review Certification

Everlaw’s Managing Review Certification goes over topics like document review, review management, and assignments. It’s recommended for professionals who are building or supporting their team’s document review workflows through Everlaw.

Project Manager Certification

The Project Manager Certification goes over database and case setup, data exploration, managing document review, and includes reviewer and data operations specialized tracks. It’s best for professionals who are overseeing their organization’s project administration efforts.

Litigation Support Manager Certification

The Litigation Support Manager Certification covers the full Everlaw platform functionality, and includes all foundational, specialized, and advanced tracks. It’s great for Everlaw power users and professionals who are fully supporting their organization’s use of Everlaw. Beginner and intermediate users of Everlaw can expect to complete this certification over time.

Arkfeld Ediscovery Education Center

The Arkfeld Ediscovery Education Center programs are known for their emphasis on the legal aspects of ediscovery, offering courses that blend legal education with practical ediscovery applications. Their certifications focus primarily on law firms and offer CLE credit.

They offer four different levels of ediscovery certification, ranging from a basic, 7-hour online course to a master ediscovery class, which features live instruction and involves reading materials and independent classwork.

NALA

The National Association of Legal Assistants (NALA) offers certification that includes ediscovery as part of its broader legal assistant certification program, making it ideal for legal support professionals who want to expand their ediscovery knowledge.

NALA's certification program emphasizes the role of support staff in the ediscovery process, covering topics such as document review, legal holds, and data privacy. It's a pathway for legal support professionals to validate their skills and advance their careers in the realm of ediscovery.

CLS by BARBRI

Certified Legal Specialist (CLS) by BARBRI focuses on providing legal professionals with a solid foundation in ediscovery principles, along with practical skills in legal technology tools. As one of the top continuing legal education providers in the country, they provide a range of courses and curriculums to all types of legal professionals.

Their ediscovery certification course is endorsed by ACEDS, and is 7 weeks long, with 24/7 course accessibility and self-paced online classes. Depending on the school you take the course with, you may need to pay for course materials like textbooks in addition to the price of tuition.

University of California San Diego Extended Studies

The UC San Diego Extended Studies program offers an Ediscovery and Litigation Technology Certificate designed for legal professionals looking to further their career and learn more about the latest in legal technology. The courses are taught by working legal professionals and cover topics like ESI, the Electronic Discovery Reference Model, litigation readiness, and more.

The course is offered exclusively online, and can be completed in six to twelve months depending on the student. They also offer up to 40 hours of MCLE credit, which is helpful for legal professionals who need to meet their annual continuing education requirements.

Is Ediscovery Certification Worth It?

Ediscovery certification is undoubtedly worth it for those looking to specialize or advance in this field. As the demand for skilled professionals continues to grow across the ediscovery industry, professional certifications can significantly enhance your marketability, credibility, and career advancement opportunities. It demonstrates a commitment to your profession and a mastery of the skills necessary to navigate the complexities of ediscovery and litigation support.

As the ediscovery field continues to grow and expand, training programs and certifications will only become more developed and detailed, providing professionals with a wider breadth of skills.

Whether you're a legal professional, IT specialist, or somewhere in between, pursuing an ediscovery certification in 2026 could be a worthwhile and strategic career move.

Editor's note: This post was originally published on Mar. 7, 2024, and updated on Jan. 27, 2026, with fresh information on the top ediscovery certification programs for 2026.

Ediscovery Costs in 2026

2026-04-26T08:35:44Z

Ediscovery Costs in 2026

by Justin Smith

Reading Time — 7 minutes

January 22, 2026

As the amount of discoverable data and electronically stored information (ESI) grows and the complexity of file types increases, the tools needed to meet and anticipate these challenges also must adapt. 2026 presents an opportunity to take advantage of new technologies in an effort to reduce costs and process data faster than ever before.

Managing ediscovery costs has become a hot topic amongst legal teams. In 2026, the ediscovery market size is expected to grow to over $16 billion, and could reach over $25 billion in the next five years.

There’s hardly any guidance from courts regarding skyrocketing prices, and many firms have been forced to pass rising costs on to their clients as a result. Although there’s hope that generative AI will help bring down costs by performing tasks like document review and batch summarization, the reality of it being consistently relied upon is still a ways off, not to mention the cost that will be associated with using the technology in its own right.

So, what is the true cost of ediscovery, and what does the price tag mean for your case? How can you protect your firm (and your budget) from inflated prices? Although it can be difficult to provide specific price ranges without knowing the ins and outs of a particular case, it is possible to at least estimate ediscovery costs based on certain factors, and strategize ways to keep costs down.

Price vs. Value

Price and value are two key components to consider when assessing ediscovery costs, and an important delineation to make. While the price is what you pay for ediscovery, the value is what you get in return.

When it comes to ediscovery software, you might pay a high price for the most comprehensive solution, but the value in return might not be great if all the bells and whistles aren’t necessary or suited to your needs.

Finding that perfect marriage of price and value can take time, but building a relationship with an ediscovery software provider can help drive down ediscovery costs and greatly benefit your organization.

What Drives Ediscovery Costs?

While there isn’t one single factor that contributes to rising ediscovery costs, there are drivers that account for a significant proportion of the total price tag.

Document Review

The document review process is the primary driver of ediscovery costs. According to the American Bar Association, it accounts for over 80% of total litigation spend, which is equivalent to roughly $42 billion per year. Determinants like your chosen ediscovery software, the amount of documents needing review, and whether you’re able to do the work in-house can make the price vary, but there’s no getting around the fact that the entire document review process will take up the majority of your typical litigation budget.

This is a concern for the entire legal industry, as the increasing amounts of data in our expanding digital world means the amount of information required for review during the discovery process will only grow in 2026 and beyond.

Data Type and Size

The specific types of data also play a huge role in the price of ediscovery. For example, a simple word document will likely cost less to upload and process than a CAD file or Slack message because of its relatively small size and straightforward search capability. A more complex file might require additional tools and time to process, adding to the cost. If your data is full of these complex files, it will be a significant expense during ediscovery.

Similarly, having a large amount of data sets will take extra time and money to process as well. Data collection can be an arduous task, and the more there is, the more time it will take to gather, and the more expensive it will be.

According to the RAND Institute for Civil Justice, it cost $18,000 to manage one gigabyte of data through the entire review process in 2012. Contrast that with 2026, when most ediscovery software charges rates based on an all-in, per-case or per-month billing cycle that average around $25 per 100 gigabytes, and you can see how advancements in technology have provided huge savings.

Staffing

With so much data to process and documents to review, there has to be staff on hand to actually do the work. Many firms do this through contract attorneys, who are brought on solely to assist during discovery for a specific case.

Hiring, onboarding, and training contract attorneys is an expensive and time-consuming process that can leave you lagging behind. For example, with the average hourly rate for a contract attorney at a little more than $50 an hour, you’re wasting over $2,000 for every week spent learning a new software, and not working on your case. As the volume of data grows, an intuitive, easy-to-use ediscovery software is imperative to helping these contract attorneys get working on your case as soon as possible.

Hidden Fees That Add Up

While these might be some of the main factors that drive the high price of ediscovery, there are also hidden fees that contribute to rising costs.

Data Processing

With each gigabyte costing around $25-$100 to process depending on the pricing plan of your chosen ediscovery software, time is literally money when it comes to processing data. When you cull your data during the ediscovery process, you’re preparing it for review. Things like deduplication, email threading, and clustering utilize automation to organize relevant data in an efficient way, which can help you find specific pieces of information quickly. If it takes several hours for your firm to upload just a few gigabytes, you’re going to pay more both in price and time than a firm that can upload thousands of gigabytes in that same period.

Although data processing times can depend on the ediscovery platform you use, any delays are still likely to be attributed to you in the eyes of the court, which can lead to fines and additional penalties if it’s late. This makes the type of ediscovery software you choose increasingly important, especially as data and file types only grow more complex. A platform that has the ability to handle complex file types can really go a long way in saving money.

Software Type

While on-premise ediscovery software providers have been popular in the past, they are now seen as outdated and slow when compared to the cloud-based software of today. On-premise systems often require steep up-front investments that don’t let you control your own data in-house, and might even have you pay a per-user fee for your desired number of custodians.

Cloud-based software streamlines the entire ediscovery process, and allows you to keep all your data in-house. Many of these solutions feature speedy processing times, convenient pricing, and many other features and tools to help maximize your ediscovery experience.

Early Case Assessment

Early case assessment (ECA) serves as a helpful form of project management in the long run, but it also costs money in the short term. Your expenses will likely be proportional to the volume of data you have to get through, and the complexity of the file types within it.

Integrations

Clients use many different types of technological tools in their daily operations, which means an ediscovery platform needs to be able to integrate with all of them to be effective. For example, if an organization uses Gmail for email, Microsoft Office to house work products, and Slack for messaging, all of that data will need to be produced during discovery, and therefore integrated into the ediscovery solution. Some software charges for additional integrations, or have fee structures in place that raise prices for certain accommodations.

Data Preservation and Security

Keeping your data safe and secure is of the utmost importance. Data breaches occur more often than you think, and can cost in the billions of dollars. Plus, if an unauthorized party gains access to your information, it can be disastrous for your firm, clients, and case. Your ediscovery software should prioritize security to ensure your data is never compromised. Data preservation is an expensive but necessary part of budgeting for ediscovery expenses in 2026.

The Role of Generative AI

Generative AI has been touted by many in the legal profession for its ability to help speed up manual processes and lower costs. While it’s yet to fully enter the mainstream, 2026 is likely to see many legal teams begin leveraging it in some form in their ediscovery practice.

For example, a user can upload document sets to a generative AI tool, and it will return a table with document by document summaries the user can scroll through to see what those documents are about. Users can also use a generative AI tool to classify and categorize documents based on specific criteria in an effort to review them in a more efficient way.

Ediscovery software providers are already incorporating this technology into their platforms, with payment approaches varying between subscription models, credits, user seats, and more. This also means costs will vary. However, because early use cases of generative AI are so promising, organizations will consider whether the potential for increased efficiency is worth the price.

Evolving Pricing Models

In 2026, the ediscovery market has reached a critical inflection point as providers pivot away from the legacy per-gigabyte pricing model toward more predictable, value-based structures. This transition is driven by client demand for budget certainty and a maturing cloud infrastructure where costs are tied to compute usage rather than just storage volume.

Consequently, flat-fee subscriptions and all-in per-case monthly billing have become the standard, often encompassing unlimited data processing and hosting to eliminate the financial penalties traditionally associated with large datasets.

The integration of generative AI has further transformed these models, with many leading platforms now bundling AI capabilities into their base subscription tiers as a standard utility. This evolution allows legal teams to prioritize strategic case assessment over volume-based cost management, effectively stabilizing litigation budgets even as global data volumes continue to surge.

Keeping Ediscovery Costs Down in 2026

So, with all the up front and hidden costs associated with the ediscovery process, how can you actually keep ediscovery costs down in 2026? The first and most important step is to invest in solutions that will last. Although it might be tempting to go for cheaper or unproven alternatives, this can ultimately hurt you in the end. Something might promise to be cheap, but could end up costing more long-term, or a solution could simply not work, leaving you short on options.

The easiest way to achieve ediscovery cost savings in 2026 is to invest for the long-term. That means working with a cloud-based software provider to help identify your needs, discuss potential areas for improvement, and build a true partnership. It might be more expensive up front to go with an alternative software, but ultimately it will be the most cost effective option. You can survey prospective service providers by getting demos of their products, studying use cases, and speaking with representatives who are knowledgeable about your market.

Evaluating your priorities and budget before beginning your search for an ediscovery solution will help immensely in finding the right software for you. If you plan to take on major litigation in the next year, your needs and budget will be much different than a firm that is looking to establish an ongoing partnership for general ediscovery services.

Additional Resources

Everlaw is an all-in-one cloud-based ediscovery software provider built for law firms, corporate legal departments, and government agencies of all shapes and sizes. Market experts who cater specifically to legal professionals can help walk through the tools and resources that fit your organization, allowing you to customize the platform as you see fit. Everlaw’s transparent pricing model means you’re never surprised by hidden costs, and always know where you stand.

Editor's note: This post was originally published on Jan. 9, 2024, and updated on Jan. 22, 2026, with fresh information on ediscovery costs for 2026.

Introducing Fact Management: A New Architecture for Case Strategy

2026-04-26T08:35:44Z

Introducing Fact Management: A New Architecture for Case Strategy

by Justin Smith

Reading Time — 3 minutes

January 13, 2026

When a new case begins, litigators have to quickly get a sense of the key players, rough chronology, and core allegations to start forming their strategy. But then, the waiting game begins. You’re stuck waiting for documents to be collected, processed, and batched for review before you can get into the real details of the case.

Once the documents finally arrive, however, you face a new structural barrier: your strategy and your evidence often exist in two completely different worlds. While the evidence resides in a review platform, your evolving narrative can be captured in static, disconnected tools like Word documents and Excel spreadsheets. Attempting to connect them requires a manual, high-risk cycle of exporting, copy-pasting, and verifying Bates numbers.

Everlaw’s new Fact Management tool bridges this divide by unifying your discovery and case strategy in a single platform, allowing you to start building your winning argument from the first moments of your case. It transforms Everlaw’s Storybuilder feature into the backbone of your case narrative, allowing you to frame your story before you’ve even reviewed a single document.

What Is Fact Management?

Fact Management exists within Everlaw’s Storybuilder tool as a way to lay out the facts of your case so you can establish key timelines and events before you receive any documents, and begin framing your narrative almost immediately.

Instead of treating a case as a flat, overwhelming list of documents, Fact Management allows you to organize your case around specific events or allegations.

Organize your case around specific events and consolidate facts into a single master view.

By creating distinct timelines to isolate specific narratives—like a key witness or a core issue—you can quickly gain clarity in your case. You can also validate broader strategy by consolidating your facts into a single master view, allowing you to instantly spot how individual facts intersect, contradict, or leave gaps in the big picture.

Additionally, since Fact Management exists within the shared workspace of Storybuilder, your entire team—from associates reviewing documents to partners drafting motions—can operate from a single source of truth. You can capture known facts immediately and establish a chronology that drives your review, rather than waiting for the review to reveal the timeline.

Fact Management Features

Everlaw’s unified workflow means you never have to leave the platform, so your team can be supported for the entire lifecycle of your case strategy—from the initial client interview to the final argument.

Fact-First Architecture

When you’re going through the ediscovery process, the narrative of your case doesn't always align perfectly with timestamped emails or PDFs.

Everlaw’s Fact Management utilizes a fact-first architecture that allows you to create facts independently of documents. It supports dateless entries and fuzzy dates to match real-world complexity, which is essential for the ea rl y stages of a case where details are murky.

Everlaw's Fact Management allows you to lay out the facts of your case so you can establish key timelines and events before you receive any documents.

For instance, if you are aware of a handshake agreement that occurred sometime last summer, you shouldn't be prevented from logging that pivotal moment just because you lack a specific date or file. With a fact-first architecture, you can create a fact in Storybuilder and upload the associate supporting documents to help frame your narrative using approximate dates, ensuring your timeline reflects the truth of the event rather than just the limitations of your metadata.

Curated Timelines

As a case grows, a single chronological list of every event can become unmanageable. When you’re dealing with thousands of facts across multiple years, a flat list provides data, but not clarity.

Fact Management allows you to master case complexity through curated timelines to isolate specific data subsets, such as a key witness or specific legal issue.

For example, if you’re trying to pinpoint inconsistencies in a fraud case, you can create a timeline that’s specific to the CFO’s communications and a separate one for board meetings. And when you need the big picture, you can leverage Fact Management’s "View All Facts" master list, which allows you to aggregate all entries to inspect the complete case record in a single view, making it effortless to spot exactly where those individual timelines intersect, contradict, or leave gaps.

End-to-End Integration

The most persistent pain point in litigation workflows is the "copy-paste” chaos. Attorneys often find a critical document in the review platform, download it, and then paste the text into a Word document to build a deposition outline. If the document is re-produced or the coding changes, the external document is instantly outdated.

Fact Management solves this through end-to-end integration within the Everlaw platform, ensuring that your strategy is woven into every work product you create. And since you’re able to remain in Everlaw for your entire case process, your data is kept in a secure environment rather than split between disparate tools.

This integration transforms the deposition preparation process. When you uncover a hot document in the Review Window, you can instantly turn that finding into a fact without switching tabs. Later, when you are building your outline in the Depositions tool, that fact—and its link to the live evidence—is ready to be pulled in naturally. You avoid repeating work and ensure that your team is always operating from a single source of truth, rather than relying on static exports that go stale the moment they are saved.

Unifying Your Case Strategy

For too long, litigation strategy has been fragmented across disconnected tools, forcing legal teams to work in silos and miss connections.

With Fact Management, you can unite your discovery and your case strategy, empowering you to stop letting documents dictate your process. Instead, you can build your story on facts and master the complexity of your case with curated timelines.

UCSF Industry Documents Library + Everlaw

2026-04-26T08:35:44Z

UCSF Industry Documents Library + Everlaw

How the Industry Documents Library and Everlaw Teamed Up to Drive Industry Accountability

2026-04-26T08:35:44Z

How the Industry Documents Library and Everlaw Teamed Up to Drive Industry Accountability

UCSF, The Forever Lobbying Project, and Le Monde Shine a Light on Public Health with Everlaw for Good

by Justin Smith

Reading Time — 5 minutes

January 6, 2026

In an era where information is abundant but transparency can be scarce, the work of investigative journalists and public archives is more crucial than ever. Their dedication to unearthing critical data and making it accessible to the public plays a vital role in holding powerful entities accountable and informing public discourse.

This commitment to transparency is exemplified by Rachel Taketa, the Processing and Reference Archivist at the University of California San Francisco (UCSF) Industry Documents Library (IDL), who has dedicated her career to making internal industry documents available for public health research and advocacy.

Taketa's work at the IDL involves managing an immense collection of documents from industries impacting public health, including tobacco, opioids, and chemicals. Her efforts are not just about preserving records, but about actively providing access to information that can lead to breakthroughs in the pursuit of justice for the public good.

The UCSF Industry Documents Library: A Beacon of Public Health Transparency

Since 2002, the IDL has served as a critical online archive, making publicly disclosed documents from industries that impact public health readily accessible.

It originally began as a repository for tobacco industry documents, born from landmark lawsuits in the late 1990s, and has since expanded to include materials from the opioid, chemical, food, and fossil fuel sectors. Taketa has been with the IDL since 2005.

“We preserve and provide access to documents that shine a light on the practices of these industries and uphold UCSF’s allegiance to social justice and public health,” Taketa said when describing the IDL’s mission. The sheer scale of this undertaking is immense, with the archive now housing over 25 million documents.

A significant challenge for the IDL, especially with newer collections like those from opioid litigation, is this high volume of documents and the need for meticulous redaction of personal information. Taketa noted the drastic increase, from receiving 15 million tobacco documents over the course of 20 years, to now getting millions of opioid documents all at once.

"In the past, we received documents that had already been redacted or did not need a comprehensive level of care. With the opioid materials, however, we’ve had to create a workflow for manual redactions," Taketa stated. "Our first opioid collections came to us completely unredacted, and with only three people on staff, we realized we were going to need some sort of partner or outside organization to help us out.”

This is where Everlaw became a game-changer. Taketa remembered Everlaw from a presentation given to her team almost a decade prior, and realized its potential for handling massive document sets and streamlining the redaction process.

"What Everlaw has allowed us to do is to actually have a project at all," Taketa said. "We couldn't put any of these documents online if they weren't reviewed and redacted for personal information. And if we can't make a concerted effort to protect people's information, then we can't put them online. If we can't put them online, our entire project is sunk.”

Taketa uses Everlaw throughout many of her projects for the IDL. She leverages Everlaw's visualizations to get a handle on content and custodians, search term reports for identifying potential personally identifiable information, and the ability to identify duplicates and attachment families.

“You can’t really break Everlaw, which is always helpful,” Taketa said.

The Forever Lobbying Project: A Multinational Investigation

In Europe, a group known as the Forever Lobbying Project was also running into a similar situation as the IDL, with a need to process and make thousands of documents available quickly.

The Forever Lobbying Project is a groundbreaking cross-border investigation, involving 46 journalists and 29 media partners across 16 countries, delving into the lobbying efforts surrounding per- and polyfluoroalkyl substances (PFAS), often called "forever chemicals.”

The team collected over 14,000 unpublished documents on PFAS, making it the world's largest collection to date on the topic. A significant portion of these documents (4,796) were obtained through 184 Freedom of Information requests to public bodies across Europe. Additionally, 3,393 attachments were downloaded from the European Chemicals Agency, and 6,026 documents came from the U.S. Environmental Protection Agency and litigation between Minnesota and 3M.

Some of the journalists involved had experience using the IDL for previous projects, and reached out to Taketa for help in uploading all those documents. It quickly became clear that due to the various time zones and regulations the Forever Lobbying Project was operating with, Taketa wouldn’t be able to assist with all their needs.

“I initially met with the project leads to walk them through what our system looks like, what we do, and how we get documents in, and it seemed like the lift was a bit difficult for them technologically,” Taketa said. “They asked if we would be one of the repositories that hosts the documents, which I was happy to do, but they also wanted to redact them first, which led to issues with the GDRP regulations the EU has in place. I pointed them to Everlaw and said, ‘Why don't you try and go through the Everlaw for Good program?’ And that's what happened.”

Journalists Stephane Horel from Le Monde, Leopold Salzenstein from Arena for Journalism in Europe, and freelancer Luc Martinon participated in the project, and worked directly in the Everlaw platform to help prepare these documents for release.

Crucially, many of these collected documents contained personal data, such as email addresses, telephone numbers, or physical addresses, which, for privacy reasons and legal prohibitions in both the EU and US, could not be made public. Deleting this information manually would have been an insurmountable task.

“In the E.U. and the U.S., you can't publish documents with personal data like phone numbers, addresses, and that sort of thing,” Horel said. “And to do that manually, with this huge number of documents, would have been impossible.”

Horel and her team quickly got up to speed in the Everlaw platform, and were able to start redacting the necessary information.

“Everlaw was a super quick miracle solution that allowed us to do this automatic redaction in the cleanest way possible,” Horel said.

Everlaw's Role in Fueling Transparency and Impact

It was Rachel Taketa and the UCSF Industry Documents Library that connected the Forever Lobbying Project with Everlaw.

Le Monde journalists initially approached UCSF for advice on creating their own repository, but due to time constraints and technological lift, decided to have the IDL host their documents. However, the need for redaction before hosting led Taketa to recommend Everlaw.

"Rachel Taketa showed us how the UCSF team uses Everlaw to automatically redact personal information from documents," Horel recalled. "The platform seemed easy to use and we were impressed by its ability to spot and redact email addresses and phone numbers. We realized it was exactly what we needed."

Through the Everlaw for Good program, the Forever Lobbying Project gained free access to the platform, enabling them to efficiently redact sensitive information. While they had already been using another tool for analysis, Everlaw was instrumental in making the publication of their vast document collection possible.

Their investigative work revealed staggering findings, including an estimated cost of cleaning PFAS contamination in Europe of €2 trillion over 20 years if emissions remain unrestricted. By analyzing hundreds of documents, the project also shed light on the ongoing efforts of industry lobbyists to water down PFAS regulations at the EU and national level.

A Partnership for Progress

The collaboration between the IDL, investigative journalists from the Forever Lobbying Project, and platforms like Everlaw demonstrates how technology can bridge the gap between vast amounts of information and public accessibility, ultimately fostering greater transparency and accountability in critical areas of public health and policy.

Everlaw's intuitive design and robust features, particularly its batch redaction capabilities and ability to handle massive data sets, proved essential for both of these organizations in overcoming significant logistical hurdles.

“By making these documents publicly available, we hope to improve the democratic process around chemical regulations, and foster a better awareness and understanding of the corporate influence on chemical regulations,” Salzenstein said.

Thanks to this project and Everlaw's involvement, Le Monde and its partners have already published over 100 stories, podcasts, and TV shows related to the Forever Lobbying Project.

The Human Element in the Age of AI: Judges Weigh in on Discovery and Deepfakes at Everlaw Summit '25

2026-04-26T08:35:44Z

The Human Element in the Age of AI: Judges Weigh in on Discovery and Deepfakes at Everlaw Summit '25

by Justin Smith

Reading Time — 5 minutes

December 18, 2025

The legal profession stands at a powerful crossroads, defined by both the explosive growth of discoverable data and the rapid rise of generative AI. This environment challenges the core functions of the justice system, demanding that the judiciary reconcile its tradition of caution with the urgent need for innovation.

This tension between tradition and technology set the stage for a candid and compelling judges panel held on the final day of Everlaw Summit ‘25.

Moderated by Everlaw CLO Gloria Lee, the panel featured a distinguished group of legal leaders who brought perspectives from federal and state benches across the country, including Judge Joy Flowers Conti (W.D. Pa.), Judge David Cunningham (Superior Court, Los Angeles County), Judge Willie Epps (W.D. Mo.), Judge Young Kim (N.D. Ill.), and Judge Victoria Kolakowski (Superior Court, Alameda County).

They witnessed firsthand how technology is reshaping the legal landscape, grappling with the complexities of ediscovery, the challenges of authenticating digital evidence, and the potential impact of AI on everything from legal research to courtroom procedures.

The collective message from the bench was clear: While technology offers extraordinary tools for efficiency, the human judge remains the indispensable foundation for ensuring a fair, transparent, and credible justice system.

Gloria Lee (left) moderates the judges panel during Everlaw Summit '25.

Bridging the Technology Gap

The conversation began by addressing the dichotomy between the legal technology industry’s rapid innovation and the judiciary’s characteristically cautious approach to adoption. Judge Conti, a veteran in the ediscovery world, acknowledged this in her opening remarks.

“I'd say the courts historically have lagged about ten years behind what is happening technology-wise in the legal profession,” Judge Conti said.

"Justice delayed is justice denied, and if AI can help reduce the timeline for some of these cases, it can be extraordinarily helpful."

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Judge Epps also discussed his courtroom’s technology adoption journey, noting how excited he was when court migrated to a software program after years of using paper binders.

“When I joined the bench in 2017, I used to go to court with three ring notebook binders full of paper,” Judge Epps said. “Then the administrative office finally bought this incredible program called OneNote, and I was so giddy that we finally went paperless. Everything I do now is on my iPad. I had an intern once who said, ‘Judge, when I was in junior high school, my teacher used OneNote to give us our assignments. Why are you so excited about this antiquated Microsoft product?’ And I said, ‘Well, you take what you can get.’”

Judge Epps (far right) speaks during Everlaw Summit '25.

Judge Kolakowski also discussed how data security is a critical issue that is likely slowing down court adoption of technology.

“There are many people who are concerned about data security issues,” Judge Kolakowski said. “They're worried both about intrusions of outside networks and information into the local courts, and the idea that if you put something into a generative AI system, you're now making it public to the world. This fundamental concern prevents judges and court staff from utilizing powerful new tools for fear of compromising confidential case information.”

AI as the New Law Clerk

Despite the caution around judicial adoption of generative AI, the panel expressed genuine excitement about its potential as an essential tool for legal practitioners, especially in high-volume, complex cases. The sentiment was that AI is not a replacement, but a force multiplier.

“In L.A. County, our filings have doubled since the pandemic, and many of our judges are incredibly overworked,” Judge Cunningham said. “We have a lot of mass tort cases, many of them surrounding wildfire litigation in particular, and AI could be really useful in organizing that huge amount of data. Justice delayed is justice denied, and if AI can help reduce the timeline for some of these cases, it can be extraordinarily helpful.”

Judge Cunningham (Center) speaks during Everlaw Summit '25.

Judge Kim provided a practical, present-day example of how he uses AI tools in his practice to enhance his own efficiency and preparation.

“I’ve been using AI tools for things like summarizing long opinions and documents, creating timelines, drafting small paragraphs on standards that I am familiar with so I can easily verify the output, and similar use cases," Judge Kim said.

Alongside generative AI’s usefulness, however, the conversation also focused on trust and transparency with the technology. Judge Conti spoke about her fear that an over-reliance on technology like generative AI could erode public confidence in the judiciary.

“I worry about people not trusting the judiciary anymore,” Judge Conti said. “Transparency is very important, especially right now in the early stages of generative AI adoption.”

"There's a lot of discretion that we have to exercise as judges, and the human element is indispensable."

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The judges agreed that the solution lies not just in waiting for new tools, but in proactive education and rule-making. Judge Cunningham noted the steps being taken in California, and how he’s thinking about AI now that he’s been appointed to chair an American Bar Association (ABA) working group. He stressed the need to educate on how AI impacts ethical obligations, particularly concerning competence and attorney-client privilege.

“There are a number of issues that we need to educate ourselves on when it comes to generative AI, both from a judicial perspective and also how it impacts your ethical obligations as attorneys,” Judge Cunningham said. “But they're extraordinary tools, and at least in California, we're trying to take the lead on this.”

The Problem of Deepfakes

Perhaps the most sobering portion of the panel focused on the threat of deepfakes and the immense pressure this places on the court’s fact-finding role.

Judge Kolakowski shared a powerful anecdote from a recent case where a self-represented litigant submitted videos that were clearly fabricated.

Judge Kolakowski (right) speaks during Everlaw Summit '25.

“We had a Ring camera video where the background is black and white, and the people in the front were in color,” Judge Kolakowski said. “There were videos where somebody was talking seemingly forever. And so it was obvious that those were really bad.”

The concern for the legal profession is generative AI’s rapid improvement, which has the potential to make it difficult for the court to determine what’s real, especially without forensic resources. This forces judges to rely on established, yet newly challenged, rules of authenticity.

"The hard part is that we tend to believe what the computer tells us,” Judge Kolakowski said. “We tend to believe what our eyes show us. And how do we get past that? How can we address a world where we can't believe what we can't believe? We can't necessarily assume that something that somebody that we trust hands us is actually real."

The Indispensable Human Element

Concluding the panel, Gloria brought the focus back to the fundamental nature of the judiciary: solving human problems. The judges unanimously affirmed that no technology, no matter how advanced, can replace judicial discretion, judgment, and empathy.

The core message centered on three vital principles: fairness, perception, and human observation.

“Efficiency is important,” Judge Kim said. “You all are here to be efficient in your work. But as judges, we also have to be concerned about perception. Perception is our reality, and for the third branch to have credibility, we have to be perceived as fair.”

Judge Kim speaks during Everlaw Summit '25.

Judge Epps highlighted the democratizing potential of generative AI for increasing access to justice, stating it will improve the quality of filings for those who cannot afford representation. However, he also warned against eliminating the human factor.

“There's a lot of discretion that we have to exercise as judges, and the human element is indispensable,” Judge Epps said. “As long as we’re dealing with human problems, humans can’t be eliminated from the decision making process. The law evolves, and society evolves, but as the technology changes, we have to present a human reaction to it.”

Finally, Judge Kolakowski offered the panel’s closing sentiment on the limits of technology in the courtroom, distinguishing between questions of law and questions of fact—the latter of which relies entirely on human observation:

"When it comes to questions of fact, I cannot imagine anytime in the near future where a machine can decide that,” Judge Kolakowski said. “We need to have a human, whether it's a jury or a judge, who can evaluate the evidence and decide what makes sense and what doesn't, and what's real and what's not."

The panel offered a valuable bridge between the urgency of technological innovation and the enduring principles of fairness, transparency, and human judgment that define the rule of law. It served as a powerful reminder that while AI is an essential tool for the legal community, the final verdict will always be rendered by a human judge.

Celebrate the Everlaw Summit ‘25 Award Winners

2026-04-26T08:35:44Z

Celebrate the Everlaw Summit ‘25 Award Winners

Recognizing the Individuals and Organizations Transforming Legal Tech

by Rachel Gonzalez

Reading Time — 5 minutes

December 17, 2025

Everlaw Summit ‘25 delivered three days of thought-provoking panels, in-depth product workshops, meaningful networking, and more.

From Jad Abumrad’s keynote on how to have better conversations to the many breakout sessions on topics like generative AI, litigation, and the future of ediscovery, there was no shortage of discussion around how legal professionals can transform their work.

In an effort to recognize some of the individuals and organizations that are working to create change in the industry, the Everlaw Summit Awards were held across two days on the Summit mainstage.

After receiving many nominations in the lead up to Summit, the winners were selected by our esteemed panel of judges, made up of:

Jeff Comeau, Senior Director, Litigation and Antitrust, Align Technology
Gloria Lee, Chief Legal Officer, Everlaw
Stephanie Wilkins, Director of Content, LegalTechnology Hub
Sheneika Hurley, Senior Solutions Architect, Everlaw
Jessica Wan, Partner, Ferguson Case Orr Paterson

We want to congratulate all our Everlaw Summit Awards finalists and our winners this year!

Corporate Breakthrough of the Year

For corporate legal departments transforming their approach to litigation and investigations in-house.

Winner: HP, represented by Thane Vallette, Associate General Counsel

HP has not only standardized on Everlaw for their core ediscovery work, but has also pushed its use far beyond traditional boundaries. Thane and his team are currently piloting Everlaw to tackle the challenge of data overload, estimating the potential to eliminate 25-30% of their stored, redundant, or obsolete data through the use of the platform.

Thane Vallette (Center) accepts the award for Corporate Breakthrough of the Year on behalf of HP.

On the generative AI front, HP utilized Everlaw^AI Assistant to achieve massive efficiencies, such as rapidly pinpointing assignment provisions during due diligence and reducing a 500-hour orphaned data extraction project to approximately 12 hours.

Thane has also led HP’s involvement in the Everlaw^AI Deep Dive beta program, using it to mine millions of documents in their archive.

Leadership in Generative AI

For leaders in ediscovery that are using technology in innovative ways.

Winner: James Bekier, Director of Litigation Services, BakerHostetler

James’s role at Am Law 200 firm BakerHostetler means he’s responsible for the implementation of technology across the organization.

James Bekier (Center) accepts the award for Leadership in Generative AI.

James has also been proactively leveraging generative AI to fundamentally rethink workflows and create real-world results. His achievements to date include using generative AI for translating and summarizing foreign-language video evidence, identifying defamatory content for complaints, and integrating Storybuilder to streamline litigation narrative building.

By advocating for smart vendor partnerships and investing in technology, James is ensuring that BakerHostetler transitions to a modern, profitable litigation stack with AI at the forefront.

Impact Agent of the Year

For paralegals and litigation support professionals making measurable impacts in their organizations.

Winner: Eric Beard, Director of Litigation Support, Barnes & Thornburg

Over the last 4 years, Eric has fundamentally reshaped Barnes & Thornburg’s Ediscovery Services solution and increased ROI each year.

Eric Beard (Center) accepts the award for Impact Agent of the Year.

One of his biggest achievements has been working on reshaping the direction and services of the internal ediscovery team's support function at the firm. He transformed what was once a loosely structured capability into a recognized and revenue-generating business unit, complete with a small but organized team and an operational model that has been revised and rebuilt over time.

As a deeply engaged innovator within his firm, Eric has driven the adoption of scalable, tech-forward practices that empower attorneys and reduce client costs. He leads a high-performing five-person team that provides white glove service across the EDRM spectrum, and has successfully gotten buy-in from attorneys, including senior partners, to review documents directly in Everlaw.

Excellence in Legal Mentorship

For those demonstrating a commitment to developing, empowering, and mentoring the next generation of legal professionals.

Winner: Randy Abraham, Deloitte Contractor, Department of Justice/EOUSA

Randy has built a mentorship culture at the DOJ that’s grounded in on-demand self-service, empowerment, and excellence for thousands of federal legal professionals.

Randy Abraham (Center) accepts the award for Excellence in Legal Mentorship.

His most remarkable achievement this year has been his unwavering dedication to mentoring and supporting thousands of users through his customer’s Everlaw helpdesk, transforming it into a mentorship hub. His team handles a significant number of enablement and training requests daily, ensuring users receive not just answers, but contextual guidance and best-practice insights that foster professional growth. This level of support is vital in an environment handling high-stakes matters for dozens of litigation and investigative branch offices.

Beyond the helpdesk, Randy delivers at least one custom training session almost every day, leads multiple ad hoc coaching sessions monthly, and is the driving force behind his 10-part Everlaw webinar series, which draws hundreds of attendees per session. His commitment to knowledge-sharing and patient instruction—also serving as faculty at numerous onsite training events—has had a cascading impact, making him a significant reason why cloud ediscovery has been adopted so successfully by the U.S. federal government writ large.

Rising Star in Ediscovery

For professionals with seven years or less of legal experience whose early accomplishments distinguish them as future leaders in the profession.

Winner: Mared Jones, Operations and Project Manager, XBundle

Mared has demonstrated exceptional technical expertise and rapid career progression since joining XBundle in late 2020.

Mared Jones (Center) accepts the award for Rising Star in Ediscovery.

Her most significant achievement this year has been her pioneering work in championing the use of generative AI through a collaboration with London law firms like Macfarlanes. She devised a bespoke and entirely novel workflow to deploy Everlaw^AI Assistant on the Everlaw platform—a method so innovative it had not even been conceived by the Everlaw team itself. This deep technical knowledge and ability to innovate were validated when initial comparisons showed Everlaw, under her guidance, providing more useful and accurate outcomes than a competing AI model when tested on the same data.

Mared’s work for major clients like Macfarlanes has involved handling massive data sets (like the 4.5 million documents in Project Lignite), providing end to end workflow support for complex litigation (like Goyal v. BGF Investment Management), and leading urgent forensic data collections. Furthermore, she actively mentors the next generation through extensive training events for Macfarlanes trainees and co-spoke at the Future Lawyers conference on the use of AI in ediscovery, cementing her status as a true rising leader.

Everlaw for Good Award

For leaders in nonprofit and pro-bono legal services helping to level the playing field for justice by supporting low income populations, civil liberties, and human, civil, public, and environmental rights.

Winner: Legal Aid Society

The Legal Aid Society is the oldest and largest public interest law firm in New York City.

Evan Henley (Center) accepts the Everlaw for Good award on behalf of the Legal Aid Society of New York.

Founded in 1876, the Legal Aid Society is the oldest and largest public interest law firm in New York City, and has been supporting low-income New Yorkers in more than 300,000 legal matters for nearly 150 years. They’ve expanded their commitment to modern legal technology in recent years in an effort to support multiple databases across their civil and criminal practices.

A powerful example of their high-impact work is their collaboration with the Housing Rights Initiative on a sweeping multi-plaintiff housing discrimination lawsuit. Facing a significant ediscovery challenge involving thousands of documents and fast-moving court deadlines, the Legal Aid Society utilized Everlaw's modern ediscovery platform to secure settlements with nearly 50 defendants, ensuring long-term housing stability and increasing access to affordable housing for almost 100,000 New York City households. The settlements require companies to implement critical changes, such as reserving units for voucher holders, demonstrating the life-changing impact of their dedication to civil rights.

People’s Choice Award

For a standout Everlaw Summit presenter, selected on-site by Summit attendees.

Winner: Eric Kolbeck, Assistant Attorney General, Minnesota Attorney General's Office

Eric serves as the liaison between the legal and technology teams at the Minnesota Attorney General’s Office. He uses his specialized knowledge and experience to create technology-based solutions for complex problems. He helps develop case strategy related to the collection, review, and production of information. In the courtroom, he helps his colleagues communicate their theory of the case through exhibits and other visuals.

Eric Kolbeck (Right) accepts the People's Choice Award.

Eric and his team at the Minnesota Attorney General's Office have successfully leveraged legal technology to establish effective processes for some of the most critical cases of the past decade. While the work of litigation support teams within Attorney General's Offices is often unseen, their impact on the justice system is substantial and directly affects our citizenry on a daily basis.

Congratulations to all Everlaw Summit Award winners for their inspiring contributions to the industry! We’re thrilled to highlight and honor the achievements of individuals and organizations who are pioneering change and innovation in the legal and ediscovery space.

Director of Customer Marketing at Everlaw, Rachel and her team work directly with customers to help highlight and celebrate their success. See more articles from this author.

How a Leading Energy Company Shaved Weeks off Compliance Audits with Everlaw

2026-04-26T08:35:44Z

How a Leading Energy Company Shaved Weeks off Compliance Audits with Everlaw

by Petra Pasternak

Reading Time — 5 minutes

December 16, 2025

Business Outcomes

Without the right tools, this U.S. company would have had to spend weeks reviewing 300,000 documents manually or ship the set to outside counsel.
Using Everlaw to handle it internally, the small team culled the data set down to the most relevant 2,000 records for estimated savings of $140,000.

For years, the three-person compliance team at this major energy management firm moved mountains to prevent disputes from escalating into litigation. The reason for the prodigious effort was not the number of disagreements, but the sheer volume and complexity of the data involved in daily communications.

The U.S. company is a recognized leader in wholesale energy marketing and services for commercial and industrial clients across North America. Its operations generate thousands of chats and other information daily as traders and sales representatives interact with customers. As with any business, those communications don't always go smoothly.

The company’s Director of Compliance said that piecing together what may have led to customer pricing disagreements — often triggered by unexpected events like major weather-related outages — could take up weeks and pull him away from his other critical responsibilities. On the occasions when outside counsel were called in to assist with review, the fees quickly added up.

“Whenever there’s any kind of dispute with a customer, whether it's legal or not, it ends up on my desk,” the compliance director said. “I’m the one who needs to figure out what actually happened and what was said between parties.”

Our old process left giant holes in what might actually be out there. Now I can spend the same amount of time and actually look at records that matter.

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In the last couple of years, the company has tackled the compliance audit process from an operational perspective. Since adopting Everlaw, it has dramatically reduced the time and effort required to surface the facts that would help lead to resolution — from over a month to about a single work day in one recent matter. And this year, the team took it a step beyond compliance, leveraging Everlaw to also support litigation and bringing in a law firm only for targeted tasks.

Method	Total # Documents	Time to Review	Hours Saved	Est. Cost Savings
Manual	300,000	~ 6 weeks (240 hours)	N/A	N/A
Everlaw	300,000	~ 8 hours	232	$140,000

“It used to be a big effort requiring a lot of outside counsel and a lot of fees,” the compliance director said. “Since we’ve implemented Everlaw, we have found that we can manage almost everything internally.”

Why Outlook Was Never the Right Tool

Force majeure events are a major concern in the energy industry. When a supplier can’t deliver due to unforeseen disruptions, customers may face blackouts or production interruptions. These often trigger disputes. Was the customer properly notified? Was the cost explained? Customers may balk at the higher bill and refuse to pay.

The company's compliance director has played a critical role in resolving these issues before they escalate. He reviews all communications between customers and customer representatives to clarify what was agreed on. On a typical day, that means more than 100 messages exchanged by 100 traders using a secure, industry-specific chat platform, all coalated in an email file. Before Everlaw, when disputes came up, he’d have to sort through hundreds of thousands of these messages using Microsoft Outlook.

But Outlook, which wasn’t built for discovery, doesn’t support threaded views or large volumes of data. He had to split datasets into smaller files for processing. The special industry chat app complicated things further: users were identified on the platform only by internal numeric IDs, not names or companies. And the exported emails lacked “to” and “from” fields, making it nearly impossible to understand who said what.

He faced what is a common pain point for legal teams across industries: meeting compliance and litigation demands with a jury-rigged toolkit and exhausting manual labor.

“It was a nightmare,” he said. “I had to do high-level keyword searches, open messages one by one, and copy PDF data into folders for later review. It was incredibly time-consuming.”

Everlaw was just about the only software that could even remotely handle the chat information in a way that made sense. Most of the other systems absolutely choked on it.

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When “Good Enough” Was Suddenly “Not Enough”

In the past, legal and compliance teams were more likely to accept the delays caused by tools that were not designed for the work. But with today’s soaring volumes of digital data, the cost of that outdated approach is harder to ignore.

At the energy company, that realization hit home during a regulatory investigation involving a former employee. With urgent pressure to unearth relevant communications, the Director of Compliance had no choice but to manually chip away at nearly 200,000 documents. The effort took him the better part of two months. More pressingly, his other responsibilities came to a standstill. “None of my other work was getting done, which meant that filings were late and we incurred some fines,” he said.

The situation made clear that a better solution was needed — and leadership agreed to invest in new technology.

Everlaw felt like a true business tool with a wide range of applications — not just a narrow solution for discovery and production.

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Choosing Everlaw for Versatility and Ease

The company evaluated several platforms before selecting Everlaw. What they needed was a flexible, easy-to-use tool suited not just for corporate compliance and audit workflows, but also for traditional discovery.

The compliance director found that many other options were narrowly designed for litigation. In contrast, Everlaw offered the adaptability he was looking for — and crucially, it could handle the company’s chat data without breaking.

“Everlaw was just about the only software that could even remotely handle the chat information in a way that made sense,” he said. “Most of the other systems absolutely choked on it.”

Everlaw features that stood out included fast, powerful search, robust tagging and organization tools, intuitive visualizations, and a dedicated Early Case Assessment, or ECA, environment.

“Everlaw felt like a true business tool with a wide range of applications — not just a narrow solution for discovery and production,” he said.

Reducing Risk by Surfacing the Right Information

Everlaw has transformed the firm’s internal compliance audit process. Instead of relying on random manual samplings from massive data sets, the compliance director can now run targeted searches and trust that he’s pulling up the most relevant content.

“Customers will make claims about what they were told or what they knew. And it works both ways. We have found cases where they’re right. They were not informed properly of what was going to happen,” he said. “With Everlaw, it's very easy to go find those conversations so we're able to avoid the need for legal action.”

Before, he had no visibility. “Our old process left giant holes in what might actually be out there,” he said. “Now I can spend the same amount of time and actually look at records that matter.”

Dramatically Reducing Manual Effort to Cut Costs

The company's team is currently working on a matter that is headed for court — their first true legal discovery project. With Everlaw’s ECA features, they’ve been able to narrow a dataset of 300,000 emails, text messages, and documents down to just the 2,000 relevant records — all in less than eight hours.

Previously, that process would have taken more than a month of laborious manual review using unsuitable tools. With Everlaw, even follow-up inquiries related to the regulatory investigation, which once consumed weeks, now take “literally an hour, 30 minutes.”

“Since we started working in Everlaw, other things have come up where we have been able to just knock stuff out really fast,” the compliance director said.

Our outside counsel found Everlaw really easy to use. They commented on the flexibility and user friendliness of it.

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By handling large-scale review internally, the company’s data is more secure because it doesn’t have to be shipped out in bulk. The team also avoids the high external fees that come with outsourcing unnecessarily large data sets for review.

His team can invite outside counsel and other partners to collaborate directly within the platform in real time, with full visibility into the documents handled and the amount of time spent. The compliance director estimates that, assuming a $600/hour associate billing rate, cutting a six-week manual review (240 hours) down to just eight hours would save roughly $140,000 in legal service fees.

Their law firm also got up to speed relatively quickly. “Once our outside counsel got it, they found Everlaw really easy to use,” he said. “They commented on the flexibility and user friendliness of it.”

Making Investments That Pay Off

Not every company faces a lot of litigation. Still, as the story of this energy client illustrates, corporate compliance professionals can get overwhelmed, too. Without the right tools, the escalating volume of modern business communications can bury teams in manual review — with no clear path out.

For the compliance director, the impact of working with Everlaw was immediate. Whether auditing business communications or reviewing documents for litigation, his small in-house team can now navigate massive datasets — across even the most complex formats — with speed and confidence. Tasks that once took weeks or months now take hours — or even minutes. That kind of agility allows the company to resolve issues faster and avoid unnecessary legal action without derailing day-to-day responsibilities.

“Everlaw is a great tool,” the Director of Compliance said. “It’s been extremely useful for us, and it’s been a tremendous money and time saver.”

U.S. Energy Company + Everlaw

2026-04-26T08:35:44Z

U.S. Energy Company + Everlaw

Fortune 500 Construction Company + Everlaw

2026-04-26T08:35:44Z

Fortune 500 Construction Company + Everlaw

Construction Giant Saves 70% in a Single Matter With Everlaw

2026-04-26T08:35:44Z

Construction Giant Saves 70% in a Single Matter With Everlaw

by Petra Pasternak

Reading Time — 6 minutes

December 11, 2025

Business Outcomes

With a traditional approach, this global company would have outsourced 400,000 documents for outside counsel review, for a price tag of about $260,000.
Using Everlaw, its legal team dramatically culled the data set down, including the most critical 2,500 records for immediate review, for an estimated cost of just $75,000.

This Everlaw corporate customer is a Fortune 500 construction company specializing in high-stakes, multi-billion dollar infrastructure and commercial projects across various sectors.

As construction projects scale into the billions of dollars, the volume of data involved in legal claims has exploded. On top of that, the industry generates a wide range of complex and specialized data types – from mobile phone records and video files to CAD and design files.

The company's legal leadership prioritizes early dispute resolution as part of its legal strategy – something that is increasingly difficult in the modern data environment.

“If you have a delay and a disruption claim on a project, the other side’s asking for every record,” said the company’s Assistant General Counsel for Litigation. “It’s a lot of data to parse through.”

The quicker you can get your arms around your data, the faster you can get to a reliable data set that supports your assertion or defense of a claim.

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To resolve cases more quickly and efficiently, the in-house legal team has had to fundamentally re-evaluate its approach. Managing the company’s litigation and investigations across multiple legacy systems and disparate data bases while relying on outside counsel for full-service ediscovery was no longer sustainable.

“As is common with most major corporations, there’s been a big focus on our external spend and achieving more financially cost-effective resolutions,” the AGC said. “A very significant portion of our spend has been on ediscovery.”

Over the last few years, the company has brought the ediscovery process in-house and centralized litigation matters on Everlaw. Since the transition, her team has transformed its approach to litigation. The result: costs reduced year-over-year with more favorable resolutions in less time.

Taking Control In-House for More Cost-Effective Outcomes

Like many corporate legal departments, the construction company historically relied entirely on third-party vendors and outside counsel for ediscovery services.

The legal team handled data collections but outsourced everything else: data hosting and processing and management of the ediscovery database, review process, and productions. The setup meant less opportunity for strategic input and higher likelihood that costs would snowball.

“There were a lot of warning signals going up that we did not have a firm grasp on our ediscovery process and our data management,” the AGC said. “By not being in control of the platform, we realized that information critical for decision-making wasn’t always being surfaced for us. Functionality that would increase our efficiency and cost effectiveness was not made available to us.”

The move to Everlaw was driven by the desire to have full control and visibility into the company’s data and to own the work product in-house, while reducing overall litigation spend.

“This lets us form repeatable processes and learnings that we can carry from case to case with a consistent team to drive more consistent, more accurate, and more cost-effective results,” she said.

It’s a huge cost saving. And we achieved the result faster with much better quality in the work product.

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Finding the Story Faster for a Stronger Litigation Posture

Achieving efficiency in the in-house legal environment is about cost and speed. The more streamlined, easier and reliable the litigation process is, the faster the team is able to get to the facts that matter most.

“I say this is about finding your story faster,” the AGC said. “The quicker you can get your arms around your data, the faster you can get to a reliable data set that supports your assertion or defense of a claim.”

With Everlaw, the legal team has been able to move to a company-directed platform and develop streamlined review workflows. The primary goal is to help the internal team reduce data volume to the most relevant documents as early in a matter as possible. The bulk of the preparation now happens up front using powerful AI and data visualization features.

Results: Reducing Costs in a Single Matter by 70%

The new approach is yielding results that can be reported to the executive suite.

In one major case, the legal team was able to narrow 700,000 records down to about 400,000 documents by culling those that were potentially responsive but not relevant.

“We completed the initial review of those 400,000 records in about three weeks, which was very fast for a small team,” the AGC said.

By the time it came to the next phase – moving documents over to the internal claims team and outside counsel – her in-house team was able to share 200,000 records that potentially hit relevant topics. Most importantly, the handoff included the 2,500 records the in-house legal team identified as most critical for immediate review. That represented a massive reduction in the documents that would otherwise have gone to an outside partner.

	Legacy Approach	Modern Approach
Total # Documents	700,000	700,000
# Documents Outsourced for Review	400,000	200,000
Estimated Cost	$260,000	$75,000
Estimated Cost Reduction	NA	70% savings

The speed and precision with which the in-house team was able to zero in on the documents that mattered most shaved off substantial time and expense. The AGC estimated that it would have cost the company $260,000 to arrive at this point using its previous third-party controlled system, not including hosting costs. By contrast, the bill using the Everlaw approach stood at $75,000 – or about 70 percent less.

“It’s a huge cost saving,” the AGC said. “It’s about one fifth of the cost I estimated for this volume of data. And we achieved the result faster with much better quality in the work product.”

Whoever has the best story and the story that’s closest to the truth faster can generally drive a resolution that’s the most financially beneficial for them.

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Harnessing the Power of Repeatable Process

Bringing oversight of ediscovery in-house has other important benefits for corporate legal teams. One of the most important is the ability to reuse work product and establish consistent, repeatable processes that enhance efficiency and reduce costs across multiple matters.

“As a construction organization, we have a lot of very repeatable actions in our first-pass review,” the AGC said. “Owning the work product means not having to reinvent the wheel for every case. It means having the ability to templatize your workflow and automate some of your first-pass review to the greatest extent possible.”

These models are allowing us to learn those lessons in a building-block fashion, and it’s getting easier and easier to self-identify these data sets with less human interaction.

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Everlaw’s Multi-Matter Models allow the legal team to automate repeatable actions by reusing trained AI models across multiple cases for instant AI-powered document prioritization in new matters. The models learn and get better with every case.

“Every case is different, but there's always a common thread in what we're looking for,” she said. “These models are allowing us to learn those lessons in a building-block fashion, and it’s getting easier and easier to self-identify these data sets with less human interaction.”

Isolating the Most Important Data Faster than the Other Side

The company is also able to quickly cut through irrelevant material using Everlaw’s data visualization features and dashboards.

The Data Visualizer helps the team identify key themes and patterns in large document sets while the Communications Visualizer surfaces exchanges between key parties in interactive searchable graphs.

“The data visualization tool makes it easy to drill into a set that's much more reasonably likely to contain the information you’re interested in and when you layer on another tool to see who’s talking to whom about what – it’s fantastic,” the AGC said. “Moving from a conceptual relationship between documents to a visual relationship between documents is a really effective way to think about data.”

Streamlining Reviews with Internal and External Partners

Building greater efficiencies into the review process has also meant better leveraging internal talent and outside counsel. Instead of shipping all data to outside counsel at the onset, the work is done in phases, with involvement based on expertise.

The in-house teams play a bigger role in the early stages of discovery when decisions are being made about data that is related to a particular project. “Nobody knows our data better than our people,” the AGC said. “Our primary goal is to cull it down to the most relevant, potentially ripe set as quickly as possible, and we do that all in-house.”

Outside counsel come in during the next stage, to help review data that’s relevant to discrete issues. The company’s law firms then collaborate with the it operations team, taking on a greater role in developing strategies to drill down into the most relevant data sets.

The benefit to outside counsel is to give them more freedom and flexibility to develop our case faster because the bulk of this work is done up front.

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“The challenge is getting outside counsel to understand and recognize the benefit to them that the faster we can move, the more efficiently we can move to get to that core data set,” the AGC said. “The benefit only serves to give them more freedom and flexibility to develop our case faster and outside the fire of discovery deadlines because the bulk of this work is done up front.”

Discovering the Difference with Everlaw

The construction company is implementing a new approach to ediscovery. Its AGC is quick to point out that her team is driving stronger results thanks to a combination of factors: modern ediscovery technology managed internally, newly streamlined workflows with repeatable processes, and consistent internal and external talent.

With Everlaw, she has modernized the approach to litigation and investigations. The result is better control over work product and discovery spend. And when it comes to steering cases to resolution, increased visibility into the most relevant data arms the team with actionable insights to make the most meaningful decisions early on.

The bottom line depends on it, she said. “Whoever has the best story and the story that’s closest to the truth faster can generally drive a resolution that’s the most financially beneficial for them.”

The Evolution of Government Legal Technology

2026-04-26T08:35:44Z

The Evolution of Government Legal Technology

Why Now Is the Right Time for Cloud Migration

by Gina Jurva

Reading Time — 2 minutes

December 8, 2025

Public sector legal teams must be thoughtful stewards of taxpayer resources and sensitive data. For years, on-premises systems represented the gold standard for government IT—providing the control, oversight, and security that public accountability demands.

But the landscape has shifted dramatically. What once represented best practices may now be limiting the very outcomes these teams work so hard to achieve. Our new white paper, "Cloud Adoption in the Public Sector: Managing Ediscovery Transitions," explores how government legal teams can navigate this evolution while maintaining the security and accountability that public service demands.

Navigating New Realities

Government legal departments face a unique challenge: balancing cutting-edge efficiency with unwavering security and compliance requirements. Unlike private firms, public sector teams operate within complex frameworks of oversight, budget constraints, and risk management that require careful consideration of any technological change.

These constraints are much needed; they're important safeguards that protect public interests. But they also mean that when government teams do decide to evolve their technology, the transition requires specialized expertise and strategic planning.

Modern cloud platforms have matured to meet and exceed government security standards, often providing better protection than traditional on-premises systems. Certifications like FedRAMP and StateRAMP demonstrate that cloud providers now understand and address the specific requirements of public sector work.

The Hidden Costs of Standing Still

While government IT teams have been rightfully cautious about cloud adoption, the cost of maintaining legacy systems has quietly grown more substantial. Manual server provisioning delays urgent cases. Aging infrastructure consumes increasing portions of already-tight IT budgets. And the gap between what citizens experience in their personal digital lives and what government agencies can deliver continues to widen.

The need to make a change is increasingly urgent. And it's not driven by trends, but by the need to ensure that government legal teams have the tools required to serve their communities effectively.

Learning from Successful Transitions

We're now seeing government agencies successfully navigate cloud transitions while maintaining the security, compliance, and accountability that public service requires. These early adopters have revealed both the challenges and solutions that make cloud migration viable for public sector legal teams.

The most successful transitions share common characteristics: they prioritize security from day one, engage stakeholders throughout the process, and implement changes gradually to minimize risk. They also recognize that technology adoption in government requires different strategies than private sector approaches.

Why This Moment Matters

Several factors make this an opportune time for government cloud adoption:

Security standards have evolved: Cloud providers now offer government-specific certifications and security frameworks that often exceed what individual agencies can maintain internally.

Budget pressures are real: Maintaining aging on-premises systems requires increasing investment in hardware, software, and specialized IT support.

Citizen expectations are rising: Communities expect government services to be as efficient and accessible as other digital experiences.

Proven pathways exist: Other government agencies have successfully navigated these transitions, creating tested frameworks that new adopters can follow.

A Strategic Approach to Change

The agencies achieving the best outcomes treat cloud migration as an organizational evolution, not just a technology project. They invest in comprehensive planning, engage stakeholders throughout, and implement changes in phases that allow for learning and adjustment.

Most importantly, they recognize that successful technology adoption in government requires addressing both technical and human factors. The most sophisticated platform in the world won't improve outcomes if teams aren't prepared to use it effectively.

Building on Success

Our latest research into government cloud adoption reveals that agencies following strategic change management principles don't just implement new technology successfully—they build organizational capabilities that prepare them for future innovations while maintaining their commitment to public service.

The transition requires patience, strategic thinking, and recognition that sustainable change happens gradually. But the agencies making this investment are discovering that modern cloud platforms don't just process cases faster—they enable more thorough work, better collaboration, and ultimately more effective service to the communities they serve.

Interested in learning how other government legal teams can successfully navigate cloud adoption? Our new white paper "Cloud Adoption in the Public Sector: Managing Ediscovery Transitions" shares insights on how to make this transition while maintaining the security and accountability standards that public service demands.

Top Predictions and Trends for Legal Tech in 2026

2026-04-26T08:35:44Z

Top Predictions and Trends for Legal Tech in 2026

Opinions on the Year Ahead from Leaders in the Legal Industry

by Justin Smith

Reading Time — 4 minutes

December 9, 2025

The legal industry has undergone monumental changes in the past few years, with the introduction of generative AI marking a genuinely new era for the profession. The rapid adoption of this and other powerful technologies has swiftly moved the conversation from cautious consideration to strategic implementation.

Innovation will continue to unfold at a fast pace as these technologies find their footing and mature within the legal space. The groundwork has been laid for a future where legal professionals are positioned as drivers of change, and legal teams are aligning technology with broader business objectives. The industry is now positioned not just to adapt, but to redefine legal workflows and unlock unprecedented opportunities for innovation and efficiency.

Everlaw gathered the thoughts and opinions of leading voices in the law, including Everlaw employees and customers, to explore their outlook on where this momentum will take the legal industry in 2026.

Julie Brown: 2026 will be a breakthrough year for legal technology

The most significant trend to watch in 2026 is the rapid development of generative AI tools, which are set to transform legal work in ways we are only beginning to imagine. By this time next year, attorneys will be leveraging AI to perform tasks that today seem out of reach, leading to higher-quality work, substantial time savings, and more opportunities for lawyers to focus on strategy and client relationships.

As AI takes over much of the traditional manual work, law firms will need to rethink how they train and develop new attorneys. Innovative solutions—such as AI-powered mentorship and simulated case exercises—will help junior lawyers gain valuable experience without relying on repetitive, tedious tasks. This shift will make the roles of young attorneys more rewarding, allowing them to concentrate on higher-value work and increasing their job satisfaction.

The impact of AI will be felt across all practice areas. Firms that embrace these new tools will gain a clear competitive edge, while those who resist risk falling behind. Perhaps most exciting is the potential to improve how litigation is practiced in the United States. AI will streamline discovery processes, reduce costs for clients, and lead to fairer, faster resolutions.

Julie Brown, Director of Practice Technology, Vorys

Julie Brown (second from left) speaks on a panel during Everlaw Summit '25.

Gloria Lee: Corporate legal teams will establish concrete expectations for how firms use AI

In-house legal departments spent the last two years figuring out their own generative AI policies. That window will close in 2026, and corporate legal teams will establish concrete expectations for how firms use AI and report on its impact.

This shift matters because 60% of in-house teams currently don’t know if their firms are using generative AI on their matters. Transparency, then, becomes a requirement, not a courtesy; law firms that share how they use AI to drive efficiency will deepen client relationships, while those who don’t will face increasing pressure.

Gloria Lee, Chief Legal Officer, Everlaw

Gloria Lee (left) moderates the judges panel during Everlaw Summit '25.

Mark Abramowitz: 2026 will be the year AI discovery truly evolves on both sides of the “V”

We will start seeing parties move beyond pilot projects into full-fledged AI-augmented discovery strategies. As data volumes continue to surge—driven by an explosion of data-collecting devices and increasingly complex enterprise systems—litigants will be forced to rethink what “reasonable” preservation, collection, review, and production will look like in this new era. I expect to see new case law that will explore the contours of proportionality, defensibility, and transparency, with judges and litigants alike asking harder questions about training data, validation, and bias.

The net effect won’t just be faster document review; it will be a re-architecture of discovery itself to cope with an explosion of collected—and ultimately produced—data, turning AI from a cost-containment tool into a core litigation competency.

Mark Abramowitz, Partner and Chair of Ediscovery/ESI Practice Group, DiCello Levitt LLP

Mark Abramowitz (left) speaks during Everlaw Summit '25.

Chuck Kellner: AI’s potential for dispute resolution will grow

More corporations will experiment with AI for resolving their disputes in 2026. Solutions will range from the American Arbitration Association's AI Arbitrator, to true case assessment using generative AI in ediscovery tools, to leveraging AI for assistance with production reviews and analysis of testimony.

We will reach a tipping point by late 2026 in which AI for use in dispute resolution is normal. Lawyers and courts will accommodate with appropriate language for quality and completeness in ESI protocols and discovery orders.

Chuck Kellner, Senior Strategic Discovery Advisor, Everlaw

Chuck Kellner (right) speaks during Everlaw Summit '25.

Joanne Sprague: AI experiments in the access to justice space will start to pay off

2026 will be the year that AI innovation by the underdogs really shines and starts to show a quantitative impact. We’ve already seen legal aid professionals adopting AI at twice the rate of the broader legal industry, mirroring rapid adoption trends in the broader nonprofit sector. New, fit-for-purpose AI solutions have popped up every few months in 2025, addressing needs from voice-assisted legal information to resolving small claims disputes.

In this next year, we will start to see the fruits of those experiments – more people getting legal help affordably, more innovators learning from the first movers to build better and more localized solutions for the biggest legal needs they see, and public interest legal teams being able to help more clients and spend more time on the uniquely human parts of their jobs.

Joanne Sprague, Senior Director, Everlaw for Good

Joanne Sprague (far right) participates in a recording of the LawNext podcast during Everlaw Summit '24.

Doug Austin: AI-generated content will become the newest mainstream form of modern data that ediscovery professionals must address

In 2026, AI-generated content will become the newest mainstream form of modern data that ediscovery professionals must address. We’re already seeing a rapidly growing share of enterprise content that is being created or assisted by generative AI tools like ChatGPT and other LLM–based chatbots, with billions of prompts being submitted worldwide each month. A significant portion of that activity is “shadow AI” where employees are using public AI tools without official approval from their IT teams, creating additional challenges for ediscovery professionals looking to identify data sources for discovery.

At the same time, Microsoft is deeply embedding Copilot into Microsoft 365, Teams, and other productivity tools, where it routinely generates a variety of AI-authored artifacts that may be relevant data in litigation or investigations. Additionally, AI note takers and meeting assistants are generating content as an automatic byproduct of collaboration. Tools that join Zoom, Teams, and other calls as virtual participants are now recording, transcribing, summarizing, and tagging meetings by default, preserving everything from high-level summaries to action-item lists and sentiment-style insights.

All these examples illustrate how the content generated by various AI-related activities must be considered by ediscovery professionals at the outset of each case, and we will see more cases in 2026 where these various forms of AI-generated content will be important evidence in litigation and investigations.

Doug Austin, Editor, eDiscovery Today

Doug Austin is the editor of eDiscovery Today.

Cloud Adoption in the Public Sector: Managing Ediscovery Transitions

2026-04-26T08:35:44Z

White Paper

Cloud Adoption in the Public Sector: Managing Ediscovery Transitions

Navigate the transition to the cloud while maintaining the security and accountability that public service demands.

Download your free copy today for an overview of the critical areas public sector teams must consider--and practical strategies for addressing each.

G2 Ranks Everlaw as #1 in Winter 2026 Report

2026-04-26T08:35:44Z

Report

G2 Ranks Everlaw as #1 in Winter 2026 Report

See why legal professionals like you rank Everlaw above the rest

G2’s quarterly ediscovery report analyzes over 100 ediscovery software and service providers, with rankings based on thousands of genuine, verified reviews from legal professionals like you.

In the report, you’ll find:

Key trends in ediscovery software, so your organization can stay ahead of the curve
User reviews and ratings directly from your peers, so you can make the most informed technology decisions
Head to head comparisons, so you can see how your options stack up.

Mastering Ediscovery: Your Guide to Rules, Workflows, and Advanced Tools

2026-04-26T08:35:44Z

Report

Mastering Ediscovery: Your Guide to Rules, Workflows, and Advanced Tools

View the guide here: https://www.everlaw.com/guides/the-everlaw-guide-to-ediscovery/

The Future of Legal Discovery: Everlaw<sup>AI</sup> Deep Dive Released for General Availability

2026-04-26T08:35:44Z

The Future of Legal Discovery: Everlaw^AI Deep Dive Released for General Availability

by Justin Smith

Reading Time — 4 minutes

December 3, 2025

Getting ahead in a case often comes down to who understands the evidence first.

Time-intensive processes like uncovering critical facts, identifying key players, and structuring a narrative requires sifting through millions of documents, a gargantuan task that thousands of legal professionals take up every day.

The side that can quickly understand their data could gain a strategic advantage over opposing counsel.

With the release of Everlaw^AI Deep Dive for general availability, that strategic advantage is now available to everyone.

Deep Dive is a generative AI tool that allows legal teams to ask natural language questions of their entire data corpus. With responses to questions grounded in the four corners of your data set, Deep Dive reduces the risk of hallucinations and cites the sources where it got its responses for easy verification.

Deep Dive has been used by everyone from partners to paralegals to gain a better understanding of their case and interact with their data in a way they’ve never been able to before.

What Is Deep Dive?

Everlaw^AI Deep Dive is a cutting-edge generative AI feature that enables legal teams to ask questions of their litigation data using plain, conversational language. This low barrier to entry makes the tool more accessible to users without extensive prompt engineering experience.

Leveraging a secure Retrieval Augmented Generation (RAG) framework, Deep Dive compiles accurate, strategic findings and insights drawn strictly from the evidence contained in your Everlaw repository. Its purpose is to accelerate your grasp of the case facts by rapidly converting raw data into practical evidence.

Deep Dive allows legal teams to leverage generative AI to ask natural language questions of their entire data corpus.

To ensure maximum reliability, all results are linked to direct citations to the original source materials. If the answer to your query can’t be found within the uploaded documents, Deep Dive will simply respond that it can’t answer. This means that there’s a reduced risk of hallucinations, so you can trust in the results.

Deep Dive Use Cases

Deep Dive is a versatile tool that can easily be leveraged at practically any point in the case life cycle.

Early Matter Exploration

Deep Dive is best at finding the obscure or hidden evidence that can help unlock your case. By asking simple, natural language questions, you can quickly understand your matter and the key characters at play.

For example, at the outset of a complex commercial case, you could ask Deep Dive a question like “Who are the key personnel involved in the acquisition of Company A?”, and receive a response rooted in your document corpus, identifying all the relevant people so you can know who to look out for as you move through the case.

“We have not had a tool like this before,” Benjamin Kennedy, Managing Director of Adio, said. “Deep Dive helps find needles in haystacks. It allows Adio and lawyers to get across large document sets faster to get to the evidence and guide the discovery and investigative effort.”

Review and Investigations

Reviewing millions of documents is a time consuming process that often requires searching through massive amounts of irrelevant and extraneous information.

Deep Dive alleviates some of this pressure on review teams by drilling into specific events, communications, or entities to pinpoint roles and timelines.

For example, instead of running broad searches and reviewing thousands of immaterial results, a team could ask Deep Dive something like, "Which communications between the former lead engineer and external parties mention 'Project X' after the termination date?", and the tool will eliminate the extraneous noise by instantly drilling into specific events and entities, pinpointing the critical roles and timelines.

By identifying only the key documents relevant to that precise query, the review team can skip thousands of irrelevant data points and begin constructing the core legal argument much faster.

Deposition Preparation

When preparing for a deposition, time is often of the essence, and it’s crucially important to remain a step ahead of the other side.

For example, a legal team preparing for the crucial deposition of a key witness needs to ensure they have their facts together before a tight deadline. They can use Deep Dive to ask their entire document corpus for specific dates and statements related to a contract breach, instantly finding and verifying evidence that would take hours with traditional methods. This efficiency enables the team to rapidly create an accurate case timeline, organize the sequence of key events, and confirm or contradict witness statements before the deposition begins.

The tool also allows for live questioning during the deposition itself. You can challenge a statement on the spot and instantly retrieve cited evidence from millions of documents to uncover contradictions or confirm facts on the fly.

“Deep Dive stands heads and shoulders above other tools in doing the heavy lifting for attorneys," Elizabeth Koenig, Senior Vice President of Consulting Services at ILS, said. "The accessibility of the tool is even leading to senior partners wanting to ask the AI questions themselves, rather than relying on more junior attorneys to get the information for them."

Quality Control

Aside from pinpointing key facts and events, Deep Dive can also function as a quality control assistant.

Julie Brown, Director of Practice Technology at Vorys, detailed this use case onstage at Everlaw Summit ‘25, regarding a case that involved 2 million documents and a one-week production deadline. To ensure defensibility, the team used traditional search and Predictive Coding to move quickly through the data set to production.

“The answers were spot on,” Brown said. “The attorneys were just in awe of the results.”

By asking the tool about information they might have missed, attorneys can feel more confident in their case and ensure they’ve covered all their bases.

End-to-End Compatibility

Deep Dive incorporates seamlessly into your existing Everlaw workflows for a fully integrated experience.

You can leverage Deep Dive to quickly understand key facts, add them to Storybuilder for collaborative case analysis, and then use Writing Assistant to create a list of key characters and organize events.

By remaining within the Everlaw platform, you can save time and keep all your data organized and secure, so your team is all working from the same set of facts.

Insights from the Beta

Deep Dive was initially released through an eight month long beta program to a select group of users.

In the beta, users asked Deep Dive thousands of questions about their case data. The average database contained 166,000 documents, and the largest matter that was successfully tested used a database of 10 million documents. This proves that Deep Dive can work as a scalable solution for large matters, providing reliable insights across massive data sets.

Based on the feedback received from beta users, the Everlaw team has been able to deliver enhancements to the product that are already making a difference in the user experience.

“Our commitment is to ensure you have access to the best technology, no matter what it may be – AI or not, big or small – and that you’re fully trained and enabled by this tech,” Everlaw CEO AJ Shankar said.

A New Way to Understand Your Case

In the high-stakes environment of litigation and investigations, gaining a faster understanding of the data can determine the outcome of a case.

Deep Dive is the tool that delivers that decisive edge. Having proven its reliability throughout the beta program, it is now ready to instill confidence across your entire team—from the partners crafting strategy to the litigation support staff managing the data.

With the ability to interrogate millions of documents and trust the verifiable, cited answers, your only limit is the next question you need to ask.

If you're interesting in learning more about Deep Dive or Everlaw^AI, request a demo today!

Ferguson Case Orr Paterson Leverages Everlaw for Modern Litigation

2026-04-26T08:35:44Z

Ferguson Case Orr Paterson Leverages Everlaw for Modern Litigation

by Justin Smith

Reading Time — 4 minutes

November 19, 2025

In the ever-evolving landscape of legal technology, firms that embrace innovation not only survive, but thrive.

Ferguson Case Orr Paterson (FCOP), the largest full-service law firm in Ventura County, California, prides itself on being at the forefront of the technological evolution in the legal profession. With practice areas spanning business transactions and litigation, trusts and estates, intellectual property, personal injury, and more, their attorneys have to remain aware of the latest developments in order to best serve their clients.

Jessica Wan is a partner in the firm’s Business Litigation, Employment Litigation and Consulting, and Intellectual Property practice groups, where she has prosecuted numerous design and utility patents to issuance, and has regularly achieved success registering word mark and stylized/design trademarks in the U.S. and foreign countries.

“What makes FCOP unique is that it's a small town firm with a big firm feel, meaning we can handle cases of any size and complexity, but with a really fine touch because the attorneys and the staff are very humble and down to earth,” Wan said.

Wan has witnessed the transformation of electronically stored information (ESI) over the course of her career, from its time as a trending topic for CLE sessions to the necessary part of the litigation process it is today.

“It has been wonderful to see advances in legal technology to be able to collect data and information in a cost effective way, and it actually makes litigation more efficient and streamlined in my opinion,” Wan said.

From Skepticism to Success: Championing Everlaw at FCOP

When Wan began exploring ediscovery platforms, transparency was key.

She found Everlaw through a Google search, and was immediately impressed by the platform's straightforward pricing and the helpfulness of the customer success team.

“Everlaw’s transparency in both the platform and its pricing made sense for FCOP, and that's why we decided to choose them to handle our ediscovery.”

However, once Wan and her team selected Everlaw, the challenge quickly pivoted toward getting attorneys and litigation support up to speed in the platform. Through the help of the customer support team and Wan’s own initiatives, she was able to get the partners to start using Everlaw during the litigation preparation process.

“With the support of our customer success representative, we were able to spearhead a lot of training and user education, which increased adoption,” Wan said. “Another tactic I had was to simply start adding the new matters I was assigned to in Everlaw. Then I’d add the partners, which allowed me to show them what I was doing, and even show the paralegals how I was uploading documents, reviewing, tagging, and producing them.”

Once people in the firm had a basic understanding of the platform, Wan was able to start leading more advanced training for features like Storybuilder, and for common workflows like deposition preparation.

“I started showing them tips and tricks about Storybuilder, and from there helped them with depositions, uploading transcripts, and linking exhibits. That’s when I saw adoption really take off with a lot of the other litigation partners, and especially the assistants. They found it much easier to use than the old school way of using Adobe and folders and subfolders and things like that.”

Delivering Client Value and Embracing AI’s Potential

This ability to quickly get the whole firm up to speed has had a direct effect on FCOP’s productivity.

“Everlaw has definitely made me more productive and more effective as a litigation practitioner,” Wan said.

As data volumes grow and deadlines become more stringent, technology is more important than ever to an effective legal practice.

“An ediscovery platform like Everlaw makes an outsized impact in digesting and understanding massive amounts of data, even though deadlines are growing less flexible and judges are becoming less likely to give continuances in certain instances.”

With Everlaw’s generative AI features, Wan and her team are excited by the prospect of saving time and creating a better work product.

“I think the potential of Everlaw’s AI features is huge,” she said. “Especially for smaller teams like ours, it can be a major time saver. Attorneys can leverage AI to save time so they can then focus on more substantive issues and strategic planning, versus the grind of getting a mediation statement started, or discovery responses started, or even taking a first pass at document production.”

Wan sees AI significantly impacting those smaller workflows, allowing attorneys to pivot away from administrative work.

“When it comes to prepping for depositions, and digesting data, and assisting with outlines, and preparing exhibits, that's a huge pro and advantage that I think AI will play a role in,” Wan said.

Leveraging Efficiency for Pro Bono and Diversity

For Wan and the entire FCOP team, their pro bono practice is one they hold in high regard. The ability to take on legal work for under-resourced litigants, and to increase access to justice in their community, has been hugely impactful for the attorneys.

“Everlaw has been huge in freeing up time to take on pro bono cases,” Wan said. “And, because of how Everlaw does its pricing structure, firms are better able to absorb the costs of those cases.”

Wan is a passionate advocate for diversity initiatives, and sees technology as a critical tool for promoting justice and affordability.

“Technology helps bridge certain gaps,” Wan said. “For example, if you can use Zoom to call in from your home versus having to go to a courtroom three hours away, that increased accessibility is huge.”

By making litigation more affordable and accessible, Everlaw directly supports this mission. “The existence of Everlaw helps bridge the gap in the affordability of legal services,” Wan said.

Setting the Standard for Modern Practice

FCOP's journey with Everlaw is a blueprint for how mid-sized firms can strategically invest in technology to elevate their practice and better serve their clients.

By embracing the efficiency and cost-savings of the Everlaw platform, FCOP has become more effective and productive in handling its full caseload. This strategic partnership ensures that FCOP can litigate complex matters with the sophistication of a large firm, yet maintain the affordability and hands-on client care that defines its small-town character.

As the legal landscape continues to be reshaped by data proliferation and AI innovation, firms like FCOP are demonstrating that the future of litigation belongs to those who prioritize client outcomes, strategic efficiency, and a user-centric approach to legal technology.

Ferguson Case Orr Paterson + Everlaw

2026-04-26T08:35:44Z

Ferguson Case Orr Paterson + Everlaw

Why Metrics Matter More Than Ever: Proving Legal’s Value in the Age of GenAI

2026-04-26T08:35:44Z

Why Metrics Matter More Than Ever: Proving Legal’s Value in the Age of GenAI

by Petra Pasternak

Reading Time — 3 minutes

November 17, 2025

Corporate law departments have long been perceived as “cost centers,” but generative AI may be an opportunity to change that. A new industry report shows that the new technology – which is being adopted by legal professionals at a rapid pace – can help teams make a stronger case as true strategic partners to their organizations.

To make inroads, however, legal professionals will need to invest in measuring the right type of performance.

The report from Everlaw and the Association of Corporate Counsel, The Role of GenAI in Proving Corporate Law Department Value, highlights a fundamental gap in how teams measure and report their true business impact. Based on survey responses from 284 CLOs, GCs, and legal ops leaders, the report shows that most in-house legal teams track cost-based metrics, such as total outside counsel spend, but few capture the metrics that tie their value to outcomes. This puts them at a disadvantage when it comes to showing their contributions to what the C-suite cares most about: risk mitigation, business speed, and growth.

The report also reveals an urgency to act. Nearly all respondents believe GenAI can help them narrow this “metrics gap,” and nearly 7 in 10 plan to prioritize AI for value tracking in the next three to five years.

Leveraging GenAI to Prove Value

In-house legal leaders see GenAI as a tool to help them tell a better strategic story. Only 4% of respondents doubt the technology’s potential to help them better demonstrate their value to the business. Four in 10 say it will, while nearly 6 in 10 say it can.

Do you believe GenAI can help your legal team demonstrate its business value?

That confidence is grounded in benefits many are already seeing. Today, legal teams say the biggest payoff is speed: 81% expect GenAI to accelerate legal support and matter resolution.

A large majority (76%) also says that GenAI will reshape how their teams work, with a positive impact on internal efficiency and resourcing. In line with that belief, many are already using GenAI to simplify workflows, free up staff time, and handle routine work more effectively. The most common tasks legal departments expect to handle more cost effectively in-house with the help of GenAI include drafting, contract management, legal research — and also some aspects of M&A and litigation work.

The benefits extend to how legal teams manage outside counsel. Many say GenAI will help them identify cost-saving opportunities on outside counsel services (43%), improve analysis of law firm billing patterns (42%), and better forecast budgets (36%).

But to show their true business value, teams need to do more than work faster and control costs. The next evolution lies in the ability to track outcomes-focused metrics.

Overcoming the Metrics Gap

The report shows that many teams, particularly at smaller organizations, are still largely tracking cost-focused indicators. In part, that's in line with traditional C-suite expectations. The vast majority track foundational cost metrics like outside counsel spend (83%) and billing rates (54%). In litigation, 72% say they report on indicators like total matter spend.

These numbers support fiscal oversight — and satisfy corporate pressure to keep costs down — but they don’t paint a full picture about value.

What's missing: widespread adoption of the metrics that demonstrate true business value.

For example, only 12% track metrics to assess outside counsel performance, the same tiny percentage measures technology ROI, and just 9% track their impact on business outcomes.

When it comes to litigation matters, a significant source of risk and cost for many organizations, only 39% measure forecast vs. actual litigation spend and still fewer track outcomes relative to cost (16%).

Which litigation metrics does your department track?

Then there is the 18% of departments that say they don't track litigation metrics, and the 13% that aren’t tracking any metrics at all.

This reporting gap undermines in-house teams' ability to demonstrate strategic value. Even the most sophisticated GenAI tools can’t compensate for missing historical data or inconsistent performance tracking — two essentials for proving impact to the CEO.

Moving Beyond Cost Control to Delivering Business Value

The survey indicates a shift is underway. Legal teams are beginning to test more advanced applications for GenAI. New data-based use cases being explored include surfacing insights across large matters, projecting litigation outcomes, detecting fraud, and comparing performance across law firms.

Some teams are even using GenAI to develop new services for their internal clients, such as custom GPTs for procurement playbooks and AI companions for high-volume, low-impact matters. This is another facet of GenAI for value creation.

Early progress aside, real barriers still exist. Legal professionals cite tight budgets, concerns about data security, and the need for training as obstacles to adoption.

Despite all that, legal leaders are signaling urgency: nearly 70% say adopting GenAI for tracking and reporting will be a top priority within the next three to five years.

How important will GenAI adoption be for performance reporting in coming years?

Reimagining What It Means to Show Value

The findings point to a profession in transition, as legal departments work to redefine themselves as strategic contributors, not just cost centers.

With GenAI, in-house teams have a real opportunity to become data-driven advisers who influence business outcomes. Most believe the technology can help them demonstrate value — but only if they move beyond efficiency gains and embrace metrics tied to risk reduction, speed, and strategic insight.

Getting there won't be effortless. It will require strategic technology investment, strong data governance, and new skills in AI-driven analysis. These steps will help legal teams shift from experimenting with GenAI to reliably measuring performance and demonstrating impact across the business.

Closing the gap is now more achievable — and more urgent — than ever.

The Role of GenAI in Proving Corporate Law Department Value

2026-04-26T08:35:44Z

Report

The Role of GenAI in Proving Corporate Law Department Value

In this new report, 284 in-house legal professionals reveal how GenAI can help them prove their value as strategic partners to the business.

This new report reveals insights from 284 CLOs, GCs, and legal ops professionals why – and how – they expect generative AI to help them deliver better services faster and make a stronger case for their true value as strategic partners.

Top Takeaways from Everlaw Summit ‘25

2026-04-26T08:35:44Z

Top Takeaways from Everlaw Summit ‘25

Key Insights on Litigation, Generative AI, and the Future of Law

by Justin Smith

Reading Time — 6 minutes

November 11, 2025

The legal technology community traveled to San Francisco for Everlaw Summit '25 this past month for three days of education, connection, and inspiration with their peers.

Sessions offered candid looks into how legal teams are moving beyond pilot programs to integrate AI into their core workflows. Organizations are using AI to augment their legal expertise, with the human lawyer acting as the expert editor, quality controller, and strategic thinker.

The pervasive theme of Summit ‘25 was clear: AI is a force multiplier, not a replacement. Mastering AI is the key differentiator for legal success in the next decade, and those who attended left with a clear roadmap for advancing their career and their firm's capabilities in the age of intelligent discovery.

AI Redefines Existing Workflows

For his annual Summit keynote, Everlaw CEO AJ Shankar highlighted how generative AI is continuing to be integrated into the platform, and the impact it’s having on the work of customers.

“Everlaw integrates AI experiences into existing workflows,” AJ said. “By defining precise use cases, we can construct prompts for you, which means that using our AI is often as simple as clicking a button. We make it easy for you to validate the AI’s output, whether by providing Bates numbered citations or direct quotations from the source material.”

He also invited customers onstage to share their journey with Everlaw’s AI tools. Steve Delaney, who serves as Director of Litigation Support at Benesch, detailed how his team has used Everlaw^AI Assistant's Coding Suggestions to save time and resources on first-pass document review and other workflows. Julie Brown, Director of Practice Technology at Vorys, also joined AJ to discuss Everlaw^AI Deep Dive, which has been deployed at various points in the case lifecycle to help attorneys quickly get up to speed in their case by being able to engage with large data sets by asking natural language questions.

Ed Valio, who serves as Director of Ediscovery & Records Management at GEICO, was the third customer to join AJ onstage. Valio told AJ about an instance where his team had to evaluate tens of thousands of contracts in a short amount of time, with no appropriate solution to do the work.

Valio detailed how he and his team created a process in which they collected all the contracts they needed to search through, uploaded them to Everlaw, and used custom extractions to identify key parties and information that would be important to hit on in the search. They then used Review Assistant to evaluate the contracts that hit on the specified terms, and using that output created a Predictive Coding model to find those contracts. Valio and his team turned around the project in just 48 hours, finding just one single contract out of 50,000 that had characteristics they were looking for.

Ed Valio speaks during Everlaw Summit '25.

When asked by AJ what his advice was for teams that were looking to get started applying generative AI in different ways, Valio said to not keep yourself in a silo.

“The tools we as ediscovery professionals use every day aren’t just valuable for litigation and investigations,” he said. “They can also solve high-value business problems across an organization. When you have colleagues who are facing a problem that’s document-heavy, it’s an opportunity to help. 50,000 documents might feel overwhelming for some people, but it’s routine for us. We can help accelerate projects, reduce risk, and improve decision making. Look for moments where you can help and don’t be afraid to offer your expertise.”

Access to Justice Can Be Transformed Through AI

As an afternoon counterpart to AJ’s morning keynote, Casey Newton, founder of Platformer and co-host of The New York Times’ podcast Hard Fork and Nilay Patel, co-founder and editor-in-chief of The Verge, were joined by Bridget McCormack, president of the American Arbitration Association (AAA), and Rebecca Delfino, Associate Professor of Law at LMU Loyola Law to discuss generative AI’s role both in and out of the courtroom.

From left: Casey Newton, Nilay Patel, Rebecca Delfino, and Bridget McCormack

McCormack’s take on this was particularly noteworthy in that she spent nine years on the Michigan Supreme Court, including three as its chief justice. She’s used that experience in her current role with the AAA to leverage AI tools that help resolve disputes faster.

“The American civil justice system is broken,” she said. “92% of Americans can't afford legal help for their civil justice problems. Almost every small and medium business can't afford legal help for their civil justice problems. To me, generative AI is a potential scalable solution for that broken system.”

Professor Delfino agreed with this perspective, while also reiterating the need for guardrails, especially when it comes to attorneys using generative AI in the courtroom.

“I think the most important guardrail is using generative AI just as a tool, and not as a substitute for human evaluation,” she said. “It’s easy to see how beautiful the output is from these tools, and think that because it’s well written, it must be accurate. But you have to check your work just as you did before this technology existed, and ensure things are cited appropriately.”

Effective Communication Continues to Define Success

Day three’s keynote from Jad Abumrad, creator and former host of the podcast Radiolab, who led an interactive discussion on how to have better conversations.

Abumrad’s talk touched on the different situations he’s been in over the years as a journalist and podcaster, and what he’s learned that’s influenced his work today.

For example, when interviewing country music star Dolly Parton for his podcast Dolly Parton’s America, Abumrad recalled how, sitting across the table from her for their first interview, Parton talked so much he could hardly ask a question.

Jad Abumrad speaks during Everlaw Summit '25.

“For the first interview we did, we sat directly across from one another, and she steamrolled me,” Abumrad said. “I don't mean that in a bad way. I mean that she was so unbelievably charismatic, she told one story after the next, after the next, and I literally could not get a question in. The feeling I had at the time was that I needed more space.”

To achieve that space, Abumrad tried a different technique. In the next interviews with Parton, he positioned himself differently to see how it would affect the conversation.

“I would sit shoulder to shoulder with her so we could swivel toward one another, but then away from one another, and it made for a better conversation,” Abumrad said. “I really began to lean into this geometry because I also figured out that if I were to bring a third object for us to stare at, such as my laptop, which I used to show pictures from her past, it created these kinds of triangles. It made a huge difference not having a person right in front of her to perform to, but instead simply having an object. She went from a performer's brain to a much more reflective state of mind.”

These insights were particularly relevant to the legal professionals in the audience, who rely on communication and conversation to find breakthroughs in their case.

Judges Reiterate the Need for Human-Centered Technology

This mainstage session, moderated by Everlaw CLO Gloria Lee, featured five sitting judges speaking about pressing topics facing the legal profession, including generative AI, deepfakes, and more.

While each of the judges had varying degrees of experience with actually using generative AI or seeing it in their courtroom, they all agreed that it’s a tool to help legal professionals work smarter and provide better services to their clients. It’s there as a resource, but not a replacement. This was a point initially raised by Judge Joy Flowers Conti (W.D. Pa.) at the very beginning of the panel, and echoed throughout.

From left: Everlaw CLO Gloria Lee, Hon. Conti, Hon. Cunningham, Hon. Epps, Hon. Kim, and Hon. Kolakowski

“The lawyers I talk to say generative AI is a very useful tool,” Judge Conti said. “It can help you validate your work, and get you thinking in different ways, but it doesn't substitute for the lawyer's own work. The lawyer has to do the thinking, and the lawyer has to do the work.”

Judge David Cunningham (Los Angeles County Superior Court) agreed on the importance of keeping the human in the loop, and emphasized that generative AI as a tool to enhance the work of lawyers, not replace them.

“I don't think you can get rid of the human element no matter how effective generative AI can be,” Judge Cunningham said. “It's really a tool for organization, but I don't think it replaces the human component.”

The judges also broached the topic of deepfakes, which are becoming an increasing concern in the legal profession, raising questions over evidence authentication, equal access, and more.

Judge Victoria Kolakowski (Alameda County Superior Court) recently encountered this very issue in her own courtroom, with a pro se litigant submitting deepfake videos and photographs to the court.

“It raises a lot of questions about where the line is between what's a deepfake, and what's an enhancement, and what's an original video,” Judge Kolakowski said. “We tend to believe what our eyes show us, but how do we get past that? How can we address a world where we can't believe what we can't believe? There are all these kinds of questions that we're going to be facing over the next couple of years about what's real and what's not.”

Technology Adoption Remains a Hurdle for Legal Teams

Apart from the mainstage sessions, Summit ‘25 had plenty of breakout panels offering practical insights and thought-provoking discussions from a number of speakers, many of whom are Everlaw customers.

Sessions on topics like novel data types, de-weaponizing ediscovery in complex litigation, change management, generative AI, and more offered attendees a range of content and learning opportunities featuring strategic ideas they could take back to their teams.

Speaking on a panel highlighting how organizations can get internal buy-in and build trust with generative AI, Julie Brown, who serves as Director of Practice Technology at Vorys, touched on how showing attorneys where they can benefit from new technology often leads to better adoption.

Julie Brown (second from left) speaks on a panel during Everlaw Summit '25.

“The biggest stumbling block for technology adoption is typically desire,” Brown said. “You have to make sure your users have a desire to change how they do things, and you can show them what’s in it for them.”

A key focus of Summit ‘25 was empowering attendees to translate the concepts introduced during these sessions into actionable strategies within their own organizations.

Legal Professionals Appreciate Opportunities to Up-Level Skills

Another highlight of Summit is the education and certification opportunities that are offered to all attendees.

Single-day product certification is an experience exclusive to Everlaw Summit, offering users the chance to get certified in different areas of the Everlaw platform in just one day. Summit ‘25 offered live certification across four tracks, including Reviewer Certification, Data Operations Certification, Storybuilder Certification, and Everlaw AI Certification. These were incredibly popular, and 125 people were able to get certified at Summit.

Everlaw users participate in a product certification workshop during Everlaw Summit '25.

User education sessions were offered during all three days of Summit ‘25, at no extra cost to attendees. Session topics focused on practical workflows and building expertise in different Everlaw features, including Difference Viewer, Storybuilder, and more.

Join Us for Everlaw Summit ‘26

Even though Summit ‘25 just wrapped up, we’re already looking forward to Summit ‘26!

Check back soon for a save the date, and we’ll hope to see you next year in San Francisco!

Everlaw Summit '25 Keynote: Reimagining Workflows for Generative AI

2026-04-26T08:35:44Z

Everlaw Summit '25 Keynote: Reimagining Workflows for Generative AI

by Casey Sullivan

Reading Time — 9 minutes

November 6, 2025

AI is everywhere. From the sparkle in your emails to the video in your social media feed to the results of your Google search, AI can feel inescapable. In many cities, the San Francisco Bay Area especially, you can’t complete your commute without an AI inundation.

“I can understand there’s some fatigue,” Everlaw Founder and CEO AJ Shankar acknowledged as he kicked off his keynote address to more than 500 legal professionals at this year’s Everlaw Summit. But there is a good reason for the attention paid to AI. “The technology continues to advance apace, with new capabilities unlocked every year,” AJ explained. “It’s transforming the practice of law faster than any prior technology.”

So, yes, this keynote would be another AI keynote, AJ said. And for good reason: With testimonials from customers driving genuine impact with generative AI, the announcement of the forthcoming public release of Everlaw^AI Deep Dive, and updates to AI pricing to make usage seamless and costs predictable, AJ’s keynote showed how AI is already changing the shape of litigation today.

Of course, “We know that each of your AI journeys is different,” AJ elaborated. Everlaw’s goal, he promised, is to support you wherever you are on that journey. “The reason I talk so much about AI is not to shill it, or to coerce you to use it. It’s to educate you so you can make an informed decision about what’s best for you and your organization.”

“We spend time thinking deeply about how new technologies like GenAI are going to impact the core workflows and goals of litigation and investigations,” AJ said. “I hope we can inspire you to rethink your own workflows to incorporate AI tools where they make sense for your journey.”

Watch AJ’s full keynote below and read on for more highlights.

Integrating AI Throughout the Everlaw Experience

As GenAI continues to improve rapidly, it is already helping legal teams automate tasks like document translations, summaries and sentiment analysis, and even do first-pass review on thousands of documents in a single go.

For maximum impact, legal teams need to understand not only how AI works, but also how it fits into their litigation and investigations workflows.

As always, “Our commitment is to ensure you have access to the best technology, no matter what it may be – AI or not, big or small – and that you’re fully trained and enabled by this tech,” AJ shared. That is accomplished with a tool where all code is developed in-house, where every experience is built by a research and development team of nearly 200 people, and where “we’ve never offshored our engineering and we’ve never acquired another company,” AJ noted.

It’s a team that thinks deeply about how GenAI will affect both the goals of litigation and investigations and how that work gets done. “We’re not adding AI functionality opportunistically, to capture news cycles or do big fundraises,” AJ explained.

“I can confidently say that we’re adding new AI features because they work.”

That means AI-assisted experiences are increasingly embedded in day-to-day workflows.

GenAI is now integrated throughout Everlaw workflows, AJ Shankar emphasized.

“Eventually, ignoring AI is going to feel like ignoring search. It’ll be an essential technology,” AJ said to the packed ballroom of legal pros from law firms, corporations, and the public sector gathered at San Francisco’s Palace Hotel. “Our job is to ensure that you always have access to the best technology and that you’re fully trained and enabled.”

A Responsible Approach to AI Development

To deliver great functionality that you can trust requires a strong commitment to responsible development, AJ noted. That means always protecting your data, ensuring that all the data that goes to model providers is never used to train their models and is never retained after the query has been answered.

It means minimizing the risk of hallucinations by avoiding the built-in knowledge in LLMs, “a huge source of hallucinations in the legal field,” AJ explained, and instead focusing on “the four corners of your documents, providing the AI with ground truth at the time we ask it a question.”

It means a clean and logical integration into current workflows, with precise use cases developed through robust testing, and the necessary context to inform the LLM, “which means that using our AI is often as simple as clicking a button,” AJ said.

It means ensuring that validation is quick and easy. “We understand that any work product is ultimately yours to own,” AJ added. “So we make it easy for you to validate the AI’s output, whether by providing Bates-numbered citations or direct quotations from the source material.”

Finally, it means taking the time to do it right. “We are much more interested in being the best than being the first,” AJ pledged, explaining that “we typically beta test our AI features, gathering thousands of items of feedback over many months, and iterating on the experience before putting them in the wild.” The “balance of prudence and pragmatism” is designed to give users the best AI functionality, and the confidence that these tools can be relied upon.

Everlaw's development approach balances prudence with pragmatism, so you have access to the best AI tools and the confidence to use them well.

To show how legal teams are doing just that, AJ invited representatives from three Everlaw customers – Benesch, GEICO, and Vorys – onto the stage to share how they reimagine their workflows through the combination of GenAI-powered tools and core Everlaw features.

Benesch: Collaborating on Coding Suggestions in Storybuilder

Everlaw^AI Assistant’s Coding Suggestions, which uses the reasoning capabilities of large language models to expedite the review determinations process, helps surface relevant documents based on prior review decisions. The GenAI feature has shown it can perform at accuracy levels that match or exceed those of human reviewers, significantly speeding up the manual review process.

Legal teams at Am Law 200 firm Benesch have used Coding Suggestions for first-pass document review, to understand productions from opposing counsel, and for privilege review, said the firm’s Director of Litigation Support Steven Delaney. To date, Coding Suggestions has performed with more consistency and at a higher speed than first-level human reviewers, he said.

The key to success is working closely with the attorneys who know the case and can refine the prompts that Coding Suggestions needs to pinpoint the correct information.

The case teams “need to help define Coding Suggestion prompts for each issue,” Delaney explained. But “the great news is that they just need to review five to 10 documents per issue.” That iterative process, focused on a smaller number of documents, “helps you to refine much more quickly,” Delaney said.

The Benesch litigation support team collaborates with attorneys in Storybuilder Drafts on the issues and prompt revisions, and to document how prompt choices were made, along with the results they yielded – all with version control.

“This is the key time to be taking advantage of this. Right now, you can get ahead of the opposing side by using this technology at this time.”- Steven Delaney, Benesch

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“We love that we can have different attorneys working on different prompts concurrently in Storybuilder,” Delaney said. “It is great to have it all in one place for the team.”

Delaney ended with a reminder for the audience: “This is the key time to be taking advantage of this. Not everyone is using it right now.”

“If you want to get a competitive advantage, you don’t get a competitive advantage by doing what everyone else is doing. The best you can get then is parity,” Delaney explained.

“Right now, you can actually get ahead of the opposing side by using this technology at this time.”

Benesch's iterative workflow for developing and refining Coding Suggestions prompts.

GEICO: Combining GenAI and Traditional AI

Ed Valio, Director, Ediscovery and Records Management at leading insurer GEICO, joined AJ on stage to talk about a unique, non-litigation use case for Everlaw that his team devised to assist the organization’s contracts group.

To find an answer to an “unusual question,” they needed to evaluate tens of thousands of contracts on a very short timeline. “Having the full end-to-end workflow in Everlaw, with AI in the right places at the right time, is really what made this process so simple to execute and allowed us to move so quickly,” Valio explained.

After uploading all 50,000 contracts into Everlaw, Valio began by leveraging custom extractions, an Everlaw^AI feature that allows you to quickly, and in bulk, pull relevant information such as contract signatories or notice periods, from your document set. Valio paired that information with high-value search terms to first identify relevant information, then used Coding Suggestions to evaluate potential relevance.

"Don’t keep yourself in a silo. The more we apply these capabilities outside of ediscovery, the more strategic and indispensable we can become.” - Ed Valio, GEICO

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The team used that output to seed a Predictive Coding model to score the full contract set to help find any contracts that might also fit the profile they were looking for, but didn’t contain the high-value search terms.

These highly scored documents and the sample set were delivered to colleagues on the contracts team.

Valio’s team was able to turn around the entire project in 48 hours and provide a definitive answer to the business.

It turned out that just one document out of the 50,000 contracts had the exact characteristics they were looking for. “That allowed us to understand the situation very quickly and clearly across that whole set,” Valio said.

Valio closed by emphasizing the strategic value of these new workflows across functions. “Don’t keep yourself in a silo. The tools and the skills that we as ‘ediscovery people’ use every day aren’t just valuable for litigation and investigations, they can solve high-value business problems across an organization,” Valio explained. “The more we apply these capabilities outside of ediscovery, the more strategic and indispensable we can become.”

GEICO's workflow for combining Everlaw AI Assistant and Predictive Coding for rapid document identification and review.

Vorys: Using Deep Dive Across the Litigation Lifecycle

Everlaw^AI Deep Dive received enthusiastic endorsements from customers in the open beta program. The tool lets case teams, including partners and other senior attorneys, engage with large data sets directly by asking questions, just as they would with a colleague, to quickly surface verifiable insights.

AJ welcomed Julie K. Brown, Director of Practice Technology at Vorys, on stage to share her experience. Brown, who leads a highly skilled legal technologist team at the Am Law 200 firm, said Deep Dive wowed the attorneys during the beta pilot. After a successful initial test, the firm has used Deep Dive at various points in a case lifecycle, including for investigations, quality control, and deposition and trial prep.

Early on in one investigation, the Vorys team applied Deep Dive to figure out who the key individuals were with knowledge about a non-compete agreement and received a detailed list of not only the people, but also explanations of how they relate to it.

Vorys also used Deep Dive for quality control in a case involving 2 million documents and a one-week production deadline. To ensure defensibility, the team used traditional search and Predictive Coding to move quickly through the data set to production. Deep Dive was an effective validation tool, she said, letting attorneys ask about information they may have missed.

“The attorneys were just in awe when they saw the results.” - Julie Brown, Vorys

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For depositions and trial prep, the team was able to use Deep Dive to identify key documents and any potential gaps by asking, for example, what a deponent knew about a topic, if there were discrepancies between documents, and who else may have known about the topic.

Demonstrating the value of Deep Dive was easy. In their initial test of Deep Dive, Brown explained, “The attorneys were just in awe when they saw the results.”

“The answers were spot on,” Brown said. “Based on just that one test, the word spread. If attorneys like something, they’re going to go tell all their friends. Ever since that, we haven’t had a challenge getting additional cases [into Deep Dive]. In fact, most of the time attorneys are coming to us saying, ‘Can you add my case to Deep Dive?’”

Now, when she introduces Deep Dive to new teams, she begins with a simple question: “Are you ready to see some magic?”

Deep Dive is scheduled to be made available to the broad public in December 2025.

Getting More Value from Everlaw^AI

To make sure that all users can take advantage of AI tools in their workflows, AJ also announced key pricing changes designed to make Everlaw^AI more accessible than ever before.

“I’m happy to announce that we are now including Writing Assistant and single-document Review Assistant tasks with your core Everlaw subscription,” he said. “No, we are not forcing you to pay more for a new ‘standard’ GB rate,” AJ added. “Our rates are staying the same.”

With AI included, your reviewers can now summarize a long, complex document, make better coding determinations for individual docs, and complete topic analysis and extractions. Case teams can add documents to Storybuilder, have them automatically summarized or incorporated into a memo, an outline, a table of key facts, and more.

“The bottom line is that we think there is powerful functionality here in Storybuilder and Writing Assistant,” AJ concluded. “We want you to try it, and if it delivers, to start using it in every case. At no extra charge.”

AJ also announced that Coding Suggestions, Everlaw’s most popular batch action, will be reduced in price by more than 40% starting in October.

AJ Shankar announced that Coding Suggestions are now 40% less expensive.

Purchasing AI will now be easier than before, AJ explained, with Staging Drive, ECA, active, suspend, and AI credits to use for batch translations, batch Coding Suggestions, or Deep Dive soon available in a single, unified contract.

“This isn’t a one-time promotion – it is real and permanent,” AJ said. “The change is consistent with our belief that, as your best technology partner, our job is to enable you to use the best cutting-edge technology out there.”

More New Tools – And the Future of Legal Workflows

Everlaw will also soon add two brand-new features to the Everlaw^AI toolbox: the Depositions Q&A tool and the Privilege Descriptions tool. With these tools, users can interrogate their deposition documents for comprehensive insights – or subtle inconsistencies – with synthesized answers citing back to source testimony for easy verification.

Meanwhile, Privilege Descriptions will take some of the pain out of creating extensive privilege logs and similar documentation, with AI-generated, grounded explanations of why a document is marked privileged.

With generative AI tools now woven throughout the Everlaw experience, “We think that soon enough,” AJ elaborated,” using these tools is going to be second nature to you. Your workflows will incorporate them, and they’ll improve the quality and speed of your work.”

Making sure those workflows are effective, repeatable, and defensible is essential, AJ said. “In some industries, it doesn’t matter how you get a result. But not our industry. You have obligations to your clients, to an opposing party, to the court. We need to ensure that when you do work, it stands up to inspection.”

That’s especially true, AJ continued, “in a future when AI agents are running rampant.”

“We think AI has a very important role to play in the future of ediscovery,” AJ acknowledged, “but it needs to be harnessed, and orchestrated, by humans.”

Meanwhile, in the present, many complex workflows are managed in spreadsheets or ad hoc.

“What if we could address both problems with one solution?”

That’s the impetus behind Everlaw Workflows, which will allow users to create and execute customized workflows. “With this tool,” AJ explained, “you can construct complex workflows and have your documents automatically flow through them, with reporting on each step.”

The steps of the workflow can be anything in Everlaw, from first-pass review to running search term reports to applying batch AI actions and more. You can add in AI where it makes sense, leveraging Coding Suggestions, automatic translations, custom extractions, and more.

An early illustration of Everlaw Workflows.

Users will also be able to trigger workflows automatically, such as when new documents are added to a matter, and manually, adding in sampled quality control, conditional branching, and gating to ensure security and reliability.

“Imagine this future,” AJ posited. “Instead of getting in the guts of Everlaw, you’re orchestrating outcomes. Your colleagues can step in at exactly the right time to add value in a defensible, repeatable way. You can use AI to solve problems when the budget requires it or the client or stakeholder allows it. You can see exactly where each of your documents is at any time: which are moving along, which are stuck, which will require additional resources to hit your deadlines.”

“Much like I demonstrated Deep Dive on this stage last year,” AJ reminded the audience, “Everlaw Workflows are in their early stages. But success is built around partnership between us and you. If you would like to be a design partner on this, reach out to your customer success manager.”

And be sure to return for Everlaw Summit ‘26.

If you’re interested in learning more about generative AI, or want to see how Everlaw^AI Assistant can improve your workflows, request a demo today.

Embracing Ethical Change: Justice Tanya R. Kennedy on Generative AI and the Future of Fair Justice

2026-04-26T08:35:44Z

Embracing Ethical Change: Justice Tanya R. Kennedy on Generative AI and the Future of Fair Justice

by Justin Smith

Reading Time — 11 minutes

October 16, 2025

In the legal profession, where careers are often built on precedent and procedure, Justice Tanya R. Kennedy has forged a path all her own.

With a career spent entirely in the public sector and in the service of the law, she comes to the bench with a perspective gained through decades spent in its institutions.

And now, with generative AI already transforming the legal profession, Justice Kennedy is grappling with the pressing questions facing the legal community today.

How can we ensure a fair process for every litigant, from corporate clients to self-represented individuals? As technology reshapes our workflows, how do we safeguard the essential human judgment that defines the practice of law?

Justice Kennedy sat down with Everlaw to discuss these issues and more, including why she believes generative AI is here to stay.

Justice Tanya R. Kennedy (A.D. 1st)

I was hoping we could start with you telling me a little bit about your legal career and how you ended up on the bench?

My entire career has been in the public sector.

I began my legal career at the New York City Law Department, Office of the Corporation Counsel, where I handled juvenile delinquency cases. From there, I transferred to the Family Court Division of the New York City Law Department, where I represented the City of New York in various personal injury actions. And after that, I was a Principal Law Clerk for Justice Barry A. Cozier (Ret.) in the Commercial Division of the Supreme Court, New York County, where I handled complex commercial cases. I continued serving in that capacity when Justice Cozier was elevated to the Appellate Division, Second Department.

I have been fortunate that various individuals recognized my potential and provided me with opportunities to showcase my talents and gifts. I remained open-minded and flexible to other opportunities when they arose.

And what I mean by that is, for example, when I went to work at the Family Court Division of the Corporation Counsel. Initially, I had hoped to be placed in another division, but I wasn't going to turn down the offer when it came. I kept an open mind, and that was one of the best decisions I ever made because I received a lot of responsibility very early on, being responsible for the prosecution of a case from its inception to disposition, handling large caseloads, being in the courtroom every day, interviewing civilian witnesses, and police officers.

And when it came to being a judge, that really wasn't in my purview because I didn't know any judges. I didn't know how to become a judge.

My former supervisor at Corporation Counsel, Betty Lawrence Lewis, told me that I would be a judge. And I laughed because I didn't see myself in that role.

Years later, another female judge approached me with the idea of becoming a judge, and I still wasn't ready. However, while working for Justice Cozier, I began to think more about it because I could start to see myself in that role.

That's why I tell this story time and again. I think it's so important that you speak into the lives of others because very often people see things in you that you don't see in yourself. This is why we must encourage and inspire one another.

You’ve presided over cases across multiple court divisions. How has your experience shaped your perspective on the legal system overall, as well as how discovery practices can impact case outcomes across different types of law?

It was a huge benefit to be involved in various courts across the legal system, first as an intern, then as an attorney, and finally as a judge.

Being in various courts provided me with a broad perspective on how the legal system works and how it's experienced through the lens of litigants. Each court really has its own character and culture.

"I know there's talk about jobs being replaced, and while I can't answer that, I do believe that new jobs will be created as a result of this technology. And those who fail to embrace it are going to be left behind."

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Let's take Civil Court, for example, which is referred to as the People's Court. Certainly, the perceptions of self-represented litigants in Civil Court may be much different from those of a corporate litigant in Supreme Court. It also depends on where the court is situated. I'm in New York City, and each borough has its own unique characteristics.

When you're talking about Criminal Court, or even Family Court, and you're looking at whether or not to set bail, or whether or not you're going to remand a respondent in a juvenile delinquency case, it’s hugely consequential.

I think that how you preside over a case and handle the discovery process not only influences the outcome but also affects how people perceive the fairness of the system.

But I'll also say this. I attended a recent event at my alma mater, Benjamin N. Cardozo School of Law, where Professor Michelle Adams discussed her recently authored book, entitled The Containment. During the conversation, Professor Adams spoke about what makes a good judge, which included having an open mind and considering all of the facts before rendering a decision.

And I chimed in and talked about the importance of having your finger on the pulse of the human condition. I've said this several times when speaking to different audiences, and it's important. Yes, you need legal knowledge, but you also need an overall understanding of what's going on in the world to relate to the situation, the litigants, and the circumstances.

What role do you see technology playing in the courts as it continues to evolve, and what sorts of opportunities and risks do you see for both courts and litigants in adopting tools?

My disclaimer is that everything I say represents the view of Tanya R. Kennedy, and I'm not representing my court or the New York State Unified Court System. However, I would like to emphasize that AI and generative AI are here to stay.

The bottom line is that it's so important for all of us to embrace it. Regarding the New York State court system, I believe they are in the process of drafting a statewide policy that will be released soon.

I'm excited that states across the country, including bar and judicial associations, are starting conversations about how state courts can begin using AI.

When I served as the presiding member of the New York State Bar Association Judicial Section, we hosted three webinars for judges and attorneys on generative AI. One of them actually featured a live demonstration on how you could use generative AI to draft jury charges.

I know lawyers are starting to use it. Firms are building their own platforms and investigating different use cases. But it's crucial that we judges and attorneys continue to learn and to be aware of our ethical obligations because the technology is so fast-paced and continually evolving.

I read an article a couple of weeks ago about the various law schools that are now implementing generative AI into their curriculum, as well as ediscovery. And I think that's really key because that’s where the legal profession is going.

I know there's talk about jobs being replaced, and while I can't answer that, I do believe that new jobs will be created as a result of this technology. And those who fail to embrace it are going to be left behind.

In terms of the education side of things and putting on webinars, do you feel like the court has a responsibility to put that sort of education out there, or do you think it should be a shared burden, so to speak, between the courts and the attorneys and bar associations?

I'm going to tweak your question and my answer a little bit because I believe that the bench and bar should always work together to advance the profession.

For example, I am aware that an upcoming symposium at Fordham Law School, sponsored by the Commercial Division Advisory Council of the New York State Unified Court System, will feature a panel discussion between the Honorable Katherine B. Forrest (Ret.) and Associate Professor Chinmayi Sharma on the topic of artificial intelligence. That is an example of the bench and bar working together. I think it's a shared responsibility. It's great that judges, attorneys, and law students will come together at Fordham Law, where those who are in the trenches with technology will share their knowledge.

"With generative AI, we often talk about efficiency and doing things faster and smarter, but you still have to verify. You have to get into this mindset that it's not the end-all or be-all. It's a tool."

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There are some judges, like Judge Xavier Rodriguez, who are in the trenches. He studies, and he speaks, and everyone learns from him. And I'm sure he also learns from the practitioners. I really see it as a give-and-take.

I have put myself out there to learn, and I'm still learning. That’s so key because there will come a time when my court will review these matters, and I can say, "Yes, I'm familiar with this.” Judges are not supposed to be skilled at everything, but just having a working knowledge is so important.

What are your thoughts on generative AI’s potential from a judges’ perspective, whether to support judicial decision-making, or at least streamline judicial workflows?

I have not used generative AI for appellate division work, but I've used it in everyday life.

I taught over the summer and used it for tasks such as creating class notes, devising catchy titles for my syllabus, and summarizing.

I'll tell you what my wish list is. I addressed this in 2023 when I was the keynote speaker at the Kiroff Bench Bar Conference, sponsored by the Toledo Bar Association. I talked about how I thought you could really use generative AI to make courts more efficient. I spoke about optimizing hearing schedules, checking attorney availability, utilizing courtrooms, prioritizing cases, indexing documents for easy retrieval in complex cases, and ensuring filings adhere to procedural requirements.

There’s even the potential of having chatbots on the court website to answer basic questions, such as procedural matters, which can free up clerical staff. It can certainly reduce their workload and resolve basic inquiries more easily.

Like I said, that’s my wish list. And the thing is, we already know that attorneys are using it for drafting complaints, contracts, and some of that busy work, allowing them to focus on more substantive tasks.

And yes, some state judges are using it. I think federal judges are more so because they have more resources compared to state courts.

I watched a webinar over the summer where Judge Scott Schlegel moderated a discussion between Judge Allison Goddard and Judge Xavier Rodriguez. Both judges shared how they use generative AI for drafting orders and summarizing testimony by utilizing their own work product and materials. I think the future is bright.

What we have to do is buy into it and embrace it. Judge Goddard said it's like “a thought partner.” It's like a first draft.

What ethical or procedural guardrails do you believe should be in place for the use of generative AI by litigants, attorneys, and judges?

The key is education.

In New York, we have the Rules of Professional Conduct, and I think that’s enough. I would never tell a judge what they can or cannot do because they have discretion.

I know there's been this tension between various judges, especially in federal court, where there's been a lot of discussion and pushback from attorneys about how some of these standing orders being released by judges are overbroad.

I believe following the ethical guidelines is enough. I think that’s more practical. It seems to me, reading the various commentary, that it often may appear that if the judge had a better understanding of the technology, perhaps the orders would not be worded in a certain way.

For example, does that mean when you're using Grammarly, you have to disclose such use to the judge? And prohibiting it totally doesn’t seem like the right solution either. I agree with the arguments that have been made about these kinds of bans stifling innovation and creativity.

"I've said a number of times that leadership is a mindset. It's value-driven. And so, when we're looking at generative AI and discussing topics like cost, closing the justice gap, transparency, and responsible use, all of these factors are interconnected."

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In 2023, I was on a panel on ethics and generative AI, and one of my fellow panelists, Dr. Shokouh H. Abadi, talked about how, in the context of the legal profession, generative AI improves mental wellness. That’s something I’ve now bought into because this profession is stressful enough. There are never enough hours in the day, and if we can ease the burden by having more time to do other things, that also improves wellness.

With generative AI, we often talk about efficiency and doing things faster and smarter, but you still have to verify. You have to get into this mindset that it's not the end-all or be-all. It's a tool.

I don't think it should be prohibited, but I do believe that if you're going to use a generative AI platform, you have to represent that you’ve verified its responses.

You’ve spoken often about the importance of equity in the legal system. How do you see generative AI helping to improve equity and access to justice?

I always believe that the glass is half full rather than empty. However, I think the legal profession is now becoming more sensitized to this justice gap.

I like that various companies and technologists are now willing to donate their time and services to public service organizations.

I believe there's a greater sensitivity, and people are going to lean in to work together to find out what we can do to bring the average Jane and Joe into the equation. It's not just about a lack of education and income; it's also about certain areas where underprivileged people don't have the necessary bandwidth.

I think that young people, even those who are young at heart, are really going to come together to figure out how we bring these people into the equation. Because that's really what it is. You need cheerleaders to speak to this, to say, “We need your help, how can we do this together?”

This is such an exciting time with innovation and creativity. I know it can be done.

And once again, it's about the partnership between the private and public sectors, and the community at large. You have to hold these entities accountable and ask for transparency. That’s where the focus has to be.

I also wanted to ask about the instance you had in your courtroom a few months back, where a self-represented litigant used an avatar created using generative AI to present their case. Can you describe how you interpreted that situation?

I know that moment went viral, appearing on TikTok and every platform you can imagine.

An individual claimed that, due to certain physical challenges, he was unable to communicate with the court and wanted an opportunity to make a video presentation. However, the presiding justice at oral argument noted that the litigant misled the court, as this individual previously appeared before the court to argue a case and had held a conversation with staff members in the clerk’s office for over thirty minutes. And if you look at that video, you can see that the litigant’s claim of his inability to communicate was inaccurate.

The presiding justice at oral argument also indicated that this individual would not use this avatar to promote his business. So that's not really an access to justice issue, right? That's being disingenuous because the avatar didn't even look like him. Remember, the self-represented litigant claimed he wanted to present his own video, right? That wasn't the case.

It’s one thing to say you’re a pro se litigant and want to present to the court, but it’s an entirely other thing to be disingenuous and to attempt to use that platform to promote a business.

This leads me to one more point I want to discuss regarding generative AI.

It's a tool, and it's not going to replace humans because it's about judgment. A machine can’t always pick up on things like creativity and nuances, which is an important point to make because, as we know, the law can be gray.

A machine is not going to fill in the gaps, but humans will.

Switching gears a bit, you’ve been a major advocate for a number of different causes throughout your career, serving as a mentor, board member to various organizations and nonprofits, and even founding your own speakers’ bureau targeting at-risk youth, as well as teaching a juvenile justice seminar for a decade at Fordham Law. How does this work influence your judicial practice?

Service is in my background.

I come from a single-parent household, and my mother and maternal grandmother always served, whether in the community, at their church, or elsewhere. That’s what I grew up with, and that's something I enjoy.

As it relates to young people, I remember when I was growing up, there were adults who poured their energy into me and mentored me. And I think it's important to give back.

I like the concept of reverse mentoring because now I have some former interns who I consider my mentors, and I’ve learned from them.

Those who are more senior and advanced in the profession must be humble and open-minded enough to recognize that younger professionals have much to offer, and we can learn from them. It's a give-and-take where we can both learn from each other.

As for speaking at events, I'm really just honored that people want to hear from me and that they feel I have something to impart. I enjoy sharing my thoughts and knowledge, but I also want to inspire, challenge the audience, and give them things to think about.

It's about learning, sharing, and connecting to a broader legal community. Leadership and mentorship are important, and it's important to get out of your silos and connect and share with others.

And lastly, thinking about the leadership and mentorship ideas you touched on, I was wondering if you have any advice for this next generation of judges and lawyers who are coming up with generative AI and all these new types of legal technology? Is there anything you think it’s particularly important for them to know?

It's all about ethical use.

Earlier, when I talked about having your finger on the pulse of the human condition, this all ties into the point about ethical use and transparency.

I've said a number of times that leadership is a mindset. It's value-driven. And so, when we're looking at generative AI and discussing topics like cost, closing the justice gap, transparency, and responsible use, all of these factors are interconnected.

It's like a hand. If you lose one finger, everything is thrown off. It's the same thing here. Judges, lawyers, technologists, law students, law professors, legal professionals, and the entire legal community, we’re all in this together, and we have to stay connected to advance the profession.

In-House Teams Turn to GenAI for Efficiency, Raising New Expectations for Law Firms

2026-04-26T08:35:44Z

In-House Teams Turn to GenAI for Efficiency, Raising New Expectations for Law Firms

New survey highlights in-house surge in adoption and outside counsel transparency gap

by Petra Pasternak

Reading Time — 3 minutes

October 14, 2025

As GenAI tools grow in sophistication, corporate legal departments are no longer debating whether to use them, but where they’ll deliver the greatest impact.

Findings from the latest survey by Everlaw and the ACC show that GenAI adoption among U.S. in-house teams has more than doubled in the last year. So has optimism about the technology as transformational for legal work.

Respondents report that GenAI helps them work faster, communicate more effectively, and deliver better client service. A growing share — one third this year, up from one quarter last year — are already seeing measurable cost savings.

As these efficiencies compound, the effects are rippling across practice areas and influencing how much work legal teams can manage internally and what they choose to outsource. Many in-house professionals now believe the next frontier lies in recalibrating how outside counsel deploy GenAI, and how legal services are ultimately priced.

These and other insights come from Generative AI’s Growing Strategic Value for Corporate Law Departments, a survey of 657 CLOs, GCs, and legal ops professionals from the U.S., Europe, Australia, and Asia.

Early Efficiencies, Savings Fueling GenAI Adoption

GenAI is fast becoming a strategic tool for in-house legal departments under pressure to do more with less. The technology’s low barrier to initial use, applicability across a broad range of legal tasks, and proof of early productivity gains makes it ideal for teams that are looking to keep pace with innovation at their organizations.

This year’s survey shows just how rapidly attitudes are shifting. GenAI adoption for legal work more than doubled among U.S. in-house teams to 52 percent, up from just 23 percent last year. The segment who have no plans to use GenAI has plummeted to just 2 percent.

Optimism about GenAI’s impact on legal work has also grown: Half of U.S. respondents now say the impact will be significant (50 percent – up from 45 percent a year ago) and 20 percent say it will be transformative, nearly doubling from 11 percent.

The doors to adoption are also swinging open with company-wide permissions to use GenAI. The number of respondents citing company bans dropped to just 9 percent this year, from nearly 30 percent a year ago.

Are you currently using, or planning to use, generative AI in your legal work?

Bringing More Types of Work In-House

GenAI is creating opportunities for legal teams to increase their self-sufficiency – and reduce costs – across a growing variety of matters. The survey reveals that nearly two-thirds of respondents (64 percent) expect to rely less on law firms thanks to GenAI.

Large majorities see the greatest opportunity to handle more drafting (78 percent), contracts (71 percent), and legal research (62 percent) internally. About a third of participants also see opportunity for greater ability to handle litigation and M&A matters internally (29 percent each).

Asked which areas of practice currently serviced by outside counsel they expect to see the biggest cost savings in the next three years, 82 percent say contract drafting and negotiation. Nearly half also see savings ahead in higher‑value, repeatable work — including regulatory/compliance and general counsel tasks, litigation, and M&A.

What type of legal work do you see the greatest opportunity to handle in-house with GenAI?

Overcoming the Disconnect with Law Firms and GenAI

The survey highlights a deep disconnect between clients and their outside counsel when it comes to GenAI. Most corporate legal teams still don’t have a clear view into how their law firms are using GenAI — or whether it’s lowering costs. Nearly six in 10 say they lack visibility into GenAI use on their matters, and the same share report seeing no savings passed on.

This may not be surprising, since four in five don’t require or even encourage law firms to use the technology. When the topic does come up, it’s usually informal and undocumented — not baked into outside counsel guidelines or RFPs. The result is missed opportunities for efficiency, transparency, and stronger partnerships.

Are any of your law firms currently using GenAI on legal matters for your organization?

Signaling a Readiness to Disrupt the Billable Hour

It’s no surprise that only about a quarter of respondents (24 percent) are satisfied with how outside counsel are using GenAI to deliver better value. While 63 percent say it’s too early for cost reductions to materialize, nearly 60 percent also note that law firms have not started to adjust their pricing models for AI efficiencies.

In-house leaders are prepared to change that status quo. A significant majority (61 percent) are ready to push for new delivery and pricing models, and nearly half (49 percent) believe client demand will be the primary driver. The future, many say, is about value-based billing and alternative fee arrangements.

Momentum is building against the billable hour. Firms that connect GenAI-enabled efficiency to fair, transparent pricing will differentiate themselves as modern, client-first partners.

How likely is your team to push for a change in how legal services are delivered and priced?

Building a More Strategic In-House Legal Department with GenAI

This year’s survey makes one thing clear: GenAI is becoming a catalyst for a more strategic in-house legal function. With new capabilities to automate routine work and accelerate insight, legal teams are poised to rebalance their mix of internal and external work while tightening control over cost and risk. The implications will extend well beyond efficiency — with potential to reshape pricing expectations, redefine value, and give legal leaders new power at the negotiation table.

Generative AI’s Growing Strategic Value for Corporate Law Departments

2026-04-26T08:35:44Z

Report

Generative AI’s Growing Strategic Value for Corporate Law Departments

This new report by Everlaw and the ACC reveals how 657 corporate in-house legal professionals view the business impacts of generative AI, including the implications for how legal work is outsourced and valued.

Tips for Writing Effective Legal Prompts

2026-04-26T08:35:44Z

Tips for Writing Effective Legal Prompts

by Zach Sousa

Reading Time — 3 minutes

October 7, 2025

Lawyers don’t need to become prompt engineers to get the most out of generative AI.

Crafting effective prompts requires skills lawyers have been honing all along: logic and reasoning, attention to detail, and clear communication. The beauty of GenAI tools like Everlaw^AI Assistant Coding Suggestions — which evaluates documents and suggests codes for them to speed up the review determinations process — is that instructing it is much like debriefing a human colleague.

Both require context, guidance, and clear expectations about the desired outcome. Lawyers need to learn how to write effective prompts because the effectiveness of these tools hinges on the quality of the instructions they receive.

In “Best Practices for AI Prompting,” an Everlaw community webinar, legal pros learned tips for how to instruct Coding Suggestions for the best results. The program covered using precise language to describe the context and the task, iterating on prompts to improve the results, and how to combine Coding Suggestions with Predictive Coding to make document review even more efficient.

While these best practices help legal professionals expedite document review, they are also broadly applicable to instructing any LLM for legal work.

[Ed. Note: Community roundtables, AMAs, and other events are exclusive to members of the Everlaw Ediscovery Community. To join, sign up here.]

Making Descriptions Clear, Detailed, and Nuanced

A well-structured GenAI prompt follows a formula. Generally, the formula involves a clear description of your goal or your intent: what type of answer are you seeking? It also requires clear context to provide the necessary background. The instruction itself has to be specific and detailed.

For example, when generating Coding Suggestions, Everlaw^AI Assistant uses three types of descriptions to set the stage:

The case description, which should include a high-level summary of the main issues, key entities and their roles, and any other important context.
The coding categories, which define any technical terms and acronyms and list alternative names for entities to capture more instances.
The coding descriptions, which should describe the specific criteria for applying a code, and define any ambiguous language or subjective terms.

The quality of the coding suggestions depends directly on these descriptions. Vague prompts lead to generic or inaccurate results, while specific, detailed prompts yield more precise and relevant outcomes.

Note: Verification of GenAI outputs by legal experts is still critical. To make validation straightforward, Coding Suggestions will provide a rationale for its suggestion and, whenever possible, provide links to relevant areas of the document – to make it easier for teams to verify the results.

Improving the First Draft Through Multiple Iterations

Prompting an LLM is an iterative process. A first draft from a single prompt should never be the final product. A legal professional who is familiar with a matter is in the best position to iterate on initial prompts for the best results.

When working with Coding Suggestions, begin by testing your prompts on a small sample of documents. Continue to improve the prompts before running the suggestions across an entire dataset. Errors are not a setback if corrected. Users should take note of them, update the descriptions, and rerun the suggestions on the original sample set of documents. This verification process ensures that the updated suggestions align with the manually applied codes and that there are no regressions.

Once Coding Suggestions is regularly returning results at a desired level of accuracy, they can be applied to larger document sets to expedite the rest of the review process.

Combining Predictive Coding and Coding Suggestions for Speed

For even greater efficiency, users can set up a predictive coding model to prioritize which documents to send to Coding Suggestions.

Based on supervised learning, Predictive Coding applies rules from reviewer decisions to predict document relevance across an entire case.

By running coding suggestions only on documents that your predictive coding model has identified as highly likely to be relevant, you can focus the LLM’s efforts where they are most needed and significantly accelerate your review.

Mastering Prompt Writing for the Law

Mastering prompts doesn’t mean lawyers need to earn a computer science degree. AI prompting calls for the same precision and strategic thinking that lawyers already bring to their work. The best results come when legal expertise shapes the questions, providing the context and nuance AI alone cannot.

Clear and precise prompts help direct Everlaw^AI Assistant to provide suggestions for documents at a rate that exceeds the speed and accuracy of first-level human reviewers. The better the prompt, the more accurate the resulting suggestions.

Nothing proves the argument better than trying it yourself: start small, run a test project, and put these prompting strategies into practice. The more you experiment, the sharper your prompts — and your results — will become.

To learn more about Coding Suggestions and Everlaw^AI Assistant, request a demo today.

Zach Sousa is a Customer Marketing Manager at Everlaw. Since joining the marketing team in July of 2021, Zach has organized Everlaw customer engagement programs such as webinars and customer testimonials. Prior to Everlaw, Zach had five years of experience as a B2B marketing manager in the medical device industry. See more articles from this author.