AI That Transforms Business Objectives into User Stories
Trusted by the world’s leading businesses
Trusted by the world’s leading businesses
The real shift in how requirements turn into work items
The Old Way
- I rewrite long requirements into actionable user stories and hope I didn’t miss anything.
- I write use cases one by one from existing requirements and spend hours on that.
- I write Gherkin scenarios line by line and often forget edge cases until later.
- I create new work items manually by copying text from one item to another.
The new way with the Convert module
- I use Convert to turn the same text into a complete story with acceptance criteria in a few seconds.
- I use AI to extract all use cases from Azure requirements, including edge cases.
- I select Convert and receive multiple Gherkin scenarios, including variations I might not have thought of.
- Once Convert generates a work item, I directly insert it into the Azure backlog with a single click.
What is the Convert feature in Copilot4DevOps?
Convert is a module of Copilot4DevOps that helps teams convert requirements into actionable and ready-to-use work items using an AI. Instead of manually turning business goals or documents into user stories, use cases, or Gherkin scenarios, teams can use Convert to create clear, structured items directly from Azure work items.
The Convert module helps teams in removing guesswork in early planning and avoiding the back-and-forth that usually happens when requirements are interpreted differently by stakeholders, analysts, testers, and engineering teams. Overall, it saves hours usually lost in rewriting or clarifying requirements.
Here is how different job roles are using the Convert module within Azure DevOps
Business Analyst
CTurn long requirements, feedback notes, and meeting notes into structured user stories using an AI and share them with development teams.
Product Owner
Convert product ideas or features into ready-to-use user stories and use cases, and insert them into the Azure DevOps.
Scrum Master
Generate user stories and Gherkin scenarios from unstructured requirements using an AI while doing the backlog grooming during the sprint planning.
Project Manager
Translate project documents into ready-to-use and actionable work items and share them with the product team to implement.
Developer
Prepare user stories with acceptance criteria from vague requirements and insert them into the Azure backlog to track the progress.
Test Engineer / QA Engineer
Produce Gherkin scenarios and edge-case checks directly from requirement text. This cuts down hours normally spent building test steps manually and gives QA teams a reliable starting point that mirrors the requirement’s intent.
Solutions Architect
Shape high-level requirement statements into use cases that list actors, flows, and conditions. This gives architects a structured view of expected behavior and helps them map system interactions without rebuilding the entire format from zero.
Compliance Officer
Turn compliance or regulatory requirements into actionable work items. So, development teams can develop the product that follows regulatory requirements.
Release Manager
Generate user stories for the product deployment and continuous monitoring from the release meeting notes.
DevOps Engineer
TConvert operational needs, environment notes, or infrastructure requests into work items that are easier for teams to follow. This helps avoid misinterpretation when translating platform requirements into engineering tasks.
Support Engineer
Turn customer feedback or bugs into user stories and share them with development teams so they can work on fixing bugs.
Domain Expert / SME
Convert industry-specific requirement text, whether medical, financial, aerospace, or manufacturing, into structured stories or scenarios without learning formal formatting rules.
Core capabilities of the Convert module help teams shape clear backlogs
User story generation
Need to convert Azure requirements into structured user stories?
The Convert module generates user stories with a title, description, and acceptance criteria from existing Azure work items content using an AI, which you can directly insert into the Azure DevOps.
Use case creation
Want to write structured use cases with all the usual components in place?
This feature generates clear use cases with summary, actors, preconditions, postconditions, primary flow, alternate flow, and acceptance scenarios. This saves teams from building the entire template manually.
Gherkin scenario generation
Need test scenarios that match the requirement and cover more than the obvious path?
The Convert drafts Gherkin scenarios that include variations and edge cases, giving testers dependable material without reinterpreting the requirements themselves.
Custom instructions
Want to generate a response in a specific format or language?
Provide custom instructions in plain text to balance response length, creativity, or structure. You can even select a language in which you want AI to write a response.
Add to field / Create work item
Want to share the generated response with internal team members?
Insert the generated response directly into the current Azure work item or create a new work item and share it with your team.
Copy output
Need to insert the generated work item into the external document?
Use the Copy button to copy the response and paste it anywhere in the document to share with team members who don’t have access to your Azure workspace.
See the Convert module in action across different industries
Use case 1: Managing regulatory work in healthcare
A software development team working on healthcare projects generally gets insurance rules, policy documents, and patient-safety guidelines in the documents or as raw requirements from business analysts or the project manager. However, those raw requirements are not enough to start development, and they need to be converted into actionable user stories. Manually converting each raw requirement into a user story can take hours.
As a solution, teams can use the Convert module of Copilot4DevOps to convert Azure work items into structured user stories using AI with a single click and insert them into the Azure backlog. The best part is that the development team also gets acceptance criteria with each user story, so they can implement all features without missing anything.
Use case 2: Tracking contract requirements in aerospace and defense
Aerospace teams usually handle lengthy government contracts packed with technical clauses, handoff conditions, and certification expectations. When these documents reach Azure DevOps, teams must manually carve them into tasks or stories, and the process often slows down because every clause must be interpreted line by line.
With Convert, teams can take a contract excerpt and turn it into structured work items using AI that reflect the intent of the requirement. They can generate use cases or Gherkin scenarios that match the contract language and insert them into the Azure backlog. This helps in aligning development and testing teams with requirements.
Use case 3: Translating operational requirements in manufacturing
Manufacturing teams often use Azure DevOps to track system behavior that depends on hardware states, production-line constraints, or quality rules. The initial requirement text is usually drafted by operations or equipment specialists, and software teams must rewrite it before any coding can begin.
Convert lets these teams take operational descriptions and produce structured stories or scenarios without reinterpreting every detail. By turning production notes into consistent Azure DevOps items, development and operations teams stay aligned, and the requirement keeps its original meaning even when passed across departments.
The quiet benefits that make Convert worth using
- Save time: Cut down 80% of the time spent on manually extracting structured work items from raw requirements.
- Reduce misinterpretation: AI takes the context from existing requirements and generates structured work items from them without missing any context. This reduces misinterpretation.
- Native to Azure DevOps: It directly works within Azure DevOps. So, teams don’t need to manage data across multiple scattered tools.
- Stay consistent: AI follows the same custom instructions provided by your team every time. Hence, it generates consistent output.
- Stronger traceability: Generated content can be directly added to the Azure backlog. So, it becomes easy for teams to track work items.
- Handle changes faster: When any changes occur in requirements, teams can quickly use AI to generate new user stories. This helps teams adapt to changes faster.