Securely Harness the Transformative Power of AI.
Data drives business. AI drives better data decisions.
AI-powered tools, models, applications and platforms promise to revolutionize the way we collect and correlate data to deliver transformative business outcomes. AI models can wade through giant data lakes in a fraction of the time humans can — and often far more accurately — to uncover insights, identify trends, and make connections that were previously inaccessible.
The upside of this amazing technology is that it can help organizations automate repetitive or time-consuming processes to reduce wasted time and improve resource allocation. It can lead to better business insights and intelligent decision-making so that companies can optimize operations, more accurately forecast results, and speed goods and services to market. AI helps businesses anticipate market trends, respond to challenges, and scale effectively. It isn’t just an advantage; it is quickly becoming a necessity in a data-driven and dynamic world.
Despite the benefits, AI also poses significant challenges and risks. To harness its power, it is essential for organizations to approach the use of this technology with a defined end state. Responsible and effective AI use requires strategic thinking, mindfulness of security and compliance best practices, an optimized and AI-ready infrastructure, teamwork across the organization, and – very often – a little expert help from the outside. Structured offers that expert help.
Our AI Solutions Process
AI Strategy
All successful initiatives begin with a sound strategy. Structured’s AI Strategy services responsibly underpin your AI plans. We align AI projects with your broader business goals and operational requirements, including time-to-value acceleration, risk mitigation and regulatory compliance, process management, and end-user satisfaction – which includes your workforce as well as your customers.
We work closely with executive teams, line-of-business leaders, and internal stakeholders to identify and gain consensus around strategic AI opportunities. These strategic roadmap services address key priorities such as:
- Governance frameworks,
- Infrastructure security, optimization, and management,
- Application(s) and model development, and
- Training and enablement.
Through proven processes, security frameworks and tools, we help establish practices that protect and operationalize your AI investments while accelerating innovation. The result is a strategic plan that balances powerful capabilities with practical controls, ensuring your AI initiatives deliver measurable business value.
STRUCTURED OFFERS EXPERT HELP
We can help you create an AI strategy and define your ideal end state. We can optimize and secure your on-premises and cloud infrastructure to minimize risk and maximize capabilities. We can work with you to identify data sets and correlate silos that feed AI algorithms, models, applications, tools and platforms, generating more accurate and actionable results. Finally, we help you establish a sound and scalable AI Factory – one that is ready to meet today’s requirements and rise to the challenges we encounter tomorrow.
SERVICE SUMMARY
- Define your desired outcomes.
- Identify opportunities to leverage AI and assess business challenges.
- Design scalable AI models and systems.
- Integrate solutions seamlessly with existing IT and communications environments.
AI Security and Compliance
Security and compliance are foundational to Structured’s AI Practice. We protect AI workloads, applications and models through strict adherence to security frameworks, robust governance controls, cybersecurity best practices, and the utilization of industry-leading threat detection tools.
Specifically, we protect AI systems and organizational data through comprehensive model security, including defense against adversarial attacks and data poisoning. Our security-first approach implements threat mitigation and privacy-preserving techniques for compliance with voluntary frameworks as well as mandates inherent in international, federal and state laws.
REGULATORY EXPERTISE
Our regulatory expertise includes deep knowledge of the:
- NIST Cybersecurity and Privacy Frameworks
- ISO 27001
- Health Insurance Portability and Accountability Act (HIPAA) and HITRUST
- Payment Card Industry Data Security Standard (PCI DSS)
- General Data Protection Regulation (GDPR)
- California Consumer Privacy Act (CCPA)
- and more
From securing training data to protecting deployed models, we ensure your AI operations meet the highest security standards for enterprise protection and compliance. Leveraging our three decades of cybersecurity expertise, we help you build resilient and trustworthy AI systems that can detect and respond to emerging threats while maintaining operational efficiency.
WE HELP YOU
- Create policies for secure data access and acceptable use of AI models and tools.
- Evaluate and deploy industry-leading cybersecurity tools and platforms.
- Secure data, applications, users and infrastructure in on-premises or cloud-based environments.
- Comply with local, state, federal and global compliance requirements for data handling and consumer privacy.
AI Service Pillars
Structured’s AI practice delivers secure AI transformation through four service pillars.
These service pillars, supported by purposeful AI strategic planning and comprehensive security and compliance oversight, ensure your journey into AI results in decreased risk, faster monetization, differentiated business value, and a workforce that is better equipped to step into the future.
Pillar 01: AI Governance Frameworks
- AI governance operating model creation, including policy creation and control definitions.
- AI program alignment with existing frameworks and controls.
- Role and responsibility definition and assignment to enhance oversight and decision-making.
- Risk identification and mitigation planning.
- Sustainable use planning and documentation.
Pillar 02: AI Infrastructure Optimization
- Setting up secure and scalable cloud and on- premises infrastructure optimized for AI workloads.
- Tuning systems to ensure they support the scalability and efficiency of AI operations.
- Ongoing infrastructure optimization, management and cost control.
Pillar 03: AI Program Development
- AI Program strategy and success definition.
- Readiness Assessment services.
- Data pipeline creation for effective AI model training.
- Prompt engineering, retrieval-augmented generation and fine tuning.
- Sandbox & pilot program development.
- Establishment of effective CI/CD infrastructure.
Pillar 04: Training & Enablement
- Technical Training: Hands-on workshops covering prompt engineering, model tuning, and best practices for interfacing with AI systems across different roles and use cases.
- Use Case Development: Collaborative sessions to identify department-specific opportunities and develop practical implementation strategies that drive measurable outcomes.
- Program Development: Methodical programs to overcome resistance, build confidence, and create networks of responsible and knowledgeable AI champions who accelerate adoption across teams.
AI Factory
Much like a traditional manufacturing facility procedurally assembles component parts into a finished hard good, an AI Factory is a digital assembly of raw data, complex algorithms, testing and feedback loops that lead to more intelligent and informed decision making.
The AI Factory is supported by optimized infrastructure – much like a manufacturer’s conveyor belts, machine shops and robotic assembly arms – on-premises, in the cloud, or both. Finally, as with every business, an appropriately trained and empowered workforce is essential to delivering on the factory’s promise.
The end result of strategic planning, meticulous security and compliance adherence, and careful preparation as outlined in the four service pillars described here, is a trustworthy AI Factory that can help streamline business processes, drive innovation, enhance workforce and customer satisfaction, and grow your market share.
Our strategic AI Factory approach supports everything from:
- Initial strategy and development,
- Data collection and correlation,
- Algorithm/model training and pilot programs,
- A/B testing and feedback loop evaluation, and
- Optimized, secure and scalable production deployment.
Transformative Business Outcomes
AI’s promise is still evolving as humans invent more ways to channel its capabilities. But even today, in the paradigm’s relative infancy, AI is powerfully transforming individual businesses, entire industries, and even global society.
The key is to get ahead of this revolutionary technology in a strategic, systematic, and secure process so that it works for you and your organization. But that is a tall order considering the dearth of qualified AI engineers to assist in this endeavor.
The solution is to partner with a trusted, experienced, and security-focused AI services provider. A trusted ally in this complex and dynamic process.
Structured is one such ally.
We can help you identify, create, protect and sustain the use of AI models and applications in your own environment. Or, if you aren’t ready to take on a project of this magnitude, we can help you leverage existing Cloud AI platforms like Microsoft Azure AI or AI-powered tools like Microsoft Copilot.
In short, we help you harness AI’s transformative power to create better outcomes for your business. Our services reduce risk and ensure you have an AI Factory that helps you automate tasks, reduce human error, identify trends, forecast events, streamline processes, and innovate faster. All for the good of your organization, its workforce, and customers.
Let’s get started today.
Answers to Your Frequently Asked Questions
How is AI being used in compliance?
AI is transforming compliance by automating risk assessments, continuously monitoring regulatory changes, and ensuring adherence to evolving standards. It enhances fraud detection and anomaly tracking by analyzing vast datasets in real-time, identifying suspicious activities that might go unnoticed by human auditors. AI-driven compliance platforms streamline document processing, contract analysis, and policy enforcement, reducing manual workloads and human errors. Machine learning algorithms help predict compliance risks by recognizing patterns and flagging potential violations before they escalate. Additionally, AI improves regulatory reporting by reducing the complexity of third-party risk management, automatically generating compliance reports, and maintaining audit trails for transparency and accountability.
What is the framework of AI governance?
The framework of AI governance consists of structured policies, ethical standards, and regulatory controls that guide the responsible development and deployment of AI systems. It establishes accountability by defining roles, responsibilities, and oversight mechanisms to ensure AI operates within legal and ethical boundaries. Risk management is a core component, focusing on mitigating issues like bias, security vulnerabilities, and unintended consequences through continuous monitoring and assessment. Compliance mechanisms, such as audits, impact evaluations, and regulatory reporting, help maintain adherence to industry and government standards. Ultimately, AI governance ensures that AI technologies align with human values, promote fairness, and remain transparent while supporting innovation.
What are three (3) of the governing principles of AI systems usage?
- Transparency ensures that AI-driven decisions are explainable, traceable, and understandable by stakeholders.
- Accountability is another essential principle. It requires organizations to establish clear responsibility for AI actions and implement mechanisms to address errors, biases, or unintended consequences.
- Fairness and Bias Mitigation ensure that AI systems operate equitably and prevent discrimination by actively identifying and reducing biases in training data and algorithms.
These principles are enforced through internal governance policies, compliance with regulatory frameworks, and continuous audits of AI performance. Together, they promote ethical AI deployment while maintaining trust and reliability in automated decision-making.
What is the governance model of AI?
The governance model of AI is a structured framework that defines how AI systems are designed, deployed, and managed to ensure ethical and regulatory compliance. It includes policies that establish oversight, accountability, and risk mitigation strategies to prevent unintended consequences such as bias, security threats, and misinformation. This model integrates technical safeguards, legal requirements, and human oversight to maintain control over AI decision-making processes. Organizations implement governance through structured committees, continuous monitoring, and automated compliance checks that evaluate AI performance and fairness. Ultimately, AI governance models aim to balance innovation with responsibility, ensuring AI operates transparently and aligns with ethical and legal standards.
Will compliance be replaced by AI?
AI will not replace compliance but will significantly enhance and automate many of its processes. While AI can streamline regulatory monitoring, risk assessments, and reporting, human oversight remains essential for interpreting complex regulations and making judgment-based decisions. Compliance involves ethical considerations, legal nuances, and industry-specific requirements that AI alone cannot fully grasp or enforce without human intervention. Instead of replacing compliance, AI will serve as a powerful tool that increases efficiency, reduces errors, and helps organizations proactively manage regulatory risks. The future of compliance will likely involve a hybrid model where AI handles routine tasks while human experts focus on strategic decision-making and oversight.
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