Technical controls and policy-as-code to manage the unique risks of generative AI.
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Technical controls and policy-as-code to manage the unique risks of generative AI.
Generative AI introduces novel attack surfaces and compliance blind spots that traditional governance misses. We build the technical guardrails to enforce policy, track lineage, and ensure safe deployment.
Move from reactive audits to continuous, automated compliance integrated into your CI/CD pipeline.
Our frameworks translate regulations like the EU AI Act and ISO/IEC 42001 into enforceable code, providing:
This transforms governance from a cost center into a competitive advantage, enabling faster, safer innovation.
For a complete governance strategy, explore our related services for NIST AI RMF Compliance Consulting and Algorithmic Bias Auditing Services.
Effective governance for generative AI is not just a compliance checkbox—it's a strategic enabler that directly impacts your bottom line, risk profile, and competitive advantage. Here are the measurable outcomes our technical frameworks deliver.
Deploy compliant generative AI applications in weeks, not months. Our policy-as-code frameworks and pre-built compliance controls eliminate manual review bottlenecks, enabling rapid iteration and faster time-to-value while maintaining audit readiness.
Proactively mitigate financial exposure from regulatory fines, IP infringement claims, and security breaches. Automated monitoring for prompt injection, data leakage, and model drift prevents costly incidents before they occur.
Build stakeholder confidence with demonstrable controls. Our immutable audit trails, explainability integrations, and bias mitigation reports provide transparent evidence of responsible AI use, strengthening customer and partner relationships.
Govern thousands of models and prompts from a single dashboard. Centralized governance replaces fragmented, team-level tools, providing unified visibility, automated policy enforcement, and streamlined reporting across all AI deployments.
Adapt dynamically to evolving regulations like the EU AI Act and NIST AI RMF. Our modular, rules-engine architecture allows you to update compliance logic without refactoring core applications, ensuring long-term viability.
A secure governance foundation empowers teams to experiment safely. With guardrails for hallucination, content moderation, and data provenance in place, developers can push the boundaries of generative AI without introducing undue risk.
A structured, phased approach to implementing a robust Generative AI governance framework, ensuring technical controls are built alongside policy.
| Phase & Key Activities | Timeline | Core Deliverables | Outcome |
|---|---|---|---|
Phase 1: Risk & Compliance Gap Analysis | 1-2 weeks | Compliance heat map vs. EU AI Act/NIST AI RMF Inventory of all GenAI models & use cases Technical risk assessment report | Clear roadmap of required technical remediations |
Phase 2: Policy-as-Code & Control Design | 2-3 weeks | Encoded governance rules (Open Policy Agent/Rego) Technical specification for moderation, watermarking, and logging systems Architecture for real-time monitoring dashboard | Automated enforcement blueprint ready for development |
Phase 3: Core System Implementation | 3-5 weeks | Deployed prompt injection defense layer Integrated AI watermarking & content provenance Immutable audit logging pipeline Bias detection hooks for training data & outputs | Foundational technical controls are live and operational |
Phase 4: Governance Dashboard & Integration | 2-3 weeks | Custom enterprise AI governance dashboard Integration with existing CI/CD and model registries Automated compliance reporting templates | Single pane of glass for model oversight and audit readiness |
Phase 5: Training & Operational Handoff | 1 week | Technical runbooks for incident response Admin training on dashboard and policy engine Final compliance documentation package | Your team is empowered to manage and evolve the governance framework |
Ongoing Support & Evolution | Optional SLA | Quarterly policy reviews & updates Adversarial testing (red teaming) for new threats Assistance with auditor inquiries | Continuous compliance as regulations and AI systems evolve |
Our generative AI governance frameworks are engineered to address the unique compliance, risk, and operational challenges of your industry. We translate broad regulations into enforceable, technical controls.
Implement governance for algorithmic trading, fraud detection, and credit risk models. Ensure compliance with SEC guidelines, model risk management (SR 11-7), and EU AI Act high-risk classification for credit scoring. Our frameworks enforce transaction traceability and prevent discriminatory lending outcomes.
Read our case study on AI-driven financial compliance auditing.
Govern clinical decision support, ambient documentation, and diagnostic AI under HIPAA, FDA (SaMD), and EU MDR. We implement technical safeguards for patient data, algorithmic fairness in treatment recommendations, and rigorous validation for generative AI in drug discovery workflows.
Explore our work on healthcare clinical decision support and ambient AI.
Deploy governed systems for contract analysis, litigation prediction, and compliance automation. Our policy-as-code enforces client confidentiality, manages jurisdiction-specific rules, and provides immutable audit trails for bar compliance and e-discovery demands under frameworks like the EU AI Act.
Learn about our legal and compliance workflow automation services.
Build air-gapped, sovereign AI infrastructure with strict governance for intelligence analysis, geospatial AI, and autonomous systems. Our frameworks ensure compliance with ITAR, EAR, and specific defense directives, implementing hardware-based confidential computing and provenance tracking for all model outputs.
See our capabilities in defense and national intelligence AI.
Govern industrial copilots, quality inspection AI, and predictive maintenance models. Align with ISO 42001 for AI management systems and implement technical controls for operational safety, supply chain data sovereignty, and explainability for automated decisions on the factory floor.
Review our smart manufacturing and industrial copilot integration expertise.
Manage governance for hyper-personalization engines, dynamic pricing, and inventory AI. Implement bias auditing for recommendation algorithms, data privacy controls for consumer behavior models (CCPA/GDPR), and transparency for automated pricing decisions to mitigate regulatory and reputational risk.
Discover our approach to retail and e-commerce hyper-personalization.
Get specific answers about our process, timeline, and technical approach for implementing robust governance for your generative AI systems.
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