Safety & Reliability
Operational controls for safety & reliability, with maturity levels, evidence requirements, and implementation guidance.
Not sure where to start? Answer 3 questions and get a tailored compliance action plan.
What applies to me? →6 controls matching filters
Hallucination Detection and Mitigation
Implement controls to detect, reduce, and manage AI-generated factual errors and fabrications before they reach end users or inform decisions.
AI Output Validation
Validate AI-generated outputs against defined quality, safety, and format criteria before they are presented to users or used in downstream processes.
AI Graceful Degradation
Define and implement fallback behavior for AI systems when they are unavailable, underperforming, or producing outputs below acceptable quality thresholds.
AI Reliability Testing
Systematically test AI systems for consistency, repeatability, edge-case handling, and behavior under load before deployment and on a recurring basis.
Harmful Content Filtering
Apply input and output filtering to prevent AI systems from generating or acting on harmful, toxic, illegal, or policy-violating content.
Post-Deployment Adversarial Testing Cadence
Schedule and execute recurring adversarial testing of production AI systems on a risk-tiered cadence, separate from and in addition to pre-deployment red-teaming.
Safety & Reliability, tracked weekly
New safety & reliability controls and the regulatory developments driving them, plus everything else changing in AI governance. Every Thursday.