Capability
Correctness, relevance, calibration, retrieval, citation support, robustness, latency, and cost where material.
AI evaluation + governance
Know what an AI system can do before asking people to depend on it.
Evaluation turns broad claims into testable requirements, visible failure modes, release criteria, and an operating plan for monitoring and human review.
Evaluation surface
Test the system that users experience.
Failure and risk
Harmful outputs, unsupported claims, data exposure, bias, edge cases, misuse, and escalation paths.
Operations
Release criteria, human review, monitoring, change control, incident handling, and ownership.
Governance should be operational
Policies matter when they change a decision.
Useful governance assigns owners, defines evidence, establishes approval and escalation, records changes, and makes monitoring actionable.
Before releaseRequirements, data, tests, thresholds, approvals
After releaseMonitoring, feedback, incidents, changes, retirement
Appropriate scope
Evaluation does not equal certification.
This service should not be represented as legal advice, regulatory certification, or a guarantee that a system is safe. Claims must match the actual review, evidence, and professional boundaries.
Planning a release or reviewing a system?