Define the boundary
Confirm the AI system, review driver, framework, evidence window, and target decision date.
Inventory and hash
Register supplied artifacts and generate SHA-256 content hashes to identify the reviewed versions.
Generate candidates
Use hybrid evidence candidate mapping to surface possible relationships between artifacts and requirements.
Verify with a human
A human reviewer accepts, rejects, or qualifies candidate relationships; candidate scores are not compliance measures.
Classify and preserve
Apply deterministic risk classification while preserving the inputs and decision path used.
Sequence remediation
Order unresolved evidence work around stated dependencies and the target submission or decision date.
Could a reviewer reconstruct the evidence position for one AI system?
Bring one active AI review, the review type, and the decision date. The request form sends these details to Mark for a personal fit review; it does not reserve a calendar appointment or accept evidence.