A defined evidence workstream for active reviews.
- AI vendors responding to procurement or customer-assurance requests outside their home market
- Multinational procurement teams that need a reconstructable evidence position for one AI system
- Law firms, advisers, and assessors that determine applicability and need a bounded evidence handoff
- Organizations using NIST AI RMF or buyer-defined requirements as common review language
What enters the review package.
AI system purpose, owner, version, deployment boundary, intended use, and material dependencies
Governance, security, privacy, testing, data handling, human oversight, and change records
Buyer requirements and the exact source or framework version assigned to the review
Approvals, reviewer decisions, limitations, open conditions, and remediation records
Where procurement and assurance reviews stall.
The same claim is described differently across buyer questionnaires, frameworks, and jurisdictions.
Evidence exists, but it is not tied to the AI system, version, owner, or review date being examined.
Legal applicability has been identified, but the supporting artifacts cannot be reconstructed by the reviewer.
An earlier package exists, but changed evidence or buyer requirements have not been re-examined.
One fixed-scope engagement. Five reviewer-facing outputs.
Evidence Inventory, Mapping Summary, Gap Register, Ordered Remediation Plan, and Chain-of-Custody Statement.
- Define the AI system and review context.
- Receive and inventory the approved evidence set.
- Verify evidence relationships and record gaps.
- Order remediation by review dependency.
- Deliver the point-in-time evidence package.
Give reviewers a package they can examine without reconstruction.
$3,500. One defined AI system and review context. No annual license required.