Markets · Vendors & Contractors
Vendor / Procured AI Evidence Review
AI vendors and AI buyers both need evidence. Buyers need to know whether a vendor's AI system can be governed, monitored, explained, contracted, and reviewed. Vendors need to show that their systems can support the obligations their customers carry.
Who this is for
Both sides of the AI procurement table.
- — Banks buying AI systems
- — Credit unions buying AI systems
- — Federal and state agencies procuring AI
- — Contractors selling AI to government
- — Vendors selling AI to regulated buyers
- — Procurement teams
- — Vendor risk teams
- — Legal and compliance teams
- — Product teams building regulated AI offerings
The problem
AI vendors sell capabilities. Regulated buyers need evidence.
A model card, system card, marketing deck, or SOC report may not be enough to answer the questions a regulated buyer has to put to a vendor before signing:
- What decisions is the system intended to influence?
- What uses are prohibited?
- What data was used?
- What testing was performed?
- What limitations are known?
- What monitoring is provided?
- What responsibilities stay with the deployer?
- What human oversight is required?
- What documentation supports adverse action, notice, appeal, correction, audit, or procurement review?
- What happens when the model changes?
That gap creates risk for both buyer and vendor.
Method
Applicability → Decision → Risk → Control → Evidence
- Applicability
- Which buyer obligations, procurement requirements, state laws, federal policies, or contractual expectations are relevant.
- Decision
- What decision or workflow the vendor system will influence.
- Risk
- Who is affected, and what could go wrong.
- Control
- Which controls need to be performed by the vendor, the buyer, or both.
- Evidence
- What documentation proves the controls exist and can be inspected.
What we review
Three sets of documentation.
Vendor documentation
- — Model cards
- — System cards
- — Product documentation
- — Intended use statements
- — Prohibited use statements
- — Training data summaries
- — Testing reports
- — Bias and fairness reports
- — Security and privacy documentation
- — Change management documentation
- — Incident response documentation
- — Monitoring and support commitments
Procurement documentation
- — AI acquisition risk assessment
- — Solicitation requirements
- — Vendor questions
- — Contractual safeguards
- — Data rights and IP terms
- — Privacy and security terms
- — Monitoring requirements
- — Human oversight responsibilities
- — Termination and portability provisions
- — Vendor lock-in risk
Deployer documentation
- — Use case intake
- — Business decision mapping
- — Owner assignment
- — Human review procedure
- — Evidence retention plan
- — Monitoring process
- — Complaint, appeal, and correction process
- — Incident escalation procedure
Common gaps
Where vendor and buyer documentation usually misses.
Intended-use gap
The vendor describes what the system can do, but not the decisions it is appropriate to influence.
Responsibility gap
The vendor assumes the deployer will handle governance. The deployer assumes the vendor has already handled it.
Evidence gap
The buyer receives product claims but not reviewable artifacts.
Monitoring gap
The contract does not define what will be monitored, by whom, how often, or what happens when performance changes.
Change-management gap
The buyer does not know when vendor model, data, prompt, policy, or system changes trigger review.
Downstream obligation gap
The vendor does not provide documentation the buyer needs for adverse action, disclosure, audit, procurement, or oversight.
Deliverables
What an engagement produces.
- Vendor AI evidence review
- Procured AI applicability matrix
- Buyer/vendor responsibility map
- Required documentation checklist
- Contract and procurement issue list
- Evidence sufficiency review
- Deployment governance checklist
- Monitoring and change-management recommendations
- Remediation roadmap
The outcome
Both sides can answer the questions that matter.
A buyer can answer
- Can this AI system be governed?
- Can we explain how it affects decisions?
- Can we monitor it?
- Can we prove our controls?
- Can the vendor support our obligations?
- Do our contracts require the right evidence?
A vendor can answer
- What documentation do regulated buyers need?
- Which obligations do our customers carry?
- Which controls can we support?
- Which responsibilities remain with the deployer?
- What evidence should we package before procurement?
Next step
Start with applicability.
If your organization is buying, deploying, or selling AI in regulated environments, the first conversation is an applicability conversation.
Book an Applicability Call