AI Vendor Evaluation & System Validation
Compare AI vendors against the work your organization actually needs to perform.
Who commissions this
A material decision needs technical evidence.
For enterprise procurement, IT, and business owners choosing between AI products, validating a shortlist, or assessing an expensive renewal.
Evaluation scope
What we examine.
- Agree representative workflows, failure costs, and a common scorecard before vendor demonstrations.
- Run equivalent trials with comparable datasets, access, human assistance, and system boundaries.
- Measure quality, operator effort, latency, integration requirements, and total cost of ownership.
- Examine privacy and security assumptions, data retention, exportability, model dependencies, and procurement evidence. Legal or certification conclusions require the relevant specialists.
Representative deliverables
Evidence you can review and use.
- Buyer-owned evaluation protocol and vendor scorecard
- Reproduced tests and a register of unverified vendor claims
- Cost and integration comparison with explicit assumptions
- Conditional recommendation and procurement evidence requests
Decision outcome
A defined decision outcome.
A traceable shortlist or purchase decision based on representative conditions. Vendor nonparticipation, unequal access, and undisclosed evaluator relationships remain visible.
Typical engagements begin at $50,000. The statement of work defines access, test conditions, deliverables, acceptance criteria, and the decision deadline. Missing access and unresolved claims are recorded explicitly.
Read the claim verification methodology · Read the adversarial evaluation protocol
Assessment scope and evaluator independence are agreed before work begins. Findings document confidence, limitations, and residual risks.
Review the assurance method ↗