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How to Audit an AI Vendor's Eval Suite Before You Sign (8-Dimension Checklist)

Most AI vendor evaluations stop at a sales demo and a certification badge, which tells you almost nothing about whether the vendor's system actually gets tested against the failure modes that matter for your use case. An eval-suite coverage audit is a more useful lens: it asks what the vendor can prove they test, not what they can describe in a call.

A recent AI vendor evaluation checklist breaks this down into eight dimensions worth checking before you sign: groundedness (are outputs faithful to the provided context), citation accuracy, regulatory compliance, adversarial-input testing (injection, jailbreak, bypass attempts), hallucination KPIs with task-specific definitions, drift and regression tracking against baselines, whether production incidents actually feed back into the eval suite, and security/compliance governance scoped to the AI workflow specifically.

The practical trick is asking for native artifacts instead of screenshots: eval plans, test taxonomies, golden datasets, scoring rubrics, failure logs, and CI/CD evidence tied to real release gates. The piece scores evidence into three buckets: green (reproducible, live artifacts, real release gates), yellow (partial or unverifiable, like screenshots or benchmarks without methodology), and red (vague claims, demo-only examples, or a vendor that won't share artifacts at all).

It's also useful for catching specific misleading claims. "We have an eval harness" isn't the same as having coverage, so ask what tests have failed and what releases got blocked. "Our RAG system prevents hallucinations" conflates retrieval recall with groundedness, which are different things worth measuring separately. And "we're compliant" needs a scope check: does that SOC 2 or ISO 42001 certification actually map to your workflow, or just some other part of the vendor's stack?

Which dimensions matter most depends on your risk profile. An internal tool needs less scrutiny than a customer-facing system, and a regulated use case needs strong evidence across all eight. The full piece includes a decision framework (proceed, proceed-with-remediation, restricted pilot, or reject) and a walkthrough of what to convert into contractual obligations once you've picked a vendor.

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