Enterprise procurement teams evaluating AI vendors operate with a systematic information disadvantage. Vendors control the benchmarks. This solution gives procurement an evidence-based scoring framework across capability, security, data residency, and pricing leverage.
AI vendor evaluation is broken in a specific and predictable way. Vendors publish benchmarks on tasks they perform well. Marketing claims outpace independent verification by 12–18 months. The technical capability required to assess model quality, security posture, supply chain provenance, and data residency compliance is concentrated in a handful of research institutions — not in corporate procurement functions.
A structured scoring system combining public benchmark data (HELM, BIG-bench, LMSYS Arena), third-party security assessments, regulatory filing analysis, and LLM-assisted capability comparison gives procurement teams an evidence-based evaluation framework. It turns the vendor selection conversation from a reference-check process into a documented, defensible scoring exercise — and the scoring artifact becomes leverage in renewal negotiations.
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