Model evaluation is the systematic testing of an AI model or agent against defined quality, safety, and business criteria.

Why Model evaluation matters

A model that performs well on general benchmarks may still fail on a company's real callers, policies, products, or revenue workflows.

How it works in practice

Evaluation should combine curated test cases, real interaction review, automated checks, outcome metrics, and repeated regression testing whenever models or instructions change.