Automated Evaluation

Automated evaluation lets you assess model behavior at scale — running thousands of test cases quickly without needing a human to review each one. Common approaches include rule-based checks (did the response include a required phrase?), similarity scoring against reference answers, and increasingly, using a separate model to judge quality. The tradeoff is precision: automated systems are fast and consistent, but they may miss nuances that a human reviewer would catch. In practice, most mature evaluation setups use automated evaluation as the foundation, with human review reserved for edge cases, calibration, or situations where automated scores seem unreliable.