What are evals in AI?
An evaluation suite is a repeatable set of real cases with known good outcomes, run before each release to measure quality and catch regressions when prompts, models or tools change.
An eval set is a collection of real cases with known good outcomes that you run every time a prompt, model or tool changes. Start with 50–200 cases during the prototype and track a few metrics, such as field accuracy, correct routing rate or how much reviewers edit drafts. Without evals, every change becomes a debate about whether outputs look better; with them, it is a number that can block a bad release.