Why it matters
AI evaluation assesses behavior across answers, retrieval, permissions, and regressions. Narrow testing on demo questions hides systemic weakness.
How it works
Combine automated suites, human rubric reviews, red-team probes, and production sampling into an evaluation program with owners and cadence.
Example
Nintendo quarterly AI evaluation spans chatbot billing tests, docs assistant API questions, permission probes, and retrieval recall benchmarks.
Common mistakes
- 1Eval only before initial launch
- 2Metrics without action thresholds
- 3Siloed eval for RAG versus policy versus UX
Test the answer before your customer does.
Run answer tests and evaluations against your governed knowledge before you ship.
See answer evaluations