Complete procedures with a way back.

Build a production RAG evaluation program that separates retrieval recall and precision from answer faithfulness, citation validity and support, correctness, usefulness, and abstention; calibrates automated graders with humans; blocks security regressions; and carries evidence through regression, canary, continuous evaluation, and rollback.

Create a privacy-governed, versioned evaluation corpus and regression system with deterministic and calibrated model graders, baselines, slices, complete coverage, failure analysis, CI gates, deprecation-aware versioning, shadow rollout, monitoring, and complete release rollback.