Testing RAG-Grounded Agents: Offline Evaluation with LLM Judges

As RAG-powered support agents become critical for production AI systems, reliable evaluation methods are essential before deployment. This tutorial shows how to build offline evaluations that test generation quality over real documentation context, catching regressions and validating prompt and model changes without production traffic. Using cross-family LLM judges and pre-computed retrieval ensures that grounded agents reason correctly over documentation—a foundational requirement for trustworthy AI support systems.