Building a RAG prototype is easy. Maintaining it ("Day 2") is hard. Manual testing doesn't scale, and generic benchmarks fail on specific business data.
Google Cloud just released auto-rag-eval to fix this "Evaluation Gap." It essentially acts as an automated, rigorous QA team for your AI.
Why it's different:
- No Circular Logic: It builds a "Ground Truth" independent of your retrieval method—so you aren't grading your homework with your own answer key.
- Mimics Humans: Instead of random queries, it uses "Adaptive Profiles" to test both simple fact-finding and complex strategic reasoning.
- Multi-Agent Debate: Three distinct AI agents argue over every question's validity. If they don't agree on the quality, the question is tossed.
Resources: