Self-improving RAG system that optimizes across 7 dimensions on Meta's CRAG benchmark
You want a RAG system that does not just retrieve and generate — it autonomously discovers which chunking strategy, embedding model, retrieval method, and prompt template works best for your domain.
The optimizer discovered that hallucination validation beats compute scaling — a finding that manual tuning would not surface at $0.78 per experiment.