RAG Pipeline Doctor
A diagnostic tool that ingests your RAG pipeline config plus a set of failing queries and tells you exactly why retrieval returns garbage: oversized chunks, embedding mismatch, missing reranking, or OCR-mangled source...
- Target market
- Indie devs and small AI teams of 1-10 who built a RAG feature on LangChain, LlamaIndex, or raw pgvector and are stuck debugging bad answers in production.
Problem snapshot
What this solves
Teams ship a RAG chatbot, it nails the demo, then in production it confidently returns the wrong paragraph or says 'I don't have that information' to questions the docs plainly answer. Debugging means eyeballing retrieved chunks by hand, guessing whether the culprit is chunking, embeddings, or the prompt, and rerunning blind. There is no single tool that…
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