The RAG question nobody plans for: 'what if it's just not in the documents?'

A confidence gate catches weak matches, but out-of-scope questions need a different check: does the retrieved context even address the question's topic at all?

Written by

Pranjul Rathour

GenAI Engineer at SCULT INDIA, based in Kanpur, India. Builds production RAG systems, fine-tunes open LLMs and ships agentic AI products; has mentored 200+ college developers. Open to GenAI roles, hackathon judging, mentorship sessions and guest talks.

pranjulrathour41@gmail.com LinkedIn GitHub X Instagram Bluesky Dev.to

A confidence gate on retrieval scores catches weak matches. It does not catch a strong match on the wrong topic — a question about refund policy retrieving a strongly-matched but irrelevant passage about return shipping addresses.

Add a relevance check, separate from a similarity score

After retrieval, ask the model directly: 'does this context address this question, yes or no?' before generating the final answer. It is a cheap extra call that catches a class of errors similarity scores miss entirely.

Refuse clearly when the check says no — 'I don't have that in the documents I was given' beats a confident wrong guess.
Log refusals; a spike on one topic usually means a document gap, not a bug.
Do not skip this check to save latency on a support or compliance bot — the cost of a wrong answer is higher there.

Builds on what a confidence gate is and citations in RAG answers.

— Pranjul Rathour, GenAI Engineer from Kanpur, India. Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at any campus: pranjulrathour41@gmail.com.