Pavan Ganesh Indupudi (Infernix) · Originally published at the-infernix.github.io

Ask most RAG demos "Who is the Prime Minister of India?" and they will happily hallucinate an answer from whatever passage happens to look semantically close. VOICE-RAG — built for HH Goa 2026 — answers that question with a refusal and a number:

Refused: Top retrieval score 0.779 below relevance floor 0.840

That sentence is the whole thesis. The system answers spoken questions in English, Hindi, Gujarati, and Telugu — strictly from a curated 40,000-passage corpus — and refuses when the corpus does not contain the answer . This article covers why that turned out to be the hard part, and how the 56 ms core around it was built.

The problem: fluent answers with no evidence

Retrieval-augmented generation fails in two directions. Too loose, and the generator papers over missing evidence with fluent nonsense. Too strict, and the system refuses questions it could have answered.…