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Get grounded answers.

RAG-powered conversations backed by your knowledge base. Every answer cites its source — no hallucinations, no guessing.

  • Answers grounded in your docs — not the open internet
  • Source citations with every response
  • Persistent conversation history
  • Works with any LLM via LiteLLM proxy
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Under the hood

How RAG works

Retrieval-Augmented Generation keeps AI answers accurate by grounding them in your actual documents.

01

You ask a question

Your question is converted to a vector embedding using the same model that indexed your KB.

02

Semantic search

The nearest matching chunks are retrieved from your knowledge base using cosine similarity.

03

Context is assembled

The top chunks are bundled with your question into a prompt with full source attribution.

04

AI generates the answer

The LLM synthesises a precise answer from the retrieved context — not from training data alone.

Features

Everything in one chat

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