RAG (Retrieval Augmented Generation)
What does it mean?
RAG, or Retrieval Augmented Generation, is a technique where an AI model first retrieves relevant information from your own documents and generates an answer based on it — with source citations. Because the answer is grounded in your sources, the chance of made-up content (hallucinations) is much smaller.
A language model knows nothing about your contracts, manuals or files on its own. RAG solves that: for every question the system first finds the most relevant passages in your knowledge base and has the model formulate an answer on top of them. The user sees which sources were used and can click through.
RAG is the foundation under most business AI knowledge systems. It works best when your sources are well organised and up to date — something we steer on during setup.
From concept to application?
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