A language model alone knows general internet knowledge but not your contracts, procedures or price lists. RAG (retrieval-augmented generation) is the pattern that lets AI answer from your documents — with a reference to the source, not from invention.
How RAG works in short
- —Company documents are split into chunks and turned into vectors (embeddings).
- —When a question comes in, the system finds the most relevant chunks.
- —The model gets the question + those chunks and answers from them.
- —The answer can point to the source — a specific document or paragraph.
Where RAG fits
- —An internal copilot for the team — fast answers from procedures and company knowledge.
- —Customer support based on real documentation, not generalities.
- —Searching across contracts, quotes, manuals.
- —Onboarding — a new hire asks the system instead of digging through folders.
tip
RAG's biggest advantage over a plain chatbot: the answer is grounded in your documents and the source is checkable — which limits hallucinations and builds trust.info
We build RAG over your company documents — with source control and data security. https://cyberninja.digital/book