Retrieval-Augmented Generation (RAG)
A method that lets an AI look up your real information before answering, so its work is grounded in facts, not guesses.
Retrieval-augmented generation (RAG) is a technique where the AI first pulls up relevant information from a trusted source — your documents, product catalog, or knowledge base — and then uses that to write its answer. Instead of relying only on what it learned in training, it works from your actual facts.
The practical benefit is accuracy. A support agent using RAG can answer with your real return policy; a marketing agent can write with your real offers and prices. It keeps the AI anchored to what's true about your business rather than a plausible-sounding guess.
Why it matters
It's what lets an AI Expert answer with your real business details instead of generic or invented ones — the difference between trustworthy and risky.