What is RAG (Retrieval-Augmented Generation)?

Retrieval-augmented generation is a technique where an AI model first retrieves relevant passages from a trusted knowledge source and then writes its answer from them.

RAG reduces made-up answers ("hallucinations") and keeps responses current, because the model answers from your documents, website or database rather than only from what it learned in training. Good RAG systems cite their sources and decline to answer when the content does not cover the question.

It is the standard architecture for business chatbots trained on a company's own content.