RAG (retrieval-augmented generation)

RAG, short for retrieval-augmented generation, is a method where an AI system first searches your documents for relevant passages and then writes its answer from those passages. It keeps answers grounded in your own material and makes it possible to show where each answer came from.

Agentic RAG goes further: the assistant plans several searches across different sources and checks the results before answering.