RAG (Retrieval-Augmented Generation) is a "retrieve first, answer second" AI architecture: before the model responds, it pulls relevant content from your knowledge base and then generates an answer grounded in that material. It treats two of the biggest pain points of large language models — not knowing your private data and hallucinating.