Retrieval-augmented generation, also referred to as RAG, is an information retrieval technique that utilizes generative AI models in order to produce more accurate, relevant output. RAG systems retrieve relevant information from a knowledge base and use that to inform the output generation process. This can make the output more up to date, specific, and in depth.
