RAG (Retrieval-Augmented Generation)

Retrieval-Augmented Generation is a technique that combines an AI model's language capabilities with the ability to look up specific information from a defined knowledge base. Instead of relying solely on what the model learned during training, RAG retrieves relevant documents or data at the moment of a query and uses them to inform the response. For businesses, RAG is what makes it possible to build AI tools that answer questions accurately about your specific products, policies, and internal knowledge — without the hallucination risk that comes from asking a general model to remember specific facts.