Back to Glossary Retrieval-Augmented Generation (RAG) An AI architecture that enhances large language model (LLM) responses by first retrieving relevant information from an external knowledge base, such as enterprise documents, databases, or SharePoint, and grounding the model’s generated output in that retrieved context. RAG enables organizations to build AI assistants that answer questions accurately based on proprietary organizational knowledge, significantly reducing… An AI architecture that enhances large language model (LLM) responses by first retrieving relevant information from an external knowledge base, such as enterprise documents, databases, or SharePoint, and grounding the model’s generated output in that retrieved context. RAG enables organizations to build AI assistants that answer questions accurately based on proprietary organizational knowledge, significantly reducing hallucination and keeping responses current without requiring costly model retraining.
