Retrieval-Augmented Generation (RAG) combines document retrieval systems with Large Language Models (LLMs) to answer queries by first retrieving relevant documents and then generating accurate responses based on their content. This approach ensures responses are grounded in specific, reliable information from a company's documents, enhancing accuracy and context. RAG improves efficiency and productivity by enabling quick access to relevant information, supporting informed decision-making within organizations.
