Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG): Building AI Systems on Enterprise Knowledge Bases

Retrieval-Augmented Generation (RAG) is a powerful approach that allows AI systems to generate responses grounded in enterprise-specific knowledge rather than relying solely on pre-trained model data. By retrieving relevant information from internal documents, databases, and knowledge repositories at query time, RAG significantly improves accuracy, relevance, and trustworthiness while reducing hallucinations.