AI Architecture
RAG (Retrieval-Augmented Generation)
An AI architecture that combines information retrieval with text generation to produce accurate, context-aware responses.
Retrieval-Augmented Generation (RAG) is an AI architecture pattern that enhances large language models by connecting them to external knowledge sources. When a user asks a question, the system first retrieves relevant documents from a knowledge base, then uses that context to generate an accurate response. RAG solves the hallucination problem common in pure LLMs by grounding responses in verified information. This approach is widely used for enterprise chatbots, document Q&A systems, and customer support automation.