What is RAG (Retrieval-Augmented Generation)? Simple Explanation (2026)
AI Glossary
What is RAG (Retrieval-Augmented Generation)?
Definition: RAG is a technique that enhances AI responses by first retrieving relevant information from a knowledge base, then using that information to generate more accurate answers. It reduces hallucinations and provides up-to-date information.
How Does RAG Work?
RAG systems work in two steps: 1) Retrieve relevant documents from a database using semantic search, 2) Feed those documents to the LLM as context for generating the answer. This grounds the AI’s responses in actual data rather than just training data.
Examples
Perplexity AI (web search RAG), custom chatbots with company knowledge bases, enterprise search tools
Related Reading
Learn more about how RAG is used in practice:
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