What is RAG?
A simple explanation of retrieval-augmented generation and why AI tools use it.
In simple terms
RAG is a way of helping AI answer with outside information instead of relying only on what it already knows.
Imagine an AI taking an open-book test instead of a memory-only test.
Before answering, it searches a trusted source like documents, notes, or a database.
Then it uses that information to build a better answer.
That usually makes the response more relevant and grounded.
Why it matters
RAG is one of the main ways businesses connect AI to internal knowledge, support content, and company documents.
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Common questions
What is RAG in simple terms?
RAG helps AI look up outside information before answering, instead of relying only on its internal knowledge.
Why does RAG matter?
RAG is one of the main ways companies make AI more useful, current, and grounded in real documents or data.
What should I learn after RAG?
The best next pages are MCP, AI agents, and vector databases.