RAG (retrieval-augmented generation)
RAG is the technique where an AI model first looks up the relevant passages in your own documents and answers with those, so the answer is based on your information and has a source.
A language model on its own does not know your price list, manuals or delivery terms. With RAG those documents are cut into pieces in advance and made searchable. On a question, the system retrieves the matching pieces and hands them to the model, which then answers based on exactly that text.
The result: answers that match your sources, with a reference to the document. That is the basis of every reliable knowledge base or customer service agent, and the main remedy against hallucinations.
Other terms
Vector database
A vector database stores text as series of numbers that capture its meaning, so you can search for "what resembles this" instead of only exact words.
MCP (Model Context Protocol)
MCP is an open standard through which AI models and agents access tools and data sources in a uniform way, so an integration is built once and usable by any agent.
Hallucination
A hallucination is an answer from an AI model that sounds convincing but is wrong: an invented price, a non-existent product, a date based on nothing.
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