Glossary · Building
abbreviation/rag/also: Retrieval-augmented generation
A technique where relevant information is looked up from your own documents or data and given to the model with the question, so answers are grounded in your sources.
In practice
RAG, or retrieval-augmented generation, is how AI answers questions from your own information rather than general knowledge. Relevant passages are found in your documents or data and given to the model with the question, so the answer is grounded in your sources and can cite them. It is the usual approach behind internal knowledge assistants and customer-facing tools built on company content.
RAG looks up your information at the moment a question is asked and gives it to the model, so it stays current and can cite sources. Fine-tuning changes the model itself through further training. For business knowledge, RAG is usually the better fit.
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