RAG (Retrieval-Augmented Generation)
Definition
A technique where an AI tool looks up relevant information from a specific source — like a company's documents or a database — before generating its answer. Instead of relying solely on what it learned during training, it retrieves current, specific data first. This makes answers more accurate and grounded in real, up-to-date information.
Why It Matters
RAG is how companies make AI tools that can answer questions about their own products, policies, and data without fine-tuning the whole model.
What does that look like in practice?
A company help-desk AI looks up your actual order in its records before answering, rather than guessing from training alone.
What people actually mean when they say this
When a company says its AI 'knows our documents,' they usually mean RAG: it looks information up first, rather than being retrained on it.
Last reviewed: March 2026
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