# Retrieval Augmented Generation (RAG)

Retrieval-augmented generation, or RAG, is a method where an AI system retrieves relevant information before generating a response or taking an action.

## Why it matters

RAG can make AI more useful with company-specific knowledge without requiring a model to be retrained. It is especially helpful when the source material changes often, such as policies, project status, or product documentation.

## Example

When asked about a customer’s contract terms, an AI retrieves the current signed agreement and uses it to prepare a response.

## FAQ

### What is Retrieval Augmented Generation (RAG) in simple terms?

Retrieval-augmented generation, or RAG, is a method where an AI system retrieves relevant information before generating a response or taking an action.

### Why does Retrieval Augmented Generation (RAG) matter for teams using AI?

RAG can make AI more useful with company-specific knowledge without requiring a model to be retrained. It is especially helpful when the source material changes often, such as policies, project status, or product documentation.

### What is a practical example of Retrieval Augmented Generation (RAG)?

When asked about a customer’s contract terms, an AI retrieves the current signed agreement and uses it to prepare a response.


Source: https://www.luffy.so/ai-glossary/retrieval-augmented-generation-rag

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