---
title: "RAG Search"
description: "Use RAG Search to query embedded knowledge in your workspace"
---

import Image from "next/image";

## What is RAG Search and how to use it?

RAG search allows the agent to check what are the things the agent already know about a specific topic (requires some data to be embedded in workspace)

You can use RAG search by asking the agent something like `@agent can you check what you already know about AnythingLLM?`

<Image
  src="/images/guides/ai-agents/rag-search.png"
  height={1080}
  width={1920}
  quality={100}
  alt="AnythingLLM AI Agents RAG Search"
/>

RAG search can update agent's own memory and that can be later used for recall in agent or regular chat. This embeds a virtual document you cannot manage.

Example: `Ah, great point. Can you summarize and save that summary for later to your memory`
