---
title: "RAG (Retrieval-Augmented Generation)"
date: 2025-11-04
author: "Anton \"JD\" Titov"
---

# RAG (Retrieval-Augmented Generation)

**Retrieval-Augmented Generation (RAG)** is a critical AI technique that anchors a **[Large Language Model (LLM)](https://stage.spiralscout.com/glossary/large-language-model)** to verifiable, external data, virtually eliminating guesswork and hallucinations. Instead of relying solely on its training data, the agent first retrieves relevant, up-to-date information from a secure knowledge base using [**Embeddings**](https://stage.spiralscout.com/glossary/embedding) and **[Semantic Search](https://stage.spiralscout.com/glossary/semantic-search)**, then uses that context to generate a precise, grounded answer.

Spiral Scout implements RAG to ensure all AI-driven tools provide trustworthy results based on the client’s most current and accurate data.