---
title: "Should I Use RAG or Fine-Tuning for a Customer-Support AI?"  
description: "Should I Use RAG or Fine-Tuning for a Customer-Support AI?"  
author: "Katherine Sullivan"  
published: 2026-10-21  
canonical: https://answers.mindstick.com/qa/117985/should-i-use-rag-or-fine-tuning-for-a-customer-support-ai  
category: "Mix Category"  
tags: ["artificial intelligence", "RAG", "fine-tuning", "Customer Support"]  
reading_time: 1 minute  

---

# Should I Use RAG or Fine-Tuning for a Customer-Support AI?

I’m planning a support assistant that needs to answer questions from our product manuals and policy pages. Those documents change every few weeks, and the answers should stay close to our support team’s tone.

Would [retrieval-augmented generation](https://answers.mindstick.com/qa/116675/what-is-retrieval-augmented-generation-rag-in-ai-applications) (RAG) or fine-tuning be a better starting point? I’m trying to understand the trade-offs in keeping information current, reducing incorrect answers, and maintaining the assistant over time. If you’ve built something similar, what did you choose and what made the biggest difference?


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Original Source: https://answers.mindstick.com/qa/117985/should-i-use-rag-or-fine-tuning-for-a-customer-support-ai

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