I’m confused about when I should use Retrieval-Augmented Generation (RAG) versus when I should actually fine-tune a model on my data. If I have a large database of proprietary technical manuals, is it better to feed them into a vector database for RAG, or will the model perform better if I retrain it on that specific vocabulary? I’m looking for the most cost-effective and accurate way to build a technical assistant.
3 answers
For most business use cases involving internal documents, RAG is the superior choice. Fine-tuning is like teaching a student for an exam months in advance—the model learns the "style" and "vocabulary" but can easily hallucinate facts or forget details over time. RAG is like giving that student an open-book exam; the model retrieves the exact text from your manuals and uses it to generate the answer. RAG is cheaper, easier to update (you just add a new PDF to the database), and provides "citations" so the user can verify the answer. Fine-tuning should only be used if you need the model to learn a very specific format or a highly specialized jargon that it doesn't already understand.
How often does your technical documentation change? If you have daily or weekly updates, fine-tuning would be a nightmare to maintain compared to a simple RAG pipeline.
RAG is generally better for "knowledge," but fine-tuning is better for "behavior." Use RAG to give the model the facts and fine-tune it to follow your company’s brand voice.
That’s a perfect distinction, Linda. Combining both—using RAG for the data and a lightly fine-tuned model for the tone—is the ultimate pro strategy for high-end bots.
Richard, our manuals change every time there is a software patch, so probably every two weeks. Based on Nancy's "open-book exam" analogy, RAG sounds like the only logical way to go. If I fine-tuned every two weeks, the compute costs would be insane. I'm curious though, does RAG have a limit on how much data it can search through efficiently before the retrieval process starts to slow down significantly for the end-user?