Teams often assume they need to fine-tune a model. Usually they need retrieval-augmented generation (RAG) instead — or first. Here's how to tell them apart.
The difference
RAG gives a model access to your current knowledge at query time. Fine-tuning changes the model's behaviour and style by training it on examples. They solve different problems.
Which to use
- Need answers grounded in your data? RAG
- Need a specific tone or format? Fine-tuning
- Most business use cases start with RAG and add tuning only if needed
We design AI systems that use each technique where it actually helps.
DO
David Okafor
VP, Digital Transformation
Part of the TechWorld Solutions team helping enterprises migrate, modernize, and secure their technology.