Evaluating RAG vs Fine-Tuning
Two of the most powerful techniques for making LLMs work on private data — but choosing the wrong one wastes time and money. Here is how we decide.
Retrieval-Augmented Generation (RAG) is excellent for dynamic external knowledge integration, while Fine-Tuning is the best fit for specialized style adaptation and core task alignment.