Fine-tuning vs. RAG: A Cost-Benefit Framework

Two common questions show up within the first month of any serious AI initiative. Should we fine-tune a model on our data? Should we build a retrieval system on top of a general model instead? The two approaches solve overlapping problems, cost very different amounts, and require very different operational discipline. Teams that pick wrong usually do not find out for six to twelve months. This post is the cost-benefit frame we walk clients through when the decision is still open. What each appro