RAG vs Fine-Tuning: Choosing the Right AI Architecture for Your Business

Retrieval-Augmented Generation (RAG) and fine-tuning solve different problems. Understanding when to use each — and when to combine them — is one of the most consequential technical decisions in enterprise AI deployment. When to use RAG RAG is perfect for knowledge-intensive tasks where the AI needs access to up-to-date, highly specific internal documents without retraining the entire model. When to Fine-Tune Fine-tuning is better when you need the model to learn a specific tone, style, or highly complex domain-specific reasoning patterns that can't fit into a prompt.