Fine-Tuning

Should I Choose RAG or Fine-Tuning for My AI System?

Choosing between RAG (Retrieval-Augmented Generation) and Fine-Tuning is one of the most important architectural decisions for any modern AI system. RAG enhances a model by fetching up-to-date, domain-specific information at query time, making it ideal for knowledge-heavy tasks, dynamic content, and systems that require accuracy without modifying the core model. Fine-tuning, on the other hand, customizes the model itself—embedding new patterns, tone, or domain expertise directly into its parameters for more consistent behavior and specialized capabilities.