RAG vs Fine-Tuning agicent.com

Retrieval-Augmented Generation (RAG) and Fine-Tuning are two powerful methods to make AI models smarter — but they serve different purposes. While RAG enhances large language models by pulling real-time, relevant data from external sources, Fine-Tuning customizes a model’s behavior by training it on domain-specific data. RAG offers flexibility and up-to-date accuracy, whereas Fine-Tuning delivers precision for specialized tasks. Choosing between them depends on your goals, data needs, and scalability. Discover how Agicent helps businesses leverage both techniques effectively.