RAG vs Fine-Tuning – Agicent Technologies

Big language models (like ChatGPT, Gemini) are very smart. But they don’t know everything, and they don’t always stay up to date. That’s why people use two main tricks to make them better:

RAG (Retrieval-Augmented Generation) → like giving the model a library card. It can go read fresh documents before answering.
Fine-Tuning (FT) → like training the model in school. It learns a subject deeply, so it can answer in a certain way every time.
Why does this matter?

Businesses lose money if answers are wrong. (Example: a bank chatbot gave outdated rules to 30% of customers in a test).
In healthcare, a wrong answer could even harm a patient.
And in customer service, style matters. A polite, consistent tone can increase satisfaction by 20–30%.