Fine-tuning
Fine-tuning is additional training of an existing AI model on your own examples, so it masters a specific style or task better. For most companies it is unnecessary: a good prompt plus your own data (RAG) gets further.
Fine-tuning changes the model itself. That takes examples (hundreds to thousands), time and money, and the result goes stale as soon as your process changes. It pays off for very specific tasks with a fixed form, such as classifying documents into your own categories.
If you want a model to use your knowledge, RAG is almost always the better route: the knowledge stays in your documents, can be updated instantly and you keep a source with every answer.
Other terms
Token
A token is the piece of text (roughly part of a word) an AI model counts in. It determines the price of every request and how much text a model can process at once.
RPA (robotic process automation)
RPA is software that imitates human clicks and keystrokes on screens to repeat a fixed task. It works as long as the screen does not change and understands nothing of the content.
Workflow automation
Workflow automation lets fixed steps between systems run automatically: when an order comes in, the invoice is created, the confirmation goes out and stock is updated, without anyone clicking.
Want to know what this means for your business?
Tell us where you lose time or margin. We show where AI pays back fastest, in plain language.