Can I train an AI on my own documents?
You almost certainly want retrieval, not training. The model stays as it is, and at question time the system searches your documents and puts the relevant passages in front of it. Updating your knowledge is then a file upload rather than a retraining run.
How it actually works
“Train the AI on my documents” is how everyone says it, and it describes something people rarely want. Fine-tuning adjusts a model's weights, costs real money per run, needs redoing whenever your content changes, and is poorly suited to teaching facts — it is much better at teaching style and format. It also bakes your content into weights, which raises questions about where that content now lives.
Retrieval-augmented generation does the thing people actually mean. Documents are split into passages and indexed. A question triggers a search, the best passages are supplied as context, and the model answers from them. Change a price and re-upload, and the next answer is correct immediately.
It also makes citation possible at all. Because the system knows which passages produced an answer, it can name them. A fine-tuned model cannot tell you where something came from, because by then there is no “where”.
What it can't do
- Retrieval finds passages, so it is strongest at questions a passage answers. Questions requiring you to synthesise across a whole document set are harder.
- Your text is processed by a third-party model provider at question time. RegenticFlow uses OpenAI under a no-training arrangement, and does not run its own model.
- RegenticFlow never fine-tunes a shared model on your content. There is no fine-tuning path in the codebase at all.
Related
See it on your own documents
One public assistant page and 100 customer messages a month, free, with no card required.