09/03/2026
A lot of businesses ask how to train an LLM on their company documents.
In most cases, you don’t actually retrain the model.
The practical approach is to:
- break documents into smaller chunks
- convert those chunks into embeddings
- store them in a vector database
- retrieve the most relevant context when a question is asked
The model then generates answers using that retrieved information.
This approach is faster, far cheaper than fine-tuning, and much easier to maintain when documents change.
When done properly, the AI stops guessing and starts answering based on the company’s real data.
This is how most production AI systems are built today.