I noticed NewRelic has a chat feature that does this sort of thing, it's scoped very narrowly down to their website and analytics DSL language, and generates charts/data from their db. I've always wondered how they did that (specifically in terms of set up the training/RAG + guardrails). It's super useful.
The most likely way of building that would be to equip it with a "search_docs" tool that lets it look up relevant information for your query. No need to train an extra model at all if you do that.
Those other ways to integrate the texts might be some form of RAG or other ideas like Apple's recent 'hierarchical memories' (https://arxiv.org/abs/2510.02375).