LLM is not so magic.
Injecting a model schema with data into the AI engine won’t likely lead to accurate results, first of all you will likely go way over the context window of the engine and second of all your datamodel database and fields name will have to very descriptive so the AI engine understand what it is.
As always, instead of expecting magic, I would define the use-cases: what are the most basics data the customer will ask for? You will then have “primitives” data the user may ask single or compound queries on.
Then define functions/tools call to feed those data into the AI engine upon customer requests.
The AI engine will figure out what to call and when depending on the user query.