Demand is 22% above the same week last year.
The engine behind
the answer.
Uriel reasons over a model of your business. It is what turns stored data into a decision you can act on.
This is what reasoning over a model looks like.
The answer is not a sentence about your data. It names the objects it was read from, and it waits before it changes any of them.
A manager asks a Discord channel where the business is losing money. Uriel answers with three figures, and the model beside it lights up the four objects the answer came from.
Nothing new to log into. Telegram and Discord, on the phone already in their hand.
Every write is previewed. It shows what it is about to do, then waits to be told.
Answers name their sources. Every figure carries the objects it was read from.
Two halves, one model.
In plain language, grounded in your own records — and it names the objects the answer came from.
It watches the model continuously and pushes what changed, before you thought to look.
It knows what your data means.
A chatbot on a database can search text. A model knows that a room has a rate, that a rate belongs to a channel, and that a channel takes a commission.
- Answers trace to their objects
- No hallucinated figures
- The same answer every time you ask
12 free next weekend — Deluxe sells out first.
How it reasons.
Not one table. A question about rooms can be answered with what it knows about revenue, because they are connected.
One review is an opinion. Two hundred are a signal. Patterns only appear when you count all of them.
Every answer lists the objects it used. A generic AI cannot say “Room 112 faces the main street”.
Room types, restrictions, permissions, who may see what. The model carries them, so the answers honour them.
See it answering real data.
The hotel demo runs on the same model Uriel reasons over.
Open the demo