ArizeFlow AI
Not a chatbot bolted to a help page. It investigates the project's own BOQ, WBS, schedule, procurement, inventory and daily records — and shows which queries produced the answer.
The ones that currently cost three phone calls.
Each of these has an answer already — spread across four modules. The assistant's job is not to be clever; it is to go and look.
Checked
- Bill of quantities16 items
- Purchase orders3 orders
- Store ledger10 movements
- Schedule2 activities
The frame needs 8,200 bags. 2,400 were ordered on PO-0037 and 2,388 entered stock — twelve were damaged in transit. Of those, 1,750 are issued, leaving 638 on hand.
The 6th floor slab is scheduled in 11 days and needs about 900. The shortfall is real.
Logged · vineeth@ · 2.4s · gpt-5.4-mini
What it will not do matters as much as what it will.
An assistant with access to a company's costs has to be explicit about its limits, and enforce them somewhere other than the prompt.
It reads your data, not the internet
Retrieval runs against the one project the user has open — capped per call and per question, and never another company's rows.
It shows its working
The retrieval functions it ran are displayed with the answer, so it can be checked rather than believed.
Every turn is logged
Who asked, on which project, what was asked, which functions ran and what came back.
It never sees credentials
The browser talks to the app; the app holds the key. Nothing sensitive is part of what is sent.
Bring your own model
OpenAI, Gemini, or a local model on your own hardware. Configure more than one and the rest become fallbacks.
It degrades honestly
With no model configured the panel falls back to the rule engine rather than guessing.
Bring the question your last project meeting could not settle. That is the demo.
Build smarter.Execute faster.Deliver better.