About
The interesting demos were solved a while ago. What is still unsolved is making an answer verifiable, permission-correct and reproducible inside a company that has twenty years of documents and a warehouse nobody fully understands.
What we believe
These are opinions, and they cost us features that demo well. We think they are why deployments stay in production.
01
Most failures we see are not model failures. They are a merged cell that became the wrong number, a chunk boundary that cut a table in half, or a permission that was asked of the model instead of enforced by the system. We spend our effort there.
02
If a person cannot check where a number came from, they will either re-derive it by hand or stop using the tool. Both outcomes waste the investment. Provenance is not a feature we added; it is the reason the architecture looks the way it does.
03
Every migration is a project that competes with the thing you actually wanted. We connect to the warehouse and the document store you already run — whether you subscribe or install the platform in your own network. Where the software sits is your call; what it reads stays where it is.
04
A pilot with five friendly users proves nothing about four hundred people with different entitlements. Scope, data roles and audit are in the product from the start because retrofitting them is how internal AI programmes die.
Where we come from
DataFact grew out of platform work already running inside large manufacturers, operators and resource groups — the kind of environments where the answer has to be right, the network has no way out, and the auditor arrives on schedule.
That is an unglamorous place to build a product, and it is the reason the parsing, the permission model and the audit trail are as specific as they are.
Get in touch
Send us one report and one table you care about. We will run them on DataFact and walk you through every source behind the answer.
SaaS subscription or private deployment · No data migration either way