About

Make enterprise data easier to question — and easier to trust.

DataFact helps teams ask questions across documents and databases and get answers they can trace back to the source. We believe AI should not hide how an answer was produced. The data, query, document, page, and reasoning behind an answer should remain visible — especially when that answer is used to make a business decision. That is what DataFact is built for.

What we believe

Four positions that shaped the product

These are opinions, and they cost us features that demo well. We think they are why deployments stay in production.

Retrieval is an engineering problem, not a prompt

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.

An answer without provenance is a liability

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.

The data should not have to move

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.

Governance decides whether a rollout survives

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

Built on production systems, not a research demo

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

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General enquirieshello@datafact.ai
Partnershipshello@datafact.ai

Start here

Bring us a question your team actually cares about.

Connect a document and a database, ask the question, and inspect the supporting material the workflow returns.

Try demo See how it works

Source visibility depends on the connected resources and workflow.