We build software — and measure how reliable it is before you put it into service.

Most people can build the system. The hard part is knowing how often it gets things wrong, before it is running in your organisation.

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How we build

Systems and integrations

The things that have to work day to day: workflows, data between systems, self-service.

AI features behind a gate

High-consequence decisions go to a human — no matter how confident the model sounds.

Measurement before go-live

We measure how often the gate routes wrongly, and we state the number. Including when it does not look good.

Documentation

The pack your auditor and AI Act owner need — not a reconstruction after the fact.

The question is not whether the system can. It is how often it gets it wrong — and what happens when it does.

We develop AI-assisted, and it makes the work faster. But that is not the reason to choose us. The difference is that we measure the reliability and write the number down, before you put the system into service.

The method is the same as in AI & compliance: the consequence of a decision determines whether it may be made automatically. Routine cases go through; the heavy ones land with a human.

Building something that has to stand up to scrutiny?

We start by agreeing what “reliable enough” means for your task — and how it gets measured.

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