AI systems for large organisations

Rarely inside one department. An incoming order touches sales, planning and administration, and between those three sit emails, exports and spreadsheets nobody would design as a system but which are there every day. That is where the time goes.

We automate one handover between departments. We build it as code on the systems already in place, and it runs alongside the existing process first, until you can check that it gives the same answer as the people doing it today.

Where possible it runs in your own environment and your own accounts, with access limited to what that one workflow needs. We sign an NDA and a data processing agreement, and we do not train public models on your data.

What the system does can be read back per run: what came in, which steps it took and what went out. That log is what an audit, an administrator and a sceptical colleague all three need.

A working first version for one agreed task, using your real data. You check it in a separate environment before the software goes live.

Then you decide whether the first version goes live and which process we tackle next. We keep maintaining the code and adjust it when the work changes.

Anything that goes out or moves money is approved by a person. The system proposes, a person signs. When the model is unsure about what it sees, it says so rather than offering a guess as an answer.

That is also why a pilot here rarely fails on the technology. It fails on work nobody can check any more. So the first version is small enough to verify by hand.