01
Audit
Map how your organisation actually works — front and back office — and find the most promising case. Whether AI is scattered (anarchy) or barely present (greenfield), we start from the ground truth.
Method
Optimisation is the goal, AI is the vector — applied with method, not in silos.
The principle
AI lasts when each capability feeds the others instead of piling up tool by tool. We do not set structure against automation — we apply AI as the vector of a coherent architecture.
It is exactly how we built Artmetria itself: a non-technical founder, using AI as the vector of optimisation, one capability nourishing the next. That is the shift we bring to your organisation.
Where we start
AI anarchy
AI is already in the organisation — individual subscriptions, duplicated costs from one team to the next, results nobody shares.
Greenfield
An isolated, token use at best, with no strategic intent behind it. A profile at least as common as the first.
How an engagement runs
01
Map how your organisation actually works — front and back office — and find the most promising case. Whether AI is scattered (anarchy) or barely present (greenfield), we start from the ground truth.
02
Build a first AI capability that works, however modestly — the proof that it is possible before deciding to go further.
03
Build one or more capabilities and put them into service, connected to your real data and workflows.
04
Train your teams to operate and adjust the capabilities themselves — so they keep running after we leave.
Three depths
A full audit and a first working prototype, built on your most promising case.
~€7k
One or two AI capabilities built and put into service with your teams, trained to keep them running.
~€45k
The same approach at the scale of the entire organisation, front and back office, over several months.
~€130k