AI strategy · Adoption · Return
We help organisations choose the AI worth doing, prove it with a working prototype, and get their teams actually using it. Every recommendation carries the economics behind it.
Why AI programmes stall
Most stalled AI programmes share a post-mortem: a pilot that worked, a business case nobody could defend, and teams who were never brought along. The model was fine. The roadmap, the ownership and the change plan were missing.
We start from the other end - the use cases that pay for themselves, sequenced into a roadmap someone owns, with the training and change work that makes them stick.
Before enthusiasm
We model the economics before anyone commits budget. If the number does not work, we say so - a cheaper outcome than discovering it in year two.
What we do
Which AI is worth doing, in what order, owned by whom - and what it returns.
The work that decides whether anyone actually uses what was built.
A working prototype in weeks, with an evaluation report and an honest verdict on whether to continue.
Where genuinely novel work can be part-funded - and when a call is not worth entering.
Turning research results and prototypes into something with a price, a market and a margin.
Proposals, deliverables and architecture documents written by people who could also build the thing.
Where to start
Six ways in, each with a defined deliverable and an end date. Larger engagements usually begin as one of these.
2–3 weeks
A scored view of where you actually stand across data, technology, people and governance - and the shortest path to the first result worth having.
2 weeks
What the initiative costs to run at your volumes, what it returns, when it pays back, and what would have to be true for that to hold.
Monthly
A Chief AI Officer on retainer. Architecture decisions, vendor selection, hiring input and roadmap ownership, without the executive hire.
4–8 weeks
Role-based training for executives, managers, engineers and analysts, plus the champions and policy needed to make it hold after we leave.
4 weeks
A working prototype against your real data, an evaluation report, and an honest recommendation on whether to continue.
3–5 days
A direct verdict on one specific call: your realistic win probability, what is missing from your position, and what entering would cost you.
An unusual advantage
Where the work is genuinely novel, it can be routed through Horizon Europe, the EIC or national programmes so that R&D budget carries part of the cost - and the prototype that proves the concept becomes the evidence in the proposal.
We write those proposals ourselves. It is not a referral to a partner, and it is not a bolt-on: the people who scope the architecture write the work packages.
Insights
Funding landscape
Practitioners say grants got harder to win and blame AI-polished proposals. Call-level data from 1,332 topics points elsewhere: submissions rose 41%, grants stayed flat - competition, not better proposals, raised the bar.
24 August 2026 · 33 min
Innovation economics
A European operator's guide: eight gates, the numbers behind each, and how to tell a real AI case from an expensive one
23 August 2026 · 16 min
Innovation economics
Most AI business cases are built backwards, from a solution that already has a champion. Here is the version that survives a second budget cycle.
4 August 2026 · 4 min
Next step
A first conversation costs nothing and usually ends with a straight answer about whether we are the right people for it.
