We help organisations decide where AI fits and then make sure it works in people's daily work. Training is part of that. In the end you should be able to do it without us.
What we do
1
Department by department we look for where AI pays off, and we judge every idea the same way. Sometimes the answer is that an idea is not a good AI case. Then we say so.
Result: A short list with value, risk and an owner per use case.
2
With the management team we look at where AI speeds up, deepens or rethinks your strategic pillars, and where you stand now.
Result: A filled-in maturity picture per director and two or three activities with an owner.
3
Sessions and series for management teams and teams, built around the participants' own work and their own context in tools such as Copilot and Claude.
Result: People who have built something themselves, a workbook and a set of agents.
4
A guided track from inspiration to a build day, in which teams build an AI solution for a case from their own work.
Result: Working solutions and teams that can continue on their own.
What it looks like
After an intake we choose the modules that are most valuable for you, or make a new one. About half the time participants work themselves, with their own material and in their own tools.
An afternoon or morning for a management team or department. We learn and choose together.
Several sessions, with assignments in between in your own work.
One to one per person, with assignments in their own work. The first session starts with real work, not slides.
Hackathon
We run the preparation and walk along on the day itself. The use cases and the results are yours.
How AI changes work, the basics and what makes a good use case.
Each participant works out a use case.
A conversation per participant about the use case.
Participants sharpen their use case and present it to each other.
Everyone gets an assignment that fits their own use case.
Teams build together on their use case.
Judging
In every format we look at two layers. And there are four questions before you build: is the business case clear (time, quality or something that is not possible now), is it feasible, is it safe and allowed, and will people use it.
Repetitive and high volume, text intensive, or information that is spread out.
Personalisation, a skill bottleneck, or translation between kinds of expertise.
One step of the process, fully working, instead of the whole chain half done.
AI makes the current process faster. The question is whether that process still makes sense now that AI exists.
What participants train
Every module trains one or more skills, so it is clear what participants take away.
AI basics, the AI toolbox, and recognising processes that suit AI.
Thinking critically, patience, AI curiosity and responsible AI.
AI as chief of staff, sharper decisions, choosing opportunities by value, rethinking strategy and bringing people along.