The question "where can AI help us?" gives you either an endless list or a frozen "I don't know". In half a day your management team weighs your own processes and chooses where to start with confidence.
From healthcare to SMEs — we make AI practical and measurable.
A list without an order never gets done. Standing still is the real cost.
The question "where can AI help us?" gives too many options or none at all. Both lead to standing still.
Without a way to compare processes, every proposal feels equally logical. So the choice keeps stalling.
Begin with a high-risk process or messy data, and AI moves the wrong way even faster.
You want to tackle everything, so no single project actually lands. No quick win, no proof, no budget.
Concrete numbers from our clients
AI-driven lead capture with email and WhatsApp automation, connected to CRM.
AI-driven intake module for vehicle photos. Automatic appraisal and faster processing.
Chat-driven AI assistant for the homeless. 8 aid organizations bundled into one access point.
We weigh together on impact and feasibility, in half a day
We put your team's work in view. Not a theoretical model, but your own processes.
What does it deliver if AI steps in here? Time, quality, calm in the team. We make it concrete.
How easy is this to build, really? Data, risk, and complexity decide whether it is a quick win.
At the top sit the processes that pay off quickly and prove the case for the next step.
5 professionals from Groningen
AI Strategy & Business Optimization
AI Implementation & Innovation
AI Engineer
AI Engineer
AI Engineer
A process is a good fit for AI when it recurs often, costs time now, runs on information you already have, and a small mistake is not a disaster. In the workshop you recognise these traits in your own work and turn them into concrete candidates.
Processes with high risk, sensitive decisions, or messy data are less suitable for a first step. That is where AI moves the wrong way faster. We name what to leave for now, so you start where the win is safe.
You weigh each process on impact and feasibility. That surfaces the quick wins: work that pays off quickly and proves the case for the next step. You leave with a shortlist of two or three processes.
No. You start with processes that run on information you already have. A big data project up front is not needed. We deliberately pick work where the data is good enough to start.
Half a day · in-company on location or at And AI
