About me
I lead data and AI projects at SWICA, one of Switzerland's largest health insurers. My job sounds technical. Mostly, it is not. The models and platforms are the easy part. The hard part is getting a large organization to change how it works so the technology actually pays off. That is the problem I work on.
What that means in a regulated industry:
Shipping AI at a health insurer includes the unglamorous parts: data protection, governance, and making sure a system still deserves trust six months after launch. The demo is not the finish line. Adoption is.
I came to IT through the side door. I trained as a mechanical design engineer and spent my early career around physical things: turbomachinery, exhibition booths, loading cranes. Physical engineering teaches a discipline software sometimes forgets. When a part does not fit, nobody argues about definitions. Something works or it does not. I still hold digital projects to that standard.
Where that discipline comes from:
MAN Diesel & Turbo in Zurich, today Everllence. A four-year apprenticeship building components for machines that run for decades. It is where I learned that quality is not a review meeting. It is a habit.
Then I switched sides. I studied computer science at FHNW, and in 2020 I co-founded TEQLY, a company focused on digitalization for Swiss small and medium enterprises. A startup serving SMEs is an honest school. The budget is the owner's own money, the users sit next door, and adoption is not a KPI on a dashboard. It is whether the office manager still uses your tool in March. I learned more about change management there than any framework has taught me since.
What founding teaches you:
Everything, once: sales, delivery, pricing, support. It permanently changes how you read a business case, and it is why I never confuse a rollout plan with actual adoption.
Today I bring those threads together at SWICA, sharpened since 2025 by the Swiss International MBA at FHNW. The point of the combination is simple: I can sit in the architecture review in the morning and the steering committee in the afternoon, and say the same thing in both rooms. Just in different words.
What I offer, in plain words:
I build data strategies that start from the business problem, not the technology.
Most data strategies are shopping lists: tools, platforms, a governance framework. Mine start at the other end. Which decision should get better, and what does it cost that it currently isn't? The architecture follows from the answer. Not the other way around.
I lead AI projects end to end.
From the first use-case discussion to the moment a team relies on the result in daily work. Shaping the case, building the team, managing delivery, and staying until it sticks.
I manage the change that comes with it.
Because a system nobody uses is just expensive infrastructure. New tools mean new roles, new habits, and sometimes uncomfortable conversations. That part cannot be delegated to a newsletter.
This blog is where I think in public about IT strategy, data, AI, and change management. Written for engineers and leaders in Swiss enterprises. Skeptical of hype. Not cynical about progress.
Sounds like a conversation worth having?
Find me on LinkedIn or write me a mail!
