The world's leading AI models are American — GPT, Gemini, Claude. They are built for the American market. Europe is different: different rules, a different culture, a different way of thinking about data. That is why strong AI products often fail here. It is not a technical problem, so it is not something your engineering team can build.
I am the European context layer for your AI product — the rules, the culture, and the trust that decide whether Europe adopts it. The gap is the same whether you are a US company entering Europe or a European company building on an American model. I help you see it and close it, before you invest.
What "AI product" means here
Most companies don't build their own models. They build software on top of one — GPT from OpenAI, Gemini from Google, Claude from Anthropic. The model is the intelligence; the product is what you sell. That works well in the US.
But the moment your product sends a European user's data to that model, you inherit a set of European questions the model was never built to answer: Where does the data go? What is kept? Could a foreign law reach it? And may the model act on its own?
Those questions are now your product's responsibility — not the model maker's. And the answers decide whether Europe trusts your product and adopts it, or quietly turns away.
This is not only an American company's problem. A European company building on GPT or Claude faces the same questions — because the gap lives in the model's origin, not the company's address. Europe runs on artificial intelligence it did not build, almost all of it American. That dependence is not going away, and the tension it creates with European rules and values has to be mediated — not wished away, and not solved by simply switching to a European model, which still leaves you with GDPR. Mediating that tension is my work.
The European context layer for AI products
I help companies fit their American-AI product to Europe. The rules, the culture, and the trust that decide whether Europe adopts an AI product — built into the product itself, so it feels made for this market. US companies entering Europe, and European companies building on American models alike.
I work only with AI — AI products and AI models. That is where I have spent my time, and it is the one place the European gap is widest.
To be clear about what I am not:
Not a market-entry firm. I don't do tax, legal paperwork, logistics or office setup.
Not a sales hire. I won't run your pipeline or build your sales team.
Four ways I help
On their own, or together. Preferred working model: Claude Opus by Anthropic.
Europe Readiness Assessment
A clear read on where your AI product — and the way you present it — will meet friction in Europe: data, autonomous agents, trust and culture. You learn what to change first, before you invest.
European Context Layer
Put the European context your product is missing into the product itself — the rules, the data worldview, the local conventions — so it feels made for Europe, because it is.
Collaborative AI Product Design
Design the product for Europe: a human in the loop instead of autonomous agents, data kept in Europe, anonymisation, and a clear line on what the model may and may not process.
Communication & Content
How to talk to European users and buyers — the tone, the conventions, the trust signals — and clear content and essays that build understanding and presence in the market.
Is your AI product ready for Europe?
Ten open questions to sit with before you invest — across data, trust, autonomy, and the way Europe buys. There is no score. The ones that give you pause are the ones worth a conversation. A few of them:
- When a European asks "on what legal basis are you processing this data?" — do you have an answer beyond "we're encrypted and SOC 2"?
- Could a US law reach your users' data even if it sits in Frankfurt?
- Is your product built around an agent that acts on its own — or a human who stays in control?
- Which "Europe" do you mean? Germany, France and the Nordics buy and trust differently.
Why AI agents don't work in Europe
The US AI story in 2026 is all about agents — systems that act on their own: they read your emails, work inside your systems, replace human steps. In Europe this hits a wall, both legal and cultural. An agent that processes other people's personal data runs straight into European data law, and people here do not trust systems that act without human control.
What works here keeps a human in the loop: the model suggests, drafts and analyses; the person checks and approves. The term is augmentation — making human thinking stronger, not replacing it. For an AI product coming to Europe, that is a design choice — and it is the one that earns trust.
Philipp Moser
The European context layer for AI products. I trained as a social scientist and spent years in political and economic consulting. For a good while now my focus has been large language models — how they work, and how people really use them.
That mix is the point. The European gap is not technical. It is about rules, culture, data, politics and public debate — read together. Reading context closely and explaining it clearly is what the social sciences train, and it is what an engineering team cannot supply from the inside.
I also think in the open. The essays on this site are some of the clearest writing available on why AI products struggle in Europe and what to do about it. That thinking is the work — and the best way to see how I would approach your product.
Visual essays
I think in the open. Each piece is made through Collaborative AI — one human, one model, a growing context in dialogue. They are the clearest way to see how I work and how I think about the European context for AI.
- American intelligence, European rules — how to actually use American AI in Europe
- What is European Context Engineering? — the discipline of fitting American AI to Europe
- Do AI agents work in Europe? Why autonomy hits a wall
- Shadow AI: why everyone in Europe uses American AI in secret — and how to do it openly
- Why US-style sales emails fail in Europe
- Europe Readiness Check — ten open questions before you ship to Europe
- AI with the handbrake on — why Germany ignores the world's best AI ecosystem (DE)
- Generative. Agentic. Collaborative. — the missing third category of the AI debate (DE)
- Do AI agents make sense? What independent systems really cost (DE)
- Augmentation, not automation — why the most threatened jobs have the most to gain (DE)
Bringing an AI product to Europe and want a clear picture before you invest? Write me — the first call is free, with no obligation.
Collaborative AI: one human, one model, a growing context. Natural language as the means of production. Judgement as the quality filter.