A few years ago, we built an autonomous system that made decisions without us.
It ran continuously. It monitored markets, evaluated signals, executed trades, logged its reasoning, and handled its own edge cases. When it worked — and it usually worked — we didn't think about it at all. It was just running, quietly, doing exactly what we'd designed it to do.
That system taught us something we hadn't expected: the hard part isn't the AI. The hard part is everything around it.
Connecting to live data sources. Managing secrets without exposing them. Recovering gracefully when an API changes. Knowing when to act and when to wait. Logging what happened in a way you can actually reason about later. Building something you can trust to run when you're not watching.
Most people trying to set up an AI agent today are attempting to solve all of these problems at once, with no prior experience, guided by tutorials written by people who've never run anything in production. The results are predictable: things break, data leaks, the agent hallucinates, and the person gives up and goes back to doing it themselves.
We'd already solved these problems. Not perfectly — no one does — but well enough that we trusted the system with real money and real decisions.
When we looked at the consumer AI assistant space, we saw the same gap we'd seen in financial automation years earlier. Lots of demos. Lots of blog posts. Very few things you'd actually rely on.
The problem isn't intelligence. It's infrastructure.
The AI models are genuinely capable now. GPT, Claude, Gemini — pick one, they're all remarkable. The limiting factor isn't what the model can do; it's whether the system around it is solid enough to support it.
An AI agent without good infrastructure is like a skilled surgeon in a poorly equipped operating theatre. The competence is there. The conditions aren't.
What does good infrastructure look like?
It means the agent knows who you are and how you work — not because you've spent weeks configuring it, but because the setup process built that context correctly. It means your data is handled the way you'd expect: your conversations stay on your machine, your credentials are stored securely, and if the service ever goes offline, your agent keeps working. It means the agent has the right tools connected — email, calendar, the things that actually govern your day — not a generic API dump that makes everything technically possible and practically useless.
It means reliability. Predictability. Something that earns your trust by behaving consistently, over time, without drama.
That's what we mean by stomme. Frame. Structure. Foundation. The thing the building depends on.
Why we built it as a product
After a while, we realised we were essentially running a personal AI operation for ourselves — and that the gap between what we had and what was available commercially was large enough to matter.
Not because the commercial tools were bad. But because none of them were built from the assumption that the infrastructure problem was real and needed to be solved first.
Most AI assistant products are UX wrappers around a model API. Fast to build, easy to demo, genuinely useful for simple things. But they don't run locally. They don't give you control over your data. They don't keep working when the company's servers go down. And they don't come configured — you spend hours setting them up and still end up with something that doesn't quite do what you wanted.
We'd built the alternative, for ourselves, and it was better. So we decided to offer it.
What we believe
We believe the best AI assistant is one you trust — and trust has to be earned, structurally, not just claimed in a privacy policy.
We believe AI should make your day smaller, not bigger. The goal isn't to add another tool you have to manage. It's to reduce the surface area of things that need your attention.
We believe you shouldn't need an engineering background to have a capable AI agent. The complexity should be invisible. The result — a useful, reliable assistant — should be immediate.
We believe local-first is the right architecture for personal AI. Not because the cloud is evil, but because your agent should work the way you do: continuously, reliably, without a dependency on someone else's uptime.
And we believe that if you're going to charge for something, it needs to actually work. Not in a demo. In a real day, for a real person, doing real work.
Stomme AI is the product of having solved the infrastructure problem for ourselves, then making it available to everyone else. It's not an idea or a pitch — it's a system we built, use, and trust.
The founding offer exists because we want early customers to take the same bet we took: try it, judge it on results, and decide from there.
Your personal AI. On your Mac. Without the complexity.
Try Stomme AI — €22.50 your first month →