On sovereign AI
The model should run where the data lives.
Every cloud AI product is built on the same assumption: that your data is safe enough to send to someone else's server. We disagree.
We build AI agents and applications that run entirely on hardware you control. The inference happens inside your infrastructure boundary. There are no outbound API calls. We are not in a position to see what you do with our software, and we have designed it that way intentionally.
On a Mac
Native Apple Silicon apps. Runs on the Neural Engine.
On your servers
On-premise deployments. Your hardware, your network.
In your cloud
Agents in your AWS, GCP, or Azure account.
Technical facts
Why we built this
The tools that handle sensitive work should not phone home.
We wanted AI we could use for client documents, legal work, financial records, private correspondence. The kind of work where you cannot ethically or legally send the contents to a third-party server.
The hardware to do this well now exists. Modern chips run large models at speeds that match cloud APIs. The software layer was missing. We are building it.
How it works
The model runs inside your boundary and stays there.
Whether you are running one of our Mac applications or deploying an agent into your own infrastructure, the inference happens on hardware you control. The model weights load once, locally. After that, every request is local too.
There is no request going out to an API. No text is processed on a third-party server. That is not a privacy policy claim. It is an architectural fact.
What we believe
For a large class of real work, sending data to a cloud AI is simply not acceptable. Compliance requirements, client confidentiality, national security considerations, personal privacy. The answer is not better privacy policies. It is different architecture.
Modern hardware runs large language models at speeds that compete with cloud APIs. The performance argument for sending data off-device no longer holds. You can have both speed and sovereignty. We build for that reality.
A subscription model puts the company's incentives in tension with the user's. We prefer the older arrangement: build something genuinely useful, charge a fair price, stand behind it. Our Mac apps are one-time purchases. Custom deployments are scoped projects.