Right now AI belongs to techbros, hobby geeks, and the companies renting it back to everyone else by the token. But what about you? You just want the thing to work, without anyone leeching your ideas or bleeding you dry every month. That's the whole ethos: radical about ownership, practical about everything else. No geekese required.
Every generation of computing asks the same question: do you own the machine, or does the machine own you? The AI industry answered early; rent it by the token, meter it, keep the off switch. We answer the other way.
When your AI runs in someone else's data centre, everything you do with it is a lease. The price can change under you, and it does. The model you built your workflow on can be killed off with a blog post. An outage on another continent takes your tools offline in the middle of your work. And every prompt, every document, every half-formed idea you feed it becomes inventory on somebody else's servers, governed by terms you didn't write and can't negotiate.
The cloud can change the price, retire the model, and read the room. Your GPU can't do any of that to you.
When the model runs on your own GPU, the economics and the politics flip. You already paid for the hardware, so everything you generate after that is effectively free: no meter ticking while you iterate, no rate limit deciding when you've created enough today. The model you like keeps running until you retire it, not until a vendor's roadmap does. Your files never leave the machine, so privacy isn't a policy you trust; it's physics you can verify. Unplug the router and everything still works.
This is not nostalgia for desktop software. It is the recognition that AI is the most personal tool ever built. It reads your documents, hears your voice, remembers your projects, teaches your children. A tool that intimate, rented, is a liability dressed as a convenience.
The same capability, two completely different deals.
Local-first is a default, not a religion. Sometimes you want a frontier model or a render your VRAM can't hold.
EveryWear applets can call API fallbacks for extra power on demand where the applet's registry gate is satisfied. The difference is the direction of control: the cloud is an overdrive you engage, not a landlord you depend on. You choose where inference runs: local GPU, a friend's node, a federated pool, or an API vendor. When the job is done, everything you made and everything you are comes home to your machine and your Vault.
Ask one question of any AI product: if the company behind it vanished tonight, would your setup still work tomorrow? With EveryWear the answer is yes. The OS is on your disk, the models are on your disk, your memory is on your disk. That's the whole point.
The old objection to local AI was real: it demanded a weekend of terminals, drivers, and YAML. Sovereignty came with homework, so only the geeks got it. We removed the homework.
The installer profiles your GPU on first boot and loads the highest-quality local stack your VRAM can handle. No model zoo spelunking, no quantisation homework.
No Docker, no pip, no CUDA version roulette. Every applet, model, and update arrives through one desktop, one click, with approval gates before anything big downloads.
Identity, memory, models, and output all live locally from the first boot. You don't graduate into sovereignty later; it's the starting position.
Own the machine. Own the model. Own the memory. It just works.