What becomes possible
When intelligence is cheap, auditable, and small enough to run on the device itself, it stops living in the cloud and starts living in the world. Here's where we think that leads. It's a direction, not a catalogue of shipped products.
Medical devices that adapt
Reasoning small enough to run on an implant's microcontroller, and auditable enough to trust, points toward devices that adjust intelligently on their own: a hearing aid that keeps tuning itself so you always hear as well as you can, or a pacemaker whose timing is optimised on-device to the person wearing it. These are illustrations of a direction, not products or medical claims — but they're the kind of thing on-device, inspectable intelligence is for.
Non-intrusive medical & wearables
The same properties — a tiny power budget, no cloud round-trip, decisions you can verify — suit non-invasive monitors and everyday wearables: sensing, interpreting, and responding locally and privately, without shipping your body's data to someone else's server to be billed by the query.
Robotics across many terrains
The reasoning compiles to a portable instruction set, so the same programs run from a microcontroller up to a full GPU. That makes it a fit for robotics that has to work across many terrains and bodies, programmable in CubeLang rather than retrained from scratch for each platform.
Factory QA / QC
Inspection and quality control that reasons on the line, on modest hardware, with decisions an engineer can actually audit — not a black box that flags a defect it can't explain. Cheap enough to run everywhere on the floor, not just where a cloud budget reaches.
For the person at the end
When running an agent costs a fraction of what renting one by the token does, the arithmetic of who-gets-AI changes. Everything today's assistants do, and more — but run many agents at once, at a small fraction of the per-use cost. Intelligence you own and run, rather than meter.
These are directions the architecture opens, not a product line we're announcing. We describe what ownable, efficient, on-device intelligence makes possible, and we'll make specific claims only where we can show the work. The medical examples illustrate capability; they are not clinical or regulatory claims.