New whitepaperNext-Generation NI: A Vision, Philosophy, and Technical Path for Continual LearningRead now

They said weights are frozen. We made them grow with you.

AI Models That Grow for You. On Your Device.

Continual learning happens on your device: the model grows with use, remembers across sessions, and your data never leaves.

We don't sell tokens. We set them free.

How it works

Neural Imprint

Memory, learning, ownership — the brain of embodied AI lives in the device, not in someone else's cloud.

01

Generate

The devices around you generate data continuously — some from what you do, some from what they sense.

02

Learn

The device locally understands your patterns, forming a cognition of who you are.

03

Evolve

That cognition is imprinted into the model's internal state — no weight edits, no fine-tuning, no cloud.

Your data physically never leaves your device.

Why it's different

Learning without touching the weights.

Not fine-tuning. Not RAG. A recoverable learning state that travels with the model — on whatever runs it.

Weights stay frozen

Learning is captured as a compact inference state — never a gradient step.

Persists · reverts · verifies

It survives sessions and restarts, is gated before activation, and rolls back in one step.

Any model, any chip

It lives at the inference-state level, so it isn't tied to a model family or a processor.

Validated end to end on consumer hardware.

Evidence and boundaries

Build with us

We're looking for researchers and engineers who want to push the boundaries of on-device AI.