AI, Unplugged.
Compute has outgrown the wire.
The single largest limit on AI economics isn't the complexity of the math—it's the physics of moving data. Shuttling bits between storage and central GPU clusters consumes 90% of a chip's energy budget.
Sibacus licenses the Compute-in-Memory architecture that stops the movement. We build the compute brain directly inside the memory cells, freeing AI from the cloud, the cooling fan, and the grid.
Processing happens directly inside RRAM conductance states. By computing at the physical location of the data, we collapse the Von Neumann bottleneck.
Runs inference on milliwatts instead of hundreds of watts. Designed for passive cooling, allowing intelligence to operate on solar, battery, or orbital power.
Data is processed where it is generated. Zero network overhead, zero latency spikes, and structural privacy guarantees because the bits never leave the device.
Unplugged training lets models adjust weights dynamically on-device using local feedback loops, without dialing back to centralized server farms.