Programmable edge silicon

The edge needs a new kind of chip.

A programmable compute fabric for edge AI and signal processing. Efficient, programmable, from sensor workload to silicon.

Become a design partner → See why
The shift

AI is moving from the datacenter to the physical world.

Compute now has to live inside cameras, microphones, robots, cars, and machines, where decisions happen in microseconds on a budget of milliwatts.

Datacenter
Answers

Big models. Big racks. Round-trips to a server.

askgeneraterespond
The edge
Acts

Models and signal pipelines. Live sensor data. On-device.

watchlistendetectreact
The problem

Nothing you can buy is efficient and programmable.

Specialized chips are efficient but rigid. Flexible chips waste power. The corner that is both sits empty.

efficient + programmable
ASICfixed function
NPU · HailoNN-only
MCUtoo weak
GPUpower-hungry
Texer.aiefficient + programmable
Programmable →
Efficient →
The architecture

A fabric of µFPUs. Not one giant GPU.

Millions of small programmable floating-point units. Each runs a tiny program on local sensor data, at the precision the workload actually needs. We spend silicon on the workload, not on generality.

→
Useful compute per transistor. Less control logic, less wasted precision.
→
Programmable to any workload. AI inference and signal processing alike.
→
Right precision, not 32-bit waste. The edge needs a few bits, not a datacenter's worth.
1
1 × FP32
=
~25 × µFPU
~25× the cores, same silicon.
What it delivers
10–100×
more useful compute per watt at the edge
Any
model or signal pipeline, on any sensor stream
Months
to working silicon, not the years an ASIC takes
The platform

From workload to silicon.

You bring the workload. We design, validate, and deliver the hardware, with a path to your own chip.

Why now

Demand is surging. Custom chips just got buildable.

The need ↑
  • Sensors are everywhere
  • Cloud is too costly, slow, and exposed
  • AI and signal processing moving on-device
The barriers ↓
  • Open-source chip tools have matured
  • FPGA prototyping is cheap and fast
  • AI now accelerates chip design

GPUs won the datacenter.
The edge needs its own compute layer.

We're building it. Partner with us to put custom silicon inside what you ship.

Become a design partner → Talk to us