Optimise, test, and secure models on real Edge AI hardware.

  • Tested on real physical hardwareModels are tested on read hardware in our lab.
  • Optimised AI modelsQuantised, pruned and checked on each platform.
  • Secured model inside the chipEncrypted at rest, decrypted using the chip’s TEE.
  • Attest your deployed modelSign your models through an HSM or KMS.
01Test

Run your model on real hardware.

  • The real numbers come from the real boardGet real throughput metrics from real hardware runs.
  • Already deployed? Keep testing on itEmbed our testing suite as a CI step, and run tests on the same silicon you ship.
  • Exploring a new platform?We run your model at several levels of optimisation, and measure latency, memory & accuracy directly on the board.
See the platforms we run on
02Optimise

Optimised only as far as it needs.

  • Only when it needs itWe will optimise your model, if needed, depdending on hardware constraints or throughput limitations.
  • Quantised, pruned and compiled for the chipWith the platform’s own toolchain, for that exact silicon.
  • Accuracy measured at every stepSo you choose the trade-off from real numbers.
Read: two medical models on one $249 box Read: how much precision do you actually need?
03Secure

Protect your IP.

  • Encrypted at restThe model is never stored in the clear on the device.
  • Decrypted only inside the chip’s TEEWith per-device keys tied to the silicon.
  • Unreadable, even with rootPull the disk, root the OS, all you get is ciphertext.
Read: shipping confidential models to edge devices
04Attest

Signed at every step.

  • Original and optimised models are cross-signedWhere a model came from is always provable.
  • The device verifies before it runsOnly a model you signed is ever loaded.
  • Built on Sigstore CosignA Linux Foundation project - the keys stay on a KMS or a hardware token.
Read more on Sigstore Cosign

Tested on real hardware.

Jetson Orin
Genio series
i.MX 8
AM69, AM68A & AM67A
RK3588
QCS6490

Latest from our blog

All articles
Oct 5, 2026 · Maxime Carriere

What is GGUF? How on-device language models routed around the standard

GGUF is the file format most on-device language models run from. Unlike ONNX it carries no computation graph, only quantised weights and the metadata to run them, and one …

Read Sep 29, 2026 · Maxime Carriere

What is actually running inside your earbuds?

You talk to an AI through them every day. Almost none of it happens in the earbud, and the part that does is a tour of every constraint on this blog, in five grams.

Read Sep 22, 2026 · Maxime Carriere

Three reasons robots will need many small AI models

Time, energy and what is allowed to travel: why robots are converging on multiple AI models and specialised learned components running at different rates, and where that …

Read