X0NE · CONFIDENTIAL INFERENCE
You run an AI model on a machine you do not own. Before any question is sent, your computer checks that machine's hardware proof.
the sequence, illustrated
Inference is the moment a trained AI model receives a question and produces an answer. It is what runs every time someone uses an assistant.
The computation runs in a virtual machine with encrypted memory, with a GPU in confidential mode. Measured on Google Cloud: Intel TDX and an H100 GPU. Other clouds and your own Intel TDX hosts are planned. Before it receives a question or a key, that machine must prove it is genuine, and your computer checks the proof. Without that proof, the engine stops before opening a port.
Preview: the measurements were made with test keys, and no image is published yet.
End-to-end confidentiality is the goal. Today the proof covers the virtual machine and its GPU, not what surrounds them.
Outside it: your computer, where malware in your session can read the local key and your questions; what the host sees go by, times, durations, sizes, IP addresses and the name of the model served; physical attacks on memory and side channels; Google's firmware and the roots of trust of Intel, NVIDIA and Google; availability, since the VM is a spot VM that Google can stop. The engine prints its limits with every verdict.
For teams that want to use AI on sensitive data without handing it to the host in clear. Goal: also protect a model they own, its weights opened only after the proof.
Written from the repository's FEATURES.toml. On a measured line the date is the first run on a real confidential VM that exercised the feature; on a tested line, the first proof.