Protection, not obfuscation
Security that rests on a hardware root of trust, not on an attacker failing to look closely.
Trusted AI at the edge
Machine learning is leaving the datacentre — onto factory floors, into vehicles, inside products you no longer control. We build the trust layer that makes that safe: your model runs where it needs to, and nowhere else.
A model represents years of data collection, training and domain expertise. The moment it ships to a customer site, an edge box or a partner's server, it becomes a file on hardware you do not control — copyable, inspectable, redeployable.
Most teams answer this with contracts and hope. We think it should be answered with engineering.
Security that rests on a hardware root of trust, not on an attacker failing to look closely.
Industrial sites are disconnected, air-gapped and slow to update. That is the normal case for us, not the exception.
Protected models run on the accelerators you already have, at the precision you already trained for.
Flagship
Model protection and device-bound licensing. A protected model is useless as a file and runs only on hardware you have licensed — online or fully air-gapped.
In development
We are building out the rest of the platform. If you have a deployment problem that looks adjacent to this, we would like to hear about it.