Company
XNN builds an in-house GPU runtime and the on-device AI tools on top of it. We started with the hardest case, real-time translation, and built it as XNN Translate.
What we do
XNN is a small team building an in-house GPU runtime and the on-device AI software on top of it.
We wrote our own low-level GPU runtime instead of leaning on heavy frameworks, so the model runs directly on the device across a wide range of NVIDIA cards.
The model runs on the user's own machine. Audio, video, and text stay local, and there is no per-minute cloud bill that scales with use.
We tuned the runtime for live, low-latency work, the toughest test of an on-device engine, before anything else.
Why translate first
We started with the hardest version of the problem, real-time translation, because shipping it proves the engine is real.
XNN Translate takes live speech in and puts translated captions out, generated locally as people speak. The full path is verified live.
Creators, classrooms, and live shows that span languages need readable captions in the moment, not a cleanup pass afterward.
The same runtime and provider traits carry straight into the next on-device tools we build, so each product starts from proven ground.
Choose the next product action that matches your workflow.