Custom AI on hardware you own.

We build custom models, agents, and applications that run on your own hardware, so your data doesn't go to a third party. Open models can now do much of the work companies pay cloud APIs for. We choose the model, compress it to fit your machines, tune it for speed, and build the software your team will use.

Our published model builds run 1.3× to 3.8× faster than stock on the same hardware, and each one ships with the benchmark we used. We've set more than 140 records on Yukon's benchmark challenges, including first place in MLX.fast with a 272% speedup on Qwen 3.8, and took the lead in OpenAI's Parameter Golf seven times.

The full interactive site: tools, games, music, and work in progress. Best on a desktop.

1. A short conversation. The work, your current setup, and what you want to improve.
2. A scoped pilot. Agree on the first deliverable and how we'll measure it.
3. Build and measure. A running system, evaluation tools, and a write-up of the results.
4. Hand-off or ongoing work. Your team runs it, or we keep building together.

Jordan Newman founded and runs Omnispace. The work spans upstream GPU kernels, published model packages, and complete applications.

Model timings are self-measured for the stated configurations. Competition results come from the organizers' leaderboards. We measure your workload before projecting performance or cost savings.

Tell us what you're building, what's getting in the way, and your timeline. We'll work out a useful place to start.

Also open to research partnerships, funding conversations, and publishing collaborations.