The hard part was never the model. It's everything beneath it.
Agents that hold up in production.
Kernel-level engine. Accurate tool calls. Full context. Lower cost. No retraining. Your hardware — for coding, support, analytics, operations.
Runs on the GPUs you already own
The Engine
A kernel-level engine that sits below your serving stack.
Yantrion rebuilds the hottest path in inference. It runs on the GPUs you already own — AMD and NVIDIA — and never touches your model.
The result: more out of every cycle, and agents that get the call right.
Toward the hardest problems in computing
The next leaps won't come from bigger models. They'll come from the layer beneath them.
We go to the lowest layer because that's where the hardest problems are won — the agents enterprises run today, and the scientific and engineering workloads HPC has always lived on. Same engine, longer horizon.
The Engine
One kernel-level engine, beneath your stack.
Rebuilds the hottest path in inference. No model changes, no retraining, no wrappers. Runs on the hardware you already own.
See How the Engine WorksFlagship Agent
Engineering Copilot — the engine, proven.
The first enterprise agent running on the engine, in a hard, tool-heavy, accuracy-critical domain: NEC-compliant electrical drawings inside AutoCAD.
See the Flagship AgentWhere it matters
Built for agents that have to be right.
Enterprise agents fail in pilots for three reasons. The engine fixes all three at the layer beneath them.
They call the wrong tool.
Accurate tool calls at the kernel layer — structured outputs that resolve correctly the first time.
They lose the thread when context grows.
Full task memory held efficiently, so long-running agents don't forget what they were doing.
They cost too much to run at scale.
More agents per GPU — same hardware, materially more throughput.
Proof, not claims
Numbers, not claims. Kernel-level work.
No wrappers, no model changes. Benchmarked on your hardware, your models, your workload — AMD and NVIDIA.