Use Case
Production inference with guaranteed latency
Serve production traffic on hardware nobody else can touch: hot spares on standby, throughput that holds at p99, and capacity that scales with a launch instead of buckling under it.
Serve production traffic on hardware nobody else can touch: hot spares on standby, throughput that holds at p99, and capacity that scales with a launch instead of buckling under it.
Dedicated GPUs mean your tokens-per-second never degrade because another tenant spun up a training job next door.
Optimized networking and locally attached NVMe keep time-to-first-token low even under heavy concurrent load.
Scale endpoints up for launch spikes and back down afterward, with reserved baseline capacity always available.
Run vLLM, TensorRT-LLM, Triton, or your own serving framework. We give you the bare metal, you keep full control.
Tell us what you're building. We'll scope the cluster, quote a fixed monthly number, and commit to a commissioning date in writing. Dedicated capacity takes a quarter or more to stand up. The difference with us is that you'll know exactly when yours arrives.