Use Cases

What teams run on our AI servers

From a single private assistant to a multi-GPU inference backend, the hardware is sized to the job. Here are the workloads clients host with us most.

Serve open models at production latency and throughput on dedicated GPUs.

Internal assistants that keep company data in-house, on your own server.

Search and reason over your own knowledge base, fully private.

Diffusion workloads on dedicated GPU capacity, sized to your throughput.

Detection, classification and inspection pipelines on private hardware.

Batch and streaming transcription at scale on dedicated GPUs.

The GPU layer behind your customer-facing product, private and predictable.

Stable environments for evaluation and staging, isolated from production.

Targeted training runs for smaller models on dedicated hardware.

Isolated environments for sensitive and regulated workloads.

Have a workload in mind?

Tell us what you want to run and we will design the right GPU server for it, host it and hand over full control.