Dedicated GPU clusters

Dedicated AI compute, built and run for you.

TensorCove designs, builds and operates private GPU clusters for AI companies and enterprises, on our power or at your site, and runs them around the clock under a service-level agreement.

Shared cloud capacity is scarce. Building your own data center takes years. A dedicated cluster gives you the middle path.

Predictable performance

Your GPUs, your network fabric and your storage. No noisy neighbors and no surprise capacity limits.

Predictable cost

A fixed contract for dedicated capacity, so you can plan training runs and inference growth with confidence.

No infrastructure burden

We handle power, cooling, procurement, installation and operations. Your team stays focused on models and products.

What we do

One partner, from design to daily operations.

We design, build and run the cluster. You get dedicated capacity.

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Cluster design

Architecture fit to your workload: GPU platform, network fabric, storage and facility, sized for training, inference or both.

Build and deploy

We procure the full stack, install and integrate it, and validate performance before we hand the cluster over.

Managed operations

24/7 monitoring, alerting and on-site response, with reporting that plugs into your own tools.

SLA assurance

Redundant design, spare parts on hand and fast replacement paths behind every service commitment.

Four layers: facility, infrastructure, platform and your workloads
Full-stack design

Engineered from the data hall to your workloads.

One integrated design across power, cooling, GPUs, networking and the software platform, so every layer works together from day one. Your models and data stay yours.

  • NVIDIA B300, GB300 and Vera Rubin, as available, plus AMD options
  • InfiniBand or Spectrum-X fabric, liquid or air cooling
  • NVIDIA AI Enterprise, Run:ai, Kubernetes or Slurm
Explore our infrastructure
Operations

Operated 24/7, from facility to GPU.

We monitor every level around the clock and act on alerts before they affect your workloads.

  • Facility: power, cooling and physical security
  • Rack: power per circuit, coolant flow and temperature
  • Compute: GPU, node and network fabric health
  • Redundant (N+1) power and cooling, spares on hand, rapid on-site dispatch
How we run your cluster
Rack diagram showing compute, rack and facility monitoring

Ready to plan your cluster?

Tell us about your workload and timeline. We will come back with a cluster design and a proposal.

Talk to us