Platform as a Service · PaaS
The layer
above the
metal
Managed Kubernetes, serverless inference endpoints, a model registry and a job scheduler. Run them, or don't: the infrastructure underneath works either way.
Architecture
How the stack
fits together
Managed services
Things you'd
rather not run
Conformant, GPU-aware
Upstream Kubernetes with the NVIDIA operator, MIG partitioning, cluster autoscaling and the CSI drivers for our block and file tiers already wired in. We patch the control plane; you keep the kubeconfig.
Serverless inference
Push a container, get an HTTPS endpoint that scales from zero to hundreds of replicas on queue depth. Cold start on a warm pool is under four seconds, and idle costs nothing.
Models and images
An OCI registry and a versioned model store in-region, so pulls happen over the internal fabric instead of the public internet. Signing and vulnerability scanning included.
Batch and queues
Slurm or Kueue on your reserved capacity, with fair-share across teams, priority pre-emption and per-project accounting that maps to your chargeback model.
Getting on
A typical
onboarding
This is the actual sequence, not a marketing funnel. Most teams are running real work in week two.
Scoping
An engineer walks through your workload, current spend and residency constraints. You get a sizing and a written quote, usually within three working days.
Landing zone
We build the VPC, projects, IAM roles and quotas, connect your SSO, and run a benchmark on the exact shape you'll be using.
Cutover
Data seeding over direct connect or a shipped appliance, a parallel run against your current provider, then a scheduled switch.