GPU & AI · cloud services

Package accelerator capacity as services customers understand.

Offer GPU instances, reserved capacity and managed Kubernetes through an operator-defined catalogue, portal and API.

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cloud.your-brand.examplebrandOverviewCompute & GPUServicesProjectsUsage & billingAPI keysSupportCompute & GPUProvision approved capacity+ New instanceInstances12 runningGPU hours6 reserved · 84 hKubernetes2 clusters · healthyYour servicesgpu-train-01 · 4× accelerator · runningapi-prod · 3 instances · healthypg-main · managed database · healthyk8s-mlops · 2 clusters · healthyUsage · this month€8,420 · 62% of budget · invoice on the 1st
Products
Multiple models
On-demand, reserved and managed
Channel
Portal & API
One service definition
Brand
Operator-owned
Your cloud relationship
Context
Plan-linked
Usage and commitment attached
Scope

A product layer around accelerator infrastructure.

Customers choose a service outcome while LayerOne carries capacity and policy underneath.

GPU instances

Expose approved accelerator shapes for immediate provisioning.

Reserved capacity

Offer committed allocations with clear tenant and pool context.

Managed Kubernetes

Publish accelerator worker profiles for training and inference clusters.

Complete environments

Connect images, storage, network and credentials around each service.

Operating workflow

Move from capacity to a customer-facing GPU product.

The catalogue joins operator infrastructure to a clear service journey.

  1. 01

    Define the product

    Choose service model, shape, location and options.

  2. 02

    Attach capacity

    Select eligible pools and reservation behavior.

  3. 03

    Publish

    Expose the product to approved tenants.

  4. 04

    Fulfil and meter

    Place the workload and begin the commercial record.

Two connected responsibilities

Operator control and customer action stay explicit.

Operator responsibility

What the operator productises

  • Service models and shapes
  • Eligible pools and locations
  • Commitments and quotas
  • Plans and lifecycle rules
Service consumer

What the buyer experiences

  • Clear GPU service choices
  • Immediate eligibility feedback
  • Project-aware provisioning
  • Usage and commitment visibility
Operational outcome

What this changes in the working model.

Outcome 01

A sellable offer

GPU infrastructure becomes a named, repeatable product.

Outcome 02

Choice without complexity

Customers select services instead of physical topology.

Outcome 03

One fulfilment path

Portal, API, placement and billing share the definition.

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Partner with us

Design the GPU products your customers will buy.

We will map instances, reservations and managed clusters onto your accelerator capacity.

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