From the makers of

Run Your GPU Data Center Like a Hyperscaler

vMetal turns your racks into a compute platform. Don’t DIY your cloud, run it with vMetal.

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Provision & PXE boot bare metal servers

Deploy and dynamically scale Kubernetes compute clusters

Manage infra declaratively or via a flexible UI

Automate networking and DNS

Spin up AI platforms like Run:ai, Ray, Slurm, and SkyPilot

Customers Expect More Than Just Bare Metal

Selling raw GPU infrastructure is quickly becoming a commodity. To win deals and maximize GPU utilization, Neoclouds must deliver a managed platform experience similar to EC2 or EKS.

Bare Metal Alone Is a Commodity

Selling raw GPU infrastructure quickly becomes a race to the bottom. Without a platform layer, teams struggle to differentiate and end up managing infrastructure tickets instead of delivering a real platform.

Customers Expect a Managed Platform

Developers expect managed Kubernetes and self-service environments. Without this, onboarding is slower and time to value increases.

Building This Platform Takes Years

Hyperscalers spent years building stable Kubernetes platforms. Trying to recreate this internally delays launch, increases TCO, and risks losing deals or slowing innovation.

vMetal helps Neoclouds deliver an EKS-like platform on their GPU infrastructure, without spending years building it from scratch

Building a GPU Cloud Platform Takes Significant Time and Resources

Delivering a managed GPU platform requires building the same infrastructure capabilities hyperscalers developed internally, often requiring months of engineering work before revenue can begin.

Platform Capability

Hiring Needs

Time to Build

Business Impact

Bare metal provisioning & PXE automation

2–3 infrastructure engineers

3–4 months

GPUs sit idle while platform is built

Network automation & tenant isolation

1–2 networking engineers

2–3 months

Complex networking increases operational risk

Kubernetes cluster orchestration

2–3 platform engineers

3–6 months

Slower customer onboarding

Multi-tenant compute infrastructure

2+ platform engineers

4–6 months

Security and isolation complexity

End-user platform integrations (Run:AI, Ray, Slurm)

1–2 engineers

2–3 months

Longer time-to-value for customers

The Hidden Cost of Building It Yourself

Launching a managed GPU platform internally requires significant investment. During this time, GPU infrastructure may sit partially unused while the platform is built.

6–10 platform engineers
$1M+ in engineering cost
6–12 months of development
Ongoing maintenance and upgrades
Continuous pressure to match competitor capabilities

A $10M GPU cluster generating $2–3 per GPU hour can lose millions in potential revenue if launch is delayed by months

The Modern AI Infrastructure Stack

Running a successful GPU cloud requires multiple layers of infrastructure, from hardware to customer environments. vMetal powers the infrastructure layer, turning raw hardware into programmable capacity for bare metal, Kubernetes clusters, and AI platforms.

From Bare Metal to Cloud Infrastructure

vMetal automates the infrastructure operations required to run a GPU cloud. Provision machines, orchestrate networks, and manage the lifecycle of GPU nodes, all from a single control plane.

Bare Metal Provisioning

Automatically provision servers with PXE boot, OS installation, and machine registration.

Machine Lifecycle

Allocate, repurpose, upgrade, and retire machines through a single control plane.

Tenant Network Isolation

Automate VLAN and VXLAN networking for secure, hard multi-tenant environments.

One Stack from Hardware to AI Platforms

vMetal works together with vNode and vCluster to create a unified, programmable platform for AI infrastructure, enabling hard multi-tenancy across networking, nodes, and Kubernetes clusters.

vCluster Certified Stacks

Preconfigured AI Environments

Run certified AI platform stacks with

Secure Runtime For AI Workloads

Runs on any Kubernetes cluster or on vCluster

Tenant & Cluster Orchestration

Runs on any public or private cloud or on vMetal

Bare Metal Machine Management

Runs directly on bare metal servers

Why Neoclouds Use vMetal

Launch Your Platform Faster

Turn GPU hardware into a cloud platform in weeks instead of building internal infrastructure tooling from scratch.

Simplify Infrastructure Ops

Provision machines, manage lifecycle, and automate networking from a single infrastructure control plane.

Maximize GPU Utilization

Allocate and repurpose infrastructure dynamically so GPUs stay productive and revenue-generating.

Trusted by NVIDIA for AI Infrastructure

“With vCluster on DGX systems, you can bring the elasticity, automation, and multi-tenancy of Kubernetes onto your on-prem infrastructure. Get the experience of the public cloud on your DGX systems.”

NVIDIA Data Center
@NVIDIADC

Dive deeper. Learn more.

Explore guides, reference architectures, and solutions for building GPU clouds and AI infrastructure.

EBOOK

NVIDIA DGX Reference Architecture

A blueprint for bringing cloud-grade elasticity and automation to NVIDIA DGX systems.

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Solution

Automate Network Isolation for Hard Multi-Tenant Kubernetes

vCluster and Netris integrate Kubernetes and network automation.

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Guide

vCluster Guide to Achieve ClusterMAX™ Platinum Rating

Learn how to deliver enterprise-grade Kubernetes for AI workloads and improve ClusterMAX™ rating.

View guide

Turn Your GPU Infrastructure Into a Cloud Platform

Provision machines. Run Kubernetes. Deliver AI environments — all on your own hardware.

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