Introducing AI Cloud Stack: turning GPU clusters into revenue-generating AI clouds

Enterprises and cloud providers face major roadblocks when trying to deploy GPU infrastructure at scale: long time-to-market, operational inefficiencies, and difficulty bringing new capacity to market profitably. Establishing AI environments with hyperscaler-grade functionality typically requires years of engineering effort, multiple partner integrations, and complex operational tooling.

Not anymore.

With Gcore AI Cloud Stack, organizations can transform bare Nvidia GPU clusters into a fully cloud-enabled environment—complete with orchestration, observability, billing, and go-to-market support—all in a fraction of the time it would take to build from scratch, maximizing GPU utilization.

This proven solution marks the latest addition to the Gcore AI product suite, enabling enterprises and cloud providers to accelerate AI cloud deployment through better GPU utilization, monetization, reduced complexity, and hyperscaler-grade functionality in their own AI environments. Gcore AI Cloud Stack is already powering leading technology providers, including VAST and Nokia.

Why we built AI Cloud Stack

Buying and efficiently operating GPUs at a large scale requires significant investment, time, and expertise. Most organizations need to hit the ground running, bypassing years of in-house R&D. Without a robust reference architecture, infrastructure and network preparation, 24/7 monitoring, dynamic resource allocation, orchestration abstraction, and clear paths to utilization or commercialization, enterprises can spend years before seeing ROI.

“Gcore brings together the key pieces—compute, networking, and storage—into a usable stack. That integration helps service providers stand up AI clouds faster and onboard clients sooner, accelerating time to revenue. Combined with the advanced multi-tenant capabilities of VAST’s AI Operating System, it delivers a reliable, scalable, and futureproof AI infrastructure. Gcore offers operators a valuable option to move quickly without building everything themselves.”

— Dan Chester, CSP Director EMEA, VAST Data

At Gcore, we understand that organizations across industries will continue to invest heavily in GPUs to power the next wave of AI innovation—meaning these challenges aren’t going away. AI Cloud Stack solves today’s challenges and anticipates tomorrow’s. It ensures that GPU infrastructure at the core of AI innovation delivers maximum value to enterprises.

How AI Cloud Stack works

This comprehensive solution is structured across three stages.

1. Provision and launch

Gcore handles the complexities of initial deployment, from physical infrastructure setup to orchestration, enabling enterprises to go live quickly with a reliable GPU cloud.

2. Operations and management

The solution includes monitoring, orchestration, ticket management, and ongoing support to keep environments stable, secure, and efficient. This includes automated GPU failure handling and optimized resource management.

3. Go-to-market support

Unlike other solutions, AI Cloud Stack goes beyond infrastructure. Building on Gcore’s experience as a trusted NVIDIA Cloud Provider (NCP), it helps customers sell their capacity, including through established reseller channels. This integrated GTM support ensures capacity doesn’t sit idle, losing value and potential.

What sets Gcore apart

Unlike many providers entering this market, Gcore has operated as a global cloud provider for over a decade and has been an early player in the global AI landscape. Gcore knows what it takes to build, scale, and sell cloud and AI services—because it has done it for customers and partners worldwide. Gcore AI Cloud Stack has already been deployed on thousands of NVIDIA Hopper GPUs across Europe to build a commercial-grade AI cloud with full orchestration, abstraction, and monetization layers. That real-world experience allows Gcore to deliver the infrastructure, operational playbook, and sales enablement customers need to succeed.

“We’re pleased to collaborate with Gcore, a strong European ISV, to advance a networking reference architecture for AI clouds. Combining Nokia’s open, programmable, and reliable networking with Gcore’s cloud software accelerates deployable blueprints that customers can adopt across data centers and the edge.”

— Mark Vanderhaegen, Head of Business Development, Data Center Networks, Nokia

Key features of AI Cloud Stack

Cloudification of GPU clusters: Transform raw infrastructure into cloud-like consumption: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), GPU as a Service (GPUaaS), or Model as a Service (MaaS).

Gcore AI suite integration: Enable serverless inference and training capabilities through Gcore’s enterprise AI suite.

Hyperscaler functionality: Built-in billing, observability, orchestration, and professional services deliver the tools CSPs and enterprises need to operate—similar to what they’re used to getting on public cloud.

White-label options: Deliver capacity under your own brand while relying on Gcore’s proven global cloud backbone.

NVIDIA AI Enterprise-ready: Integrate pretrained models, chatbots, and NVIDIA AI blueprints to accelerate time-to-market.

The future of AI clouds

With Gcore AI Cloud Stack, enterprises no longer need to spend years building the operational, technical, and commercial capabilities required to utilize and monetize GPU infrastructure. Instead, they can launch in a few months with a hyperscaler-grade solution designed for today’s AI demands.

Whether you’re a cloud service provider, an enterprise investing in AI infrastructure, or a partner looking to accelerate GPU monetization, AI Cloud Stack gives you the speed, scalability, and GTM support you need.

Ready to turn your GPU clusters into a fully monetized, production-grade AI cloud? Talk with our AI experts to learn how you can go from bare metal to model-as-a-service in months, not years.

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