AI Cloud Stack
Deploy your AI cloud faster with Gcore. Turn GPU infrastructure into enterprise-grade AI services in just months.
Why enterprises choose Gcore AI Cloud Stack
With over a decade of building global cloud infrastructure, Gcore delivers AI-native, cloud-ready, enterprise-proven solutions. We combine hyperscaler functionality with deep AI expertise to help enterprises launch and monetize AI clouds faster, with confidence.
Time to market
Launch your AI cloud in as little as 2 months vs 12–24 months in-house. Eliminate delays and accelerate adoption with a ready-made stack.
Proven success
Backed by 10+ years of cloud expertise and certified architects. Trusted to cloudify estates of tens of thousands of GPUs with enterprise grade reliability.
Operate with confidence
Enjoy hyperscaler-grade orchestration, monitoring, and billing. 24/7 support minimizes risk and frees your team to focus on innovation.
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 at Nokia
A clear path from deployment to revenue
Your three-step path to launch, scale, and monetize your AI cloud.
01
Deploy and launch
Start fast with a full architecture audit and cloud stack deployment. Your infrastructure is performant and compliant from day one.
02
Operate and scale
Maintain outstanding performance with 24/7 monitoring, automated incident response, capacity planning, and expert optimization. Scaling AI workloads becomes simple and reliable.
03
Grow revenue
Unlock monetization opportunities. With go-to-market support, reseller channels, and onboarding automation, idle capacity is replaced by profitable cloud services.
Enterprise power, out of the box
Smarter control
Create projects, select regions, and set quotas with ease. Track async tasks, audit user actions, and manage IAM roles and bindings, giving you enterprise-grade governance without added complexity.
High-performance compute and storage
Run on-demand VMs or bare metal GPUs. Manage images, volumes, snapshots, and S3-compatible objects while seamlessly sharing files across networks for high-throughput AI workloads.
Secure networking at scale
Build robust environments with VPCs, custom routing, firewalls, and load balancing. Allocate public or reserved IPs, manage ranges, and enable enterprise-class DDoS protection to keep traffic secure and latency low.
Effortless orchestration
Deploy, scale, and run applications with managed Kubernetes and CaaS. Control clusters and registries via a unified service, simplifying orchestration for even the most complex AI deployments.
AI-ready platform services
Accelerate adoption with managed PostgreSQL, Slurm-on-K8s, Jupyter, and GPUaaS. Enable 3-click serverless deployments of inference jobs, with autoscaling, monitoring, and lifecycle management built in.
Always-on management and support
Get enterprise observability with SSH key management, cost reporting, and 24/7 monitoring. Multi-tenancy across CPU, network, and storage ensures secure isolation and consistent performance at scale.
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 future-proof AI infrastructure. Gcore offers operators a valuable option to move quickly without building everything themselves.
Dan Chester, CSP Director EMEA, VAST
Why most enterprises don’t DIY
| Service model | Setup complexity | Time-to-launch | Revenue model | Primary skills | Infrastructure needed |
|---|---|---|---|---|---|
| Infrastructure as a service | High | 12-24 months | Pay-per-VM | DC & network ops, Sys-admin Linux | DC space, power & cooling, Compute, storage, network HW |
| Platform as a service | Medium | 18-33 months | Usage-based | Platform/K8s engineering, SRE & DevEx | IaaS plus: Managed runtimes, DBs, queues |
| GPU platform as a service | Medium-high | 22-39 months | GPU-hours | GPU cluster ops & tuning, ML/Ops | PaaS plus: GPU servers, NVLink/InfiniBand fabric |
| Model as a service | Low-medium | 25-45 months | Per-token/request | ML research & fine-tuning, API product mgmt | GPU PaaS plus: Pre-trained model zoo, Inference micro-services |
Ready to turn GPU clusters into revenue?
Talk to an AI expert about Gcore AI Cloud Stack.
Frequently asked questions
How quickly can we launch our AI cloud?
With Gcore AI Cloud Stack, you can launch in as little as two months, depending on your capacity, compared to 12–24 months building in-house. Our proven methodology includes deployment, operation, GTM, and immediate operational support to accelerate your time-to-market.
Can the deployment process be tailored to our specific needs?
Yes. Gcore can design an AI cloud solution from the ground up, or integrate with your existing infrastructure to optimize, cloudify, and monetize GPU estates already in use.
What level of customization and branding is available?
Complete white-labeling with your branding across the entire platform from IaaS to MaaS.
What ongoing operational support is included?
24/7 monitoring and expert management by certified cloud architects, AI specialists, and partners. This includes incident response, proactive maintenance, capacity planning, performance optimization, and technical support with guaranteed SLA performance.
What differentiates Gcore from other providers?
We have 10+ years of cloud expertise and proven success cloudifying estates of tens of thousands of GPUs.