Enterprise GPU as a Service (GPUaaS) Platform
Rafay is the platform that enables enterprises and providers to deliver GPU as a Service.
Organizations are investing heavily in GPU infrastructure, but most struggle to deliver it as a usable service. Access is manual, environments are inconsistent, and utilization remains low. Developers wait for resources while expensive GPUs sit idle.
GPU as a Service (GPUaaS) solves this by enabling on-demand, self-service access to GPU resources. Rafay provides the platform layer that allows enterprises and providers to build and operate GPUaaS offerings—turning raw infrastructure into a scalable, governed service for AI/ML workloads.
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What is GPUaaS?
GPU as a Service (GPUaaS) delivers on-demand access to GPU compute through APIs or self-service portals, similar to how cloud platforms deliver CPU-based infrastructure. Instead of provisioning clusters manually, users can instantly launch GPU-backed environments with built-in governance, isolation, and usage tracking.
Rafay enables this model by transforming existing GPU infrastructure into a fully operational GPUaaS platform.
How to Build and Operate a GPUaaS Platform
Deliver a Self-Service GPUaaS Experience
Enable developers, data scientists, and customers to provision GPU resources instantly without tickets or manual intervention. Rafay provides a fully automated, self-service experience for AI/ML workloads.
- On-demand GPU provisioning via UI, API, or CLI
- Pre-configured environments for consistent workloads
- Rapid setup for Kubernetes clusters, VMs, and AI frameworks
Operate GPUaaS with Multi-Tenant Control
Deliver GPU as a Service securely across teams, business units, or external customers. Rafay provides built-in multi-tenancy, RBAC, and policy enforcement so infrastructure can be shared safely.
- Tenant isolation across projects and users
- Role-based access control and policy enforcement
- Auditability and compliance across all workloads
Maximize GPU Utilization and Efficiency
GPUaaS platforms only succeed when utilization is high and waste is minimized. Rafay pools GPU resources and dynamically allocates them across workloads to ensure infrastructure is fully utilized.
- Reduce idle GPU time and resource fragmentation
- Allocate compute based on real-time demand
- Gain visibility into usage across teams and tenants
Unified Orchestration for GPUaaS Infrastructure
Rafay provides centralized orchestration across Kubernetes, GPUs, and hybrid environments—enabling consistent delivery of GPUaaS across cloud and on-prem infrastructure.
- Manage clusters across AWS, Azure, GCP, and data centers
- Standardize environments with templates and blueprints
- Automate lifecycle management for AI/ML workloads
Trusted by leading enterprises, neoclouds and service providers
Run Compliant Cloud-Native and AI Workloads in Private Clouds Without Slowing Development
Most enterprises face a trade-off: meet strict compliance requirements or move fast. The Rafay Platform makes both possible. With air-gapped deployments, multi-tenancy, and centrally governed self-service environments, enterprises can securely operationalize AI workloads in their own data centers—while still giving internal teams the agility of a modern cloud experience.
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Slash Cloud Complexity and Costs in AWS, Azure, or GCP
Workloads in the public cloud create new challenges: spiking infrastructure costs, governance gaps, and operational drag. The Rafay Platform abstracts away the complexity, giving platform teams a single pane of glass to orchestrate, govern, and optimize AI/ML infrastructure across clouds. Enterprises cut costs, reduce overhead, and give developers the freedom to innovate faster.
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One Platform - Multiple Deployment Options
Deploy as a SaaS
A majority of Rafay customers consume Rafay in a SaaS form factor. Why? Because the SaaS model lets them start immediately with the Rafay Platform and deliver value to their customers. The Rafay platform is SOC-2 Type compliant, and will address all requirements put forward by your security team.
Deploy in an Air-Gapped Model
Customers in highly regulated industries prefer Rafay’s air-gapped controller model. Team Rafay is ready to help you deploy the Rafay Platform in your data center or in your private/public cloud environment. You get exactly the same experience and all the same features available to our SaaS customers.
Deploy across Data Center and CSP Environments
Whether you plan to deploy GPUs in multiple colos, or lease GPUs in a CSP environment, or both, Rafay can help. With Rafay, all your compute across all private and CSP environments can be managed as a single pool of GPUs and CPUs, reducing operational overhead and enabling cloud-bursting use cases.
GPU PaaS™ FAQs for Enterprises
Find answers to common questions about the Rafay Platform's GPU Cloud orchestration services below.
Yes. GPU and Sovereign Cloud providers can choose to offer fractional GPUs to end users in a self-service fashion. The Rafay Platform will take care of security, compute isolation and chargeback data collection.
Yes. The Rafay Platform offers a variety of workbenches out of the box. These are based on Kubeflow and KubeRay, with end users consuming these platforms “as a service,” without needing to configure or operate any of these tools on their own. Further, the Rafay platform provides a low-code/no-code framework that empowers partners to bring new capabilities to market faster, e.g. verticalized agents, co-pilots, document translation services, and more.
Yes. The Rafay Platform has always supported CPU-based workloads and can easily deliver a PaaS experience that offers CPU+GPU instances to end users.
Rafay offers a comprehensive solution for chargebacks and billing. The platform collects granular chargeback information on resource usage, which can be easily exported to customers’ existing billing systems for further processing and distribution. Rafay allows for customizable chargeback group definitions to align with organizational structures or projects. Both group definition and data collection can be carried out programmatically, enabling efficient and accurate billing processes.
Yes. Rafay supports a number of IaC frameworks, enabling customers to programmatize every aspect of their cloud. The Platform supports Terraform, OpenTofu, GitOps pipelines, CLI and API workflows out of the box.
Turn your GPU infrastructure into a GPUaaS platform
Deliver self-service GPU access, improve utilization, and scale AI/ML workloads with confidence.
