Launch a self-service GPU Cloud in days

Deliver AI/GenAI experiences to enterprise customers with enterprise-grade controls, leveraging GPU virtualization, cluster multi-tenancy, and self-service workflows to maximize your investment. Streamline platform engineering with Rafay to automate operations and empower small teams to achieve more efficiently.

Talk to a PaaS expert

Immediately monetize your
GPU investment with Rafay

With Rafay, GPU Cloud and Sovereign Cloud providers move from a stack of hardware to a dynamically partitioned, secure multi-tenant platform in days. Rafay provides the fastest path to monetization – bar none.

Key Rafay platform capabilities for delivering a GPU/Sovereign Cloud:

 

Self-service GPU Consumption

Empower developers & data scientists to consume GPU resources in a store-front experience on demand

AI Apps delivered as a Service

Templatize and package AI/ML apps on the Rafay Platform for as-a-Service delivery

Cost Efficiency

Maximize your infrastructure efficiency with real-time monitoring and optimized GPU utilization.

One Platform – Multiple Deployment Options

The Rafay Platform is designed to address the most complex requirements from the most demanding Cloud customers. Rafay’s customers have multiple deployment options available to them:

Consume the Rafay

Platform as SaaS

A majority of Rafay customers consume Rafay in a SaaS form factor. Why? Because the SaaS model lets them start to immediately deliver value to customers with a SOC-2 compliant platform that addresses all requirements put forward by your security team.

Consume the Rafay Platform

in an air-gapped model

Sovereign AI Clouds and 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.

Consume the Rafay Platform

across data center and CSP
environments

Whether you plan to deploy many small GPU Cloud footprints across a large region or mix your GPU Cloud environments with capacity from an in-region CSP, Rafay can help. All of 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

Is GPU Virtualization supported?

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.

Do you also provide AI/ML workbenches and other tooling?

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.

Does your platform also support CPU consumption?

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.

How does Rafay solve for chargeback and billing?

The Rafay Platform collects granular chargeback information that can easily be exported to the customer’s billing systems for downstream dissemination. Chargeback group definition and data collection can be carried out programmatically.

Does Rafay support infrastructure-as-code (IaC) principles?

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.

Want to Start Now?

See for yourself how Rafay delivers the automation developers and operations want with the right level of standardization, control and governance platform teams need!

Sign up now