For Enterprises

Convert a stack of GPUs into a GPU PaaS™ in days

Rafay’s Platform-as-a-Service layer simplifies the complexities of managing cloud-native and AI infrastructure by providing a secure, multi-tenant foundation. It enables self-service access for platform and devops teams, improves governance, optimizes costs, and accelerates the delivery of cloud-native and AI-powered applications.

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Immediately monetize your
GPU investment with Rafay

Rafay delivers self-service AI/ML and GenAI infrastructure with enterprise-grade governance:

Secure GPU access for dev/data science teams

Packaged AI/ML workbenches for model training & inference

Kubernetes automation across disconnected/air-gapped sites

EKS-like experiences on private infrastructure

What the Rafay Platform Delivers for Enterprises in the Private Cloud

AI/ML Workload Enablement

On-demand GPU access for model training and inference
Elastic resource allocation to avoid overprovisioning, idle GPU capacity, and wasted GPU spend
Self service GPU consumption complete with packaged notebooks and an MLOps capability with support for distributed training and inference, LLM model catalog, inference and fine tuning work

Automated Infrastructure Operations

Fleet-wide, automated Kubernetes provisioning, upgrades and lifecycle management workflows
Simplified management of distributed clusters and platform add-ons

Air-Gapped & Secure Environments

Full cluster lifecycle automation in air-gapped environments
Support for AI/ML workloads and microservices within high-security zones (e.g. defense or government labs)

Get Compliant AI Workloads in Private Clouds Without Slowing Development

Intelligent GPU Allocation & Scheduling

Optimize utilization of high-value GPU resources across shared and dedicated workloads.

Built-in AI/ML & GenAI Workbenches

Bring AI/ML tooling and platforms (e.g., AWS Bedrock equivalents) to private cloud environments

Self-Service Portals with Governance Controls

Empower teams while maintaining enterprise-grade policies and guardrails

Private Cloud Kubernetes-as-a-Service

Deliver a managed Kubernetes experience (EKS-like) across on-prem and hybrid infrastructure

Key Benefits Enterprises Can Expect with the Rafay Platform

Unified Infrastructure Control

Manage Kubernetes environments consistently across cloud providers (EKS, GKE, AKS) and on-prem.

Data Sovereignty & Isolation

Enforce strict data residency policies and maintain workload separation to minimize breach risks.

Air-Gapped Operability

Enable disconnected environments to maintain full lifecycle capabilities without relying on public internet.

Tooling Compatibility

Integrate seamlessly with existing enterprise CI/CD, observability, networking, and security stacks.

Developer Empowerment

Offer GPU-powered workspaces and AI/ML environments with streamlined access and full compliance.

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.

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GPU PaaS™ Reference Architecture

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