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Rafay Systems Brings Software Standardization to Neocloud and Sovereign AI Factories Through Its NVIDIA-Validated Platform

Infrastructure orchestration for AI and cloud-native workloads

News provided by

Rafay Systems

May 13, 2026, 13:00 ET

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With the Rafay Platform having undergone NVIDIA AI Cloud-Ready validation, neoclouds and sovereign AI cloud operators have the assurance that they can service the most demanding AI customers with Rafay-powered AI factories

SUNNYVALE, Calif., May 13, 2026 /PRNewswire/ -- Rafay Systems, a leader in infrastructure orchestration for AI and cloud-native workloads, today announced that it has achieved NVIDIA AI Cloud-Ready validation. This validation confirms that the Rafay Platform meets NVIDIA's software standard for operating production-grade AI cloud infrastructure. Rafay is among the first few independent software vendors to earn this designation, joining a select group of platforms validated to deliver the API-driven, multi-tenant capabilities that AI factories require to serve neocloud and sovereign workloads at scale.

The Rafay Platform delivers a suite of capabilities – from metal to model – that AI factories can monetize quickly, complete with token-based consumption options. Operators that leverage the Rafay Platform can meet the most stringent requirements from the world's biggest consumers of GPUs, including frontier model builders, while also being ready to meet enterprise governance and automation requirements.

The NVIDIA AI Cloud-Ready initiative sits alongside the NVIDIA Cloud Partners (NCP) program, part of the NVIDIA Partner Network (NPN), leveraging the NCP reference design which defines the hardware standard for the AI cloud infrastructure. Much like how the NCP program has become the industry standard for how AI factories are built, the AI Cloud-Ready initiative defines how cloud AI factories should deliver use cases. Together, the NVIDIA Cloud Partner program and AI Cloud-Ready initiative define a full-stack recipe for cloud AI factories. Customers are likely to require GPU providers to align with these standards before engaging in any high-value collaborations.

From rack to revenue
The AI factory market is maturing fast. Operators worldwide are deploying NVIDIA-powered infrastructure at unprecedented scale. Buyers evaluating neocloud and sovereign AI cloud providers are asking a pointed question: can you deliver infrastructure as a service? NVIDIA AI Cloud-Ready initiative is the answer to that question.

The Rafay Platform provides API-driven access to AI compute with hard and soft multi-tenancy, self-service workflows and production-grade governance built in. Combined with the NVIDIA Infra Controller, the Rafay Platform gives operators a validated, day-1 AI cloud platform. No custom integration required. Operators using the Rafay Platform can also deliver token-metered access to models hosted as NVIDIA NIM microservices and leverage NVIDIA NeMo libraries, AI Blueprints and a full range of AI compute services, turning GPU capacity into revenue from the moment infrastructure comes online.

"NVIDIA AI Cloud-Ready and its Cloud Partner program, together, offer a standard for how to build and deploy an AI factory from the hardware through the software stack," said Haseeb Budhani, CEO and co-founder of Rafay Systems. "Every GPU provider that has worked hard to meet NVIDIA Cloud Partner requirements will now need to ensure that their offering is operating an NVIDIA AI Cloud-Ready software stack. By partnering with Rafay, neoclouds and sovereign AI cloud providers can deliver validated hardware and software on day-1."

Built alongside NVIDIA, validated at scale
Rafay's AI Cloud-Ready designation reflects a multi-year technical relationship with NVIDIA. Among other deep integrations, the Rafay Platform works in concert with the NVIDIA Infra Controller, which handles rack-scale provisioning of NVIDIA Grace Blackwell systems, while Rafay provides the orchestration, governance and service-delivery layer above it. Together with NVIDIA Cloud Providers, they form a complete stack from bare metal to AI services. Rafay is also a member of the NVIDIA Inception program for startups.

The Rafay Platform complies with the NVIDIA Enterprise AI Factory validated design for Blackwell-based enterprise deployments, natively supports NVIDIA BlueField-3 DPUs and RTX PRO 6000 Blackwell Server Edition for full-stack GPU cloud orchestration, with planned support for future NVIDIA BlueField-4 DPUs, and is available via NVIDIA DSX Air for customers looking to validate their deployments from metal to model. Rafay also published a reference architecture for GPU PaaS with NVIDIA accelerated computing and NVIDIA AI Enterprise software.

"Neoclouds and service providers are racing to build AI factories capable of supporting the most demanding production-grade workloads," said Warren Barkley, vice president of product management, NVIDIA. "By becoming NVIDIA AI Cloud-Ready validated, the Rafay Platform — using NVIDIA Infra Controller — provides a turnkey, full-stack recipe for deploying an API-driven AI cloud. This validated software stack helps neoclouds and sovereign AI cloud operators deliver the secure user isolation and built-in guardrails required to scale enterprise AI globally."

What Rafay being "AI Cloud-Ready" means for operators
With the Rafay Platform having undergone NVIDIA AI Cloud-Ready validation, Rafay customers instantly meet four key market requirements:

  • API-driven infrastructure access: Kubernetes, virtual machines, SLURM and bare metal delivered as services, accessible programmatically via published APIs and consumable on demand.
  • Hard and soft multi-tenancy: Workload isolation at the hardware and platform levels, with quota enforcement and policy governance across teams, applications and geographies.
  • Production AI workload support: Validated compatibility with the NVIDIA accelerated compute stack, including orchestration, networking and AI platform software, with support for token-metered NVIDIA NIM microservices, NVIDIA NeMo libraries and AI Blueprints.
  • Enterprise-grade operational controls: Lifecycle management, security, compliance, self-service workflows and real-time monitoring that large buyers require before committing capacity.

For operators evaluating their path to AI cloud readiness, Rafay provides it out of the box, without the cost, complexity or time required to build or assemble a platform in-house.

Rafay is powering AI factories across six continents
The Rafay Platform powers sovereign and neocloud AI deployments worldwide.

  • Yotta, India's premier AI Cloud, is running its Shakti Cloud Platform on NVIDIA and Rafay.
  • Cassava Technologies is deploying Africa's first NVIDIA-powered AI factories on the Rafay Platform.
  • Firmus Technologies has integrated Rafay's PaaS capabilities into its green-energy-powered Australian AI Cloud.
  • TELUS is building a sovereign AI Studio in Canada with Rafay and NVIDIA.
  • Additional deployments span the Middle East, Latin America and Southeast Asia.

For more information about Rafay's AI Cloud-Ready designation and the Rafay Platform, read these blog posts:

  • NVIDIA AICR Generates It. Rafay Runs It. Your GPU Clusters, Finally Under Control
  • Accelerating the AI Factory: Rafay & NVIDIA NCX Infra Controller (NICo)

About Rafay Systems
Rafay Systems is a leading platform provider for modern infrastructure and AI workloads, delivering Platform-as-a-Service (PaaS) capabilities that enable organizations to operationalize compute infrastructure with self-service automation, governance and multi-tenancy. The Rafay Platform helps enterprises, cloud providers and sovereign AI cloud operators transform raw infrastructure into fully operational platforms for AI, Kubernetes and cloud-native applications. By simplifying infrastructure orchestration and lifecycle management, Rafay enables organizations to accelerate innovation while maintaining security, consistency and operational control. For more information, visit rafay.co.

MEDIA CONTACT
Cristin Connelly
Cathey.co for Rafay Systems
[email protected]

SOURCE Rafay Systems

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