As enterprises and cloud providers continue investing in advanced AI infrastructure, the focus is shifting from GPU deployment to operationalizing AI platforms that support secure, scalable, and production-ready services. Modern AI environments require orchestration, governance, automation, and self-service capabilities that enable organizations to rapidly move from infrastructure installation to AI application deployment.
Rafay Systems has announced a strategic collaboration with Aolani to deliver one of the industry's first deployments of NVIDIA DSX OS running on NVIDIA GB200 NVL72 infrastructure. The partnership aims to help AI cloud providers and enterprises accelerate the transition from GPU infrastructure deployment to fully operational AI platforms capable of supporting model development, training, inference, and enterprise AI workloads.
The collaboration combines Aolani's next-generation AI infrastructure with the Rafay Platform, delivering orchestration, lifecycle management, automation, governance, and multi-tenancy capabilities for enterprise AI deployments.
Instead of offering GPU resources alone, the platform enables organizations to provision Kubernetes clusters, virtual machines, AI development workspaces, and inference environments through a secure self-service interface while maintaining centralized policy enforcement and operational visibility.
The solution is designed to simplify AI infrastructure management while supporting scalable enterprise AI operations.
As organizations deploy increasingly powerful AI hardware, software platforms have become essential for transforming infrastructure investments into commercially viable AI services.
"Aolani has always been committed to delivering faster time-to-value for our customers," said Nicholas Chia, CEO of Aolani. "Our customers are at the bleeding edge of AI development, and they need to provision, govern, and scale from day one in an industry that moves at lightning speed. Building the next generation of AI cloud means solving for more than just compute capacity, but also production-grade platforms that enable operational readiness from the get go. That's why we are so excited about this partnership with Rafay."
The announcement reflects a broader shift across the AI infrastructure industry. While GPU availability remains important, organizations increasingly require software platforms capable of automating deployment, enforcing governance, supporting multi-tenant environments, and enabling developers to consume AI services immediately.
The Rafay Platform helps simplify infrastructure bring-up, automate lifecycle management, enforce enterprise governance, and provide developers with production-ready AI environments for model development, training, and inference.
"AI infrastructure has entered a new phase," said Haseeb Budhani, CEO and Co-founder of Rafay Systems. "The question is no longer how quickly organizations can deploy GPUs. It's how quickly they can transform that infrastructure into a governed, self-service platform that developers can use and operators can manage at scale. We're excited to collaborate with Aolani to help demonstrate what's possible with NVIDIA AI infrastructure and accelerate the path from hardware deployment to production AI services."
By combining NVIDIA AI infrastructure with enterprise orchestration capabilities, the joint deployment aims to improve infrastructure utilization, shorten deployment timelines, and help organizations accelerate the delivery of production AI services while maintaining security, governance, and operational control.
Where AI gets built in Asia. Founded in 2023, Aolani's AI factories enable enterprises, AI natives, and sovereigns to build with confidence, scale ambitiously, and move at hyper-speed in the world's fastest-growing AI market. Founded in Singapore and backed by compliant and purpose-built neocloud infrastructure, Aolani delivers the performance capabilities for next-generation AI. For more information, visit www.aolanicloud.com and follow @AolaniCloud on LinkedIn.
Rafay Systems is a leading software provider powering the operators building the AI cloud, including neoclouds, telecommunications providers, enterprises, and sovereign AI operators. The Rafay Platform lets these organizations operationalize GPU and compute infrastructure with self-service automation, governance, and multi-tenancy, spanning bare metal provisioning, infrastructure lifecycle management, virtual machines, Kubernetes, GPU PaaS, AI development environments, and Token Factory for publishing AI models as token-metered inference services. By simplifying orchestration and operations across this stack, Rafay helps operators increase GPU utilization and turn raw infrastructure into monetizable, production-ready AI services, all while maintaining security, consistency, and control. For more information, visit rafay.co.
