Unlock Your AI Potential with Cisco and Rafay: Transform AI PODs into a Self-Service GPU Cloud
Cisco provides AI-optimized infrastructure. Rafay makes it usable across teams, tenants, and use cases in days.
EVENT
Dell Technologies World 2026
Rafay + Dell: Powering AI Factories Worldwide
Trusted by leading Sovereign Clouds & Neoclouds to operate AI at scale
Meet with us at booth #113
At Dell Technologies World, the focus is clear: turning AI infrastructure into real-world outcomes. Dell AI Factory and APEX deliver the foundation—secure, scalable, and built for performance.
Rafay extends that foundation into a fully operational AI platform.
We help organizations transform deployed GPU infrastructure into self-service, governed AI environments that teams can actually consume. By enabling multi-tenant access, policy-driven control, and developer-ready experiences, Rafay closes the gap between infrastructure investment and AI in production.
Together, Rafay and Dell enable AI Factories that are not just built—but usable, scalable, and ready to deliver results across the enterprise.
Visit us to see how leading Sovereign Clouds and Neoclouds are accelerating from infrastructure to AI services—faster, more efficiently, and at global scale.
Rafay's Valued Partnerships:
Featured Resources
AI Factory FAQs
Learn how Rafay helps companies go from idle and expensive GPUs to building fully-scaled AI factories to accelerate AI and ML innovations.
Who uses AI factories?
AI factories are used by enterprises, cloud service providers, and sovereign AI clouds that need to scale AI workloads efficiently, maximize GPU utilization, and deliver AI as a production service rather than isolated projects. You can see how Rafay worked with Canadian telecommunications provider Telus in this case study.
What role does Rafay play in AI factories?
Rafay provides the control plane for AI factories, handling orchestration, multi-tenancy, governance, and self-service access to AI infrastructure across cloud, on-prem, and sovereign environments.
Is Rafay an AI factory?
Rafay is not a GPU manufacturer or model provider. Rafay provides an infrastructure orchestration and consumption platform that enables organizations to operate AI factories by turning AI infrastructure into a governed, self-service platform.
Does Rafay support NVIDIA NIMs/NIM?
Yes, Rafay supports NVIDIA NIM (NVIDIA Inference Microservices). NIM is NVIDIA’s proprietary solution for delivering packaged inferencing capabilities. It comes pre-configured with NVIDIA’s in-house models and has been optimized for use with a wide range of open-source models, including Meta’s Llama variants. While NIM is often viewed as an alternative to the open-source kServe package, Rafay’s platform supports both NIM and kServe. This flexibility allows customers to choose their preferred inference endpoint and deploy it effortlessly on GPU instances using the Rafay platform. By supporting multiple inferencing solutions, Rafay enables organizations to leverage the most suitable tools for their specific AI/ML needs while maintaining a consistent and manageable infrastructure.
How is Rafay different from Run.AI?
Run:AI focuses on providing fractional/virtualized GPU consumption and a proprietary scheduler optimized for AI/GenAI workloads, replacing the default Kubernetes scheduler. Rafay, however, provides a more comprehensive platform that manages the full lifecycle of underlying Kubernetes clusters and environments. Rafay offers an out-of-the-box experience to deploy and consume Run:AI on Rafay’s GPU PaaS, while also providing its own GPU virtualization and AI-friendly Kubernetes scheduler for customers preferring a single-vendor solution. Essentially, Rafay can either complement Run:AI’s offerings or provide a standalone solution that covers similar functionalities along with broader infrastructure management capabilities, giving customers flexibility in their AI infrastructure choices.
Does Rafay offer a GPU PaaS?
Yes, Rafay provides infrastructure orchestration and workflow automation for cloud-native (Kubernetes) and AI use cases for enterprises, cloud providers, neoclouds, and Sovereign AI clouds. Rafay helps companies deploy a Platform-as-a-Service (PaaS) experience that supports both CPU-only and GPU-accelerated compute environments. Platform teams can quickly set up and deliver customized self-service experiences for developers and data scientists, typically within days or weeks. This flexible platform allows end-users to easily access the computational resources they need, whether it’s standard CPU processing or more powerful GPU capabilities. Rafay’s solution streamlines the deployment and management of diverse computing environments, making it easier for organizations to support a wide range of applications, from standard software to complex AI/ML projects.
