Rafay Platform | Infrastructure Orchestration for AI

Rafay helps neoclouds, telcos, sovereign AI clouds, and enterprises turn infrastructure into self-service, governed services across AI use cases and cloud-native applications. The Rafay Platform orchestrates Kubernetes, VMs, SLURM, bare metal, GPUs, and AI services with the multi-tenancy, policy controls, usage visibility, and automation required to scale from infrastructure to consumption.
Can One Platform Support the Full AI Infrastructure Stack?
The Rafay Platform unifies the operations and consumption of AI infrastructure through a single control plane. Operators can manage bare metal, virtual machines, Kubernetes, SLURM, GPU resources, and AI services from one platform instead of relying on a patchwork of point solutions.
For providers, that creates a consistent foundation for delivering multiple consumption and monetization models across the same AI infrastructure estate.
The result is AI Factories that deliver hypercaler-grade user experience with enterprise controls to customers, while delivering higher margins to the business.
Combat infrastructure lifecycle management complexity. Bring relief to frustrated developers and peace of mind to enterprises and cloud service providers with the Rafay Platform. Cloud-native and AI workload teams can effortlessly manage compute resources in a cloud-like experience across any environment–automating complex operations and accelerating time-to-market.
Centrally enforce enterprise-grade policies and CCOE-approved configuration and software manifests, cost controls, etc. the latest addons, policies and cost controls across all environments, clusters and landing zones.
Automate the lifecycle management of managed Kubernetes services available in public clouds (e.g. EKS, AKS, & GKE) with enterprise-grade controls, highly customizable fleet management capabilities, and more.
Leverage Rafay’s turnkey, fully-managed Kubernetes distribution that scales to meet the needs of the largest enterprises and the most complex service provider environments.
Centralize visibility and attribution of costs to downstream customers and users, along with the application policies to keep overall costs in check.
Provide a turnkey MLOps platform to internal and external users with built-in AI workbenches that data scientists and researchers can leverage on demand across GPUs and CPUs.
AI infrastructure and GPUs aren't an expense; they present an opportunity. The Rafay Platform empowers businesses to deliver CSP-grade use cases to users – from virtual machines to K8s clusters to ML workbenches to high-value, large-language models (LLMs), all delivered as a service – that drive high utilization and high margins.
Deliver self-service experience across public clouds and data center environments. Developers get self-service access to compute and tooling needed to move fast and experiment, while platform teams maintain full control, governance, and cost-efficiency.
With a vast library of Generative AI, compute consumption and infrastructure management built in, enterprises and service providers can deliver “as a Service” experiences at each layer of the stack without investing in massive teams and multiple quarters.
Cloud providers, neoclouds and Sovereign AI clouds who have partnered with Rafay are leading the charge to deliver CSP-grade use cases to their user communities. From agentic applications, ML workbenches, models as a service, to highly tuned virtual machines, K8s clusters and baremetal servers, Rafay is the partner of choice for the most innovative GPU providers in the world.
Learn why so many enterprises and service providers choose the Rafay Platform for their modern infrastructure needs With the Rafay Platform, customers:
Understand what it takes to deliver the right GPU infrastructure to your business.