AI Infrastructure Orchestration Platform | Rafay

Rafay helps neoclouds, sovereign AI clouds, Telcos, and enterprises turn GPU infrastructure into self-service, governed AI cloud services, from Token Factory and inferencing to Kubernetes, SLURM, bare metal, and VMs.
Whether you’re building a neocloud, launching a sovereign AI cloud, or scaling enterprise AI, Rafay helps you move up the stack from GPU capacity to self-service compute, packaged environments, and monetized AI services.
Neoclouds need to stand out beyond raw GPU availability. Rafay helps GPU-first cloud providers turn infrastructure into a full AI cloud platform with self-service access, multi-tenant governance, packaged compute, usage visibility, and higher-value AI services.
One of Canada's largest telecoms built a production-grade AI Studio — a sovereign environment for enterprises, startups, and research institutions to build and deploy AI applications.
Sovereign AI clouds must deliver local control, governed access, and production-grade AI services. Rafay helps operators turn in-region GPU infrastructure into a secure, multi-tenant AI cloud where users can consume compute, models, and AI services within required boundaries.
One of Canada's largest telecoms built a production-grade AI Studio — a sovereign environment for enterprises, startups, and research institutions to build and deploy AI applications.
Enterprise AI stalls when platform teams are forced to manually provision environments, enforce access, and manage fragmented infrastructure. Rafay gives developers and data scientists governed self-service access to the compute and AI services they need, while platform teams retain control over cost, policy, and usage.
The precision oncology company runs Kubernetes across on-prem and cloud with Rafay, enabling developers to build, test, and deploy faster without sacrificing control.
AI clouds span GPUs, clusters, storage, networking, tenants, and services. Rafay Observability gives operators a multi-tenant view across the data center, with AI-assisted dashboards, synthetic monitoring, automated triage, and workflow-driven remediation so teams can see what is happening, understand why it is happening, and act faster.
The precision oncology company runs Kubernetes across on-prem and cloud with Rafay, enabling developers to build, test, and deploy faster without sacrificing control.
AI factories create more value when users consume models and APIs, not just infrastructure. Rafay Token Factory helps organizations expose AI services through governed APIs, track usage at the token level, and monetize consumption across teams, tenants, and customers.
The precision oncology company runs Kubernetes across on-prem and cloud with Rafay, enabling developers to build, test, and deploy faster without sacrificing control.
Rafay helps platform teams and cloud providers convert GPU infrastructure into standardized compute services. Offer users the right abstraction for the job, including bare metal, VMs, Kubernetes, SLURM, containers, notebooks, and AI workbenches, all delivered through self-service.
One of Canada's largest telecoms built a production-grade AI Studio — a sovereign environment for enterprises, startups, and research institutions to build and deploy AI applications.
Kubernetes remains a critical foundation for AI and cloud-native workloads, but it should not be the whole story. Rafay helps teams manage Kubernetes consistently across environments while connecting it to the broader AI factory operating model: self-service, multi-tenancy, governance, and workload automation.
A global consulting firm modernized a Rancher stack that had become too costly and complex to operate, migrating to Rafay with enterprise-grade controls intact.
Measured production data showing how GPU operators can boost annual revenue per GPU by 2x–4.8x by shifting from hourly rental to token-metered AI services.
This white paper breaks down what it actually takes to turn GPU investments into measurable business outcomes.
This playbook outlines a practical, phased approach for telecommunications providers to transform existing GPU infrastructure into a revenue-generating AI Factory in as little as 12 weeks.
Understand what it takes to deliver the right GPU infrastructure to your business.
Cisco provides AI-optimized infrastructure. Rafay makes it usable across teams, tenants, and use cases in days.
AI Token Factory extends the Rafay Platform to deliver AI services through APIs and token-metered consumption. Production-ready AI APIs run on GPU infrastructure while maintaining governance, multi-tenancy, and operational control. Token-metered consumption provides visibility into usage and enables internal chargeback or monetization models.
Orchestrating the future of AI: The CIO’s guide to scalable, compliant, and developer-ready AI deployment
Rafay's central orchestration platform facilitates efficient, self-service infrastructure and AI application management.
Evaluating how the Rafay Platform delivers a GPU cloud for enterprises and cloud service providers by PivotNine.
This paper explores the key challenges that organizations experience supporting these initiatives, as well as best practices for successfully leveraging Kubernetes to accelerate AI/ML projects.
Talk with Rafay experts to assess your infrastructure, explore your use cases, and see how teams like yours operationalize AI/ML and cloud-native initiatives with self-service and governance built in.