The RAFAY PLATFORM - For neoclouds

Build, Operate and Monetize a Neocloud with Rafay

Neoclouds use the Rafay Platform to launch CSP-grade services without building from scratch. The Rafay Platform delivers everything required to operationalize and monetize GPU infrastructure: self-service consumption, multi-tenancy, SKU automation, billing APIs, and a white-labeled portal, to turn GPU investments into revenue-ready clouds in weeks.

What Is a Neocloud Provider?

A neocloud provider is a specialized cloud provider built primarily to deliver accelerated computing and AI services. Neoclouds typically offer GPU infrastructure, packaged compute environments, AI development platforms, and inference services optimized for training, fine-tuning, and production AI workloads.

AI Services You Can Launch with Rafay

GPU Infrastructure Services

Deliver bare metal and GPU capacity through governed, self-service workflows with automated provisioning, tenant isolation, inventory management, and usage tracking.

Packaged Compute Services

Offer virtual machines, Kubernetes, virtual clusters, SLURM, containers, and fractional GPU configurations as standardized, reusable SKUs.

AI Development Environments

Provide developers and data scientists with notebooks, workbenches, training environments, fine-tuning workflows, and curated AI tools.

Model and Token Services

Expose models through governed APIs with tenant controls, usage metering, rate limits, and token-based billing.

Core Capabilities for Neocloud Providers

Multi-Tenancy & Governance

Manage multiple organizations, teams, and users with fine-grained isolation and policy controls. Enforce quotas, role-based access, and security policies across every tenant while maintaining centralized visibility and governance.

Infrastructure and Workload Orchestration

Automate server provisioning, networking, storage integration, and lifecycle operations across bare metal, virtual machines, Kubernetes, SLURM, and AI workloads.

Self-Service Access

Empower developers and data scientists with on-demand environments, without IT bottlenecks. Accelerate onboarding and reduce manual provisioning by delivering approved services through APIs or branded self-service portals.

SKU Automation

Standardize small, medium, and large GPU/CPU packages for seamless consumption. Package infrastructure into reusable service offerings that simplify provisioning, improve consistency, and speed up service delivery.

Billing & CRM Integration

Placeholder

Frequently Asked Questions About Neoclouds for AI Infrastructure

What counts as a node?
A node is a physical or virtual server/machine.

Do you have any volume discounts?
Yes! As the number of nodes increases, the price per cluster or per node decreases.

What about short-lived or ephemeral clusters?
Our customers love to experiment, and we don’t ding them for it. We don’t charge for node count spikes but look at the running average of nodes in use when calculating usage.

Is there a difference between production and non-production pricing?
The management overhead for helping our customers operate dev vs prod clusters is effectively the same, so we treat all nodes the same.

What if I use more nodes than I’ve licensed?
Rafay has a true-up forward policy, meaning that we don’t carry out chargebacks for scenarios where the consumption in a completed billing cycle exceeded the licensed count. If the new, steady-state number of nodes is expected to be higher, our customer success team will discuss the situation with you and take steps to adjust billing accordingly for the next billing cycle.

How much does Enterprise Support (24x7x365) cost?
Enterprise Support is available at an additional fee equaling 20% of the cluster or node subscription.

Do you have EDU or GOV discounts?
Yes, please contact sales for more information about discounts for educational institutions and government agencies.

What is a neocloud provider?
A neocloud provider is a cloud provider focused on delivering AI infrastructure and accelerated computing services. Unlike general-purpose cloud providers, neoclouds package GPU infrastructure, compute environments, AI development platforms, and inference services for AI training, fine-tuning, and production workloads.

What does a neocloud platform need?
A successful neocloud platform requires more than GPU infrastructure. Providers need capabilities for infrastructure orchestration, multi-tenancy, governance, self-service provisioning, service catalogs, usage metering, and billing integration to deliver AI services efficiently and at scale.

How does Rafay help build a neocloud?
Rafay provides the platform for building and operating a neocloud by automating infrastructure provisioning, standardizing service delivery, enforcing governance policies, and enabling secure self-service access. This helps providers launch AI services faster without building and maintaining their own cloud management platform.

How does Rafay improve GPU utilization and margins for neoclouds and GPU cloud providers?
Rafay increases GPU utilization by enabling shared, fractional GPU consumption through NVIDIA MIG partitioning and time-slicing, which allow multiple workloads or tenants to share physical GPUs that would otherwise sit idle between large training jobs. Quota-based allocation and self-service provisioning keep more of the fleet active at any given time, reducing the stranded capacity that drives down utilization rates. On the margin side, Rafay helps providers move up the value stack from commodity GPU-hour rental toward token-metered AI services — which command stronger price points and higher margins than raw compute. Providers can offer foundation, compute, and AI SKUs additively on the same fleet, shifting their revenue mix toward AI services without re-platforming.

How quickly can a neocloud go from raw GPUs to billable services with Rafay?
A neocloud can typically reach its first billable AI services in approximately six to eight weeks using the Rafay Platform, compared to the many months a from-scratch platform build would require. Rafay provides the multi-tenant operating layer, self-service portal, SKU design tools, metering engine, and billing integration that neoclouds would otherwise need to build themselves. Once the platform is running, operators can expand their service catalog — adding new GPU SKUs, inference endpoints, or AI service tiers — without re-platforming. The accelerated timeline means neoclouds can begin generating token-metered revenue while their infrastructure is still scaling, rather than waiting for a complete build-out.

How does multi-tenancy work for neoclouds sharing a GPU fleet across customers?
Rafay enforces hard multi-tenancy so many customers can share one GPU fleet without sharing blast radius, data, or network access. Network isolation is implemented with per-tenant VRF and VLAN for north-south traffic and InfiniBand PKEY isolation via NVIDIA UFM for east-west GPU traffic. Each bare metal tenant receives a dedicated provisioning head node, and storage uses dedicated namespaces, access zones, and per-tenant bucket policies. Operators govern the entire fleet from a single control plane while every tenant remains cleanly separated — with their own quotas, RBAC policies, and performance isolation that prevents noisy-neighbor effects.

What services can neocloud providers launch with Rafay?
Providers can deliver bare metal, virtual machines, Kubernetes clusters, SLURM clusters, AI workspaces, applications, Model-as-a-Service offerings, and token-metered AI APIs through a governed, self-service platform.

How does Rafay support multi-tenant AI infrastructure?
We provide tenant isolation, role-based access controls, policy enforcement, and quota management that allow multiple teams, customers, or business units to securely share infrastructure while maintaining governance and operational consistency.

How does Rafay enable Model-as-a-Service and inference-as-a-service?
Rafay enables organizations to package models, inference endpoints, and AI tooling into governed, self-service services. Through multi-tenancy, usage metering, policy controls, and service catalogs, organizations can deliver and monetize AI capabilities at scale.

Can I white-label the Rafay customer portal under my own brand?
Yes. The Rafay platform supports full white-label customization, so GPU cloud providers and neoclouds can present the self-service portal entirely under their own brand. Logo, colors, domain name, and product name are configurable per white-labeled partner. Language, number format, currency display, and unit systems are configurable at the tenant level. This delivers a branded, hyperscaler-style self-service experience to end customers without building a portal from scratch.

Can GPUaaS be deployed in sovereign or air-gapped environments?
Yes. GPUaaS can be deployed in sovereign, private, and fully air-gapped environments to meet data residency, security, and regulatory requirements while providing controlled access to GPU resources.