Rafay-Powered AI Inference as a Service

Rafay-powered Inference as a Service enables providers and enterprises to deploy, scale, and monetize GPU-powered inference endpoints optimized for large language models (LLMs) and generative AI applications.

Organizations can deliver LLM-ready inference services using supported inference engines such as vLLM, NVIDIA Dynamo, NVIDIA NIM microservices, SageMaker, and NemoClaw.

They expose Hugging Face and OpenAI-compatible APIs, making it easy to serve production workloads securely and efficiently.

• Instant Deployment: Launch vLLM-based inference services in minutes through a self-service interface. ‍
• GPU-Optimized Performance: Leverage efficient GPU utilization through vLLM's optimized runtime and configurable resource allocation.
• Flexible Scaling: Scale inference endpoints by adding replicas, with traffic load-balanced across them for consistent throughput.

Simplify Inference Management at Scale

Rafay enables organizations to manage AI inference workloads at scale while maintaining high performance, compliance, and cost efficiency.

vLLM Runtime Integration

Use vLLM’s optimized runtime to serve large models with low latency and high throughput.

Distributed Inference Scaling

Scale workloads across GPUs and nodes with automatic balancing.

API Compatibility

Support Hugging Face and OpenAI-compatible endpoints for easy integration with existing AI ecosystems.

Governance and Policy Control

Enforce consistent performance and auditability through centralized management.

Why Choose Rafay for AI Inference as a Service?

Whether you're building an internal AI platform or launching managed inference services as a GPU cloud provider, Rafay simplifies the deployment and operation of production-ready AI inference. We combine GPU orchestration, self-service provisioning, multi-tenancy, governance, and usage metering to help organizations deliver secure, scalable inference services with less operational overhead.

With Rafay, you can:

• Launch self-service inference services without building custom platforms.
• Deliver secure, multi-tenant environments with enterprise governance.
• Maximize GPU utilization through automated resource management.
• Support sovereign and air-gapped deployments for regulated industries.
• Simplify lifecycle management for inference infrastructure and AI workloads.

Deliver Production-Ready AI Inference with Governance and ROI

Expose inference endpoints as high-demand service SKUs to maximize GPU ROI.

Deliver self-service APIs with predictable latency, throughput, and elastic capacity.

Offer compliant, in-region inference services with full governance and auditability.

Automate endpoint creation, scaling, and policy enforcement to reduce operational overhead.

Benefits of Rafay-Powered AI Inference as a Service

Faster AI Deployment

Launch production-ready inference endpoints in minutes rather than building and managing the infrastructure yourself.

Lower Operational Overhead

Automate provisioning, scaling, governance, and lifecycle management across inference workloads.

Better GPU Utilization

Maximize infrastructure efficiency through optimized scheduling, dynamic scaling, and resource sharing.

Enterprise Governance

Enforce policies, access controls, and compliance requirements across environments from a central platform.

Monetization Opportunities

Turn GPU infrastructure into revenue-generating inference services with self-service access and usage-based consumption models.

Production Readiness

Deliver reliable, scalable inference services with built-in automation, observability, and operational controls.

Common Use Cases of Our AI Inference Services

Rafay-powered AI Inference as a Service helps organizations deploy and manage inference workloads across a wide range of production AI use cases, including:

For Cloud Providers:

• Offer managed LLM APIs to enterprise customers through secure, self-service inference endpoints.
• Monetize GPU infrastructure by delivering hosted inference services with usage-based consumption models.
• Deliver sovereign AI services for customers with strict data residency, security, and compliance requirements.
• Launch differentiated AI offerings that complement GPU-as-a-Service and expand your AI service portfolio.

For Enterprises:

• Power AI assistants and copilots with scalable, production-ready inference services.
• Deploy private AI applications while maintaining centralized governance and policy controls.
• Run retrieval-augmented generation (RAG) workloads with GPU-accelerated inference for knowledge-intensive applications.
• Standardize AI inference across teams through self-service access, automation, and centralized operations.

FAQs

Find answers to common questions about our Rafay-powered inference services below.

• 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 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...

Start a conversation with Rafay

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.