.webp) # **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](/content/solutions/generative-ai/index.html). 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](/content/platform/multi-tenancy-infrastructure/index.html), 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](/content/solutions/gpu-paas-for-service-providers/index.html) 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 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 inference as a service? Inference as a Service is a managed cloud service that provides on-demand access to AI inference endpoints. It enables organizations to deploy, scale, and manage large language models (LLMs) and other AI models without building and operating the underlying GPU infrastructure. Which LLMs are supported? Rafay supports open-source and custom large language models that run on vLLM, including models available through Hugging Face. Organizations can deploy the models that best fit their performance, cost, and compliance requirements. Can I route inference based on sovereignty requirements? Yes. Rafay enables policy-driven inference routing based on data residency, sovereignty, compliance, latency, capacity, and cost requirements. Organizations can ensure that inference requests are served only from approved regions or infrastructure locations, helping meet regulatory obligations while maintaining performance and availability. Does Rafay support OpenAI-compatible APIs? Yes. Rafay-powered inference endpoints support OpenAI-compatible APIs, making it easier to integrate AI applications and tools without significant code changes. Can I run my own models? Yes. Organizations can deploy and manage their own supported AI models alongside open-source models, giving them full control over model selection, performance, and data governance. 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.