GPU PaaS

Effortlessly manage and optimize GPUs across multiple racks in your data center or across CSP environments

Dynamically match end-user needs with the optimal environment based on proximity, cost efficiency, GPU type, etc. Virtualize GPUs for sub-GPU sharing to get the most out of your GPU hardware

Let developers and data scientists select from an array of preconfigured GPU workspaces on demand, sized by the number of GPUs, cores, amount of memory, and storage options

Supply pre-configured workspaces for AI model development, training and serving/inferencing with all required AI tools, such as Jupyter Notebooks and model registries, so your data scientists can be productive quickly

Leverage Rafay’s robust, multi-tenancy capabilities to support hundreds of internal or external customers from a single pane of glass. Each customer operates as a separate tenant, ensuring data isolation and security, while supporting multiple users within each environment

Take charge of your limited GPU resources with our comprehensive administrative tools designed for service providers and enterprise IT. Enforce policies that control usage and prevent wastage, ensuring that your resources are used efficiently and effectively