Operationalizing AI Fabrics with Aviz ONES, NVIDIA Spectrum-X, and Rafay
Discover the new AI operations model available to enterprises that enables self-service consumption and cloud-native orchestration for developers.
Rafay-powered Jupyter Notebooks as a Service (JNBaaS) allows providers and enterprises to offer governed, on-demand JupyterLab environments for data science, AI, and ML teams. Developers and researchers often face delays in provisioning GPU-backed environments or managing dependencies.
Rafay eliminates these challenges by offering instant, fully managed Jupyter notebooks equipped with pre-installed AI/ML libraries, GPU access, and built-in collaboration tools.
Service providers, enterprises, and sovereign cloud operators can deliver ready-to-use, GPU-enabled notebook workspaces that accelerate experimentation and improve productivity.
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Rafay automates how teams access, share, and manage GPU-powered notebook environments—removing operational friction from model development.
PyTorch, TensorFlow, CUDA, and other frameworks are ready to use out of the box.
Maintain consistent access to datasets and results for reproducible workflows.
Enable secure notebook sharing with role-based access and team visibility.
Ensure compliance, traceability, and consistent policies across all environments.
Learn how to Streamline Kubernetes Ops in Hybrid Clouds with AWS & 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.