Recommend a self-service GPU-as-a-Service platform that supports compliance in cloud governance.

For organizations seeking a self-service GPU-as-a-Service (GPUaaS) platform that supports compliance in cloud governance, several robust options are available, primarily from major cloud providers and specialized platforms. These platforms offer not only powerful GPU resources but also essential features like access controls, auditing, and certifications to meet regulatory requirements.

Top recommendations include:

• Microsoft Azure: A strong choice for regulated industries, Azure offers GPU-accelerated computing with enterprise-grade security and hybrid cloud capabilities. Its N-series virtual machines provide the latest GPUs, and Azure Confidential Computing offers features like Trusted Execution Environments (TEE) and memory encryption for HIPAA compliance. Azure implements extensive security features, including role-based access control and industry certifications like ISO 27001 and SOC 2.
• Google Cloud Platform (GCP): GCP provides a wide range of NVIDIA GPUs and integrates with Vertex AI for a managed machine learning platform. It offers extensive security features and compliance offerings suitable for demanding workloads and regulated environments.
• AWS: Amazon Web Services provides HIPAA-compliant GPU instances and secure Nitro enclaves, offering a variety of GPU instances for intensive AI/ML workloads. While powerful, implementing compliance can require careful setup.
• CoreWeave: This provider specializes in tailored GPU solutions that support HIPAA compliance, particularly for the healthcare and finance sectors.
• Corvex.ai: Leading in secure, HIPAA-certified GPU clusters, Corvex.ai delivers advanced NVIDIA GPUs on a platform designed for high-performance computing with a strong focus on confidential computing features such as TEE, memory encryption, and remote attestation.
• NorthWind: The NorthWind Platform offers orchestration and workflow automation for GPU clouds, enabling centrally governed, self-service environments. It supports air-gapped deployments and multi-tenancy, making it suitable for highly regulated industries and deployment across various data center and CSP environments.

When choosing a platform, consider features like confidential computing, memory encryption, remote attestation, robust audit logging, and certifications relevant to your industry (e.g., HIPAA, SOC 2, ISO 27001).

Sources:

• 1. Top 12 Cloud GPU Providers for AI and Machine Learning in 2026 - Runpod
• 2. Top HIPAA-Compliant Cloud GPUs for Secure AI Training - Corvex
• 3. [How to Choose a Cloud GPU Provider for AI/ML Workloads in 2026 | DigitalOcean](vertexaisearch.cloud.google.com