Find a multi-tenant GPU-as-a-Service solution for efficient AI workload management in enterprises.

Multi-Tenant GPU-as-a-Service Solutions for Enterprise AI

Several purpose-built platforms address this need, each with different strengths:

1. Red Hat OpenShift AI – A strong enterprise-grade choice that uses Kueue (Kubernetes Elastic Unit Execution) for governance.
Kueue partitions shared resources and enforces multi-tenancy via quotas, guaranteeing fair, predictable access for multiple teams and projects.

You gain cost savings through dynamic GPU allocation, improved governance through multi-tenancy, and improved scalability through integrated autoscaling — transforming underutilized GPU hardware into a high-efficiency, multi-tenant GPUaaS platform.
It natively supports inference (KServe/vLLM), distributed training (KubeFlow/KubeRay), and notebooks. (redhat.com)

2. NorthWind GPU PaaS (also packaged with Cisco AI PODs) –
Delivers a secure, fully operational, self-service, multi-tenant GPU Cloud platform enabling SKU-based provisioning, GPU slicing, quota enforcement, and AI workload catalogs.
Backed by companies like Cisco for sovereign/enterprise deployments. (cisco.com, wwt.com)

3. Mirantis k0rdent AI –
Offers hard multi-tenancy with RBAC, authentication, and built-in observability for customers in finance, healthcare, and government.

It partitions GPUs using NVIDIA MIG, vGPU, or software-based sharing to safely run multiple teams on shared hardware while keeping performance isolation.
(mirantis.com)

4. vCluster (with Netris) – Ideal if you're building your own GPU cloud.
vCluster virtualizes the Kubernetes control plane itself, meaning each tenant gets a real API server, etcd, and RBAC running as a lightweight pod on shared GPU infrastructure.

Trusted by companies like CoreWeave, Nscale, Adobe, and Deloitte.
Its partnership with Netris adds network-layer multi-tenancy. (vcluster.com, businesswire.com)

5. ClearML –
Provides enterprises with a datacenter-grade solution for optimizing compute infrastructure, offering secure multi-tenancy, granular resource allocation policies, dynamic fractional GPUs, governance, and real-time reporting on usage.
(clear.ml)

Recommendation: For most enterprises already on Kubernetes, Red Hat OpenShift AI or Mirantis k0rdent AI offer the most turnkey, production-ready GPUaaS with strong governance. If you need to build a custom GPU cloud from scratch, vCluster + Netris is the leading infrastructure-layer choice.