AI Cloud Maturity Model
A Phased Approach to Building Profitable, Scalable GPU Clouds
GPU cloud providers face a common challenge: turning capital-intensive AI hardware investments into scalable, profitable revenue streams as fast as possible. But building the operational capabilities — bare metal automation, Kubernetes orchestration, GPU virtualization, observability, and a service catalog — takes months of engineering effort and expertise that many teams don't have.
The AI Cloud Maturity Model gives service providers a clear, phased roadmap for building GPU cloud infrastructure that grows with their business. It defines three stages of AI cloud capability — from automated bare metal delivery to a fully self-service cloud experience — with an NVIDIA-validated stack that reduces risk and accelerates time-to-production at every step
Download this handout to learn:
The three stages of AI cloud maturity and what operational and revenue milestones define each one
How to start generating cloud revenue immediately without months of custom integration work
How hardware-enforced multi-tenancy enables sovereign and private AI while improving GPU utilization and unit economics
How a self-service AI cloud lets revenue scale faster than OpEx — and how k0rdent AI's NVIDIA AI Cloud Ready Initiative validation supports full automation at scale
What capabilities are delivered at each stage, and how Mirantis Professional and Managed Services can accelerate your path forward
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