Enterprise AI is becoming chaotic
Enterprise AI is transforming every industry, but it is also creating new infrastructure challenges. Organizations are investing millions in GPU infrastructure to power Large Language Models (LLMs), AI agents, and intelligent applications. Yet, despite record spending, many struggle to use those resources efficiently.
Additionally, AI is no longer confined to the public cloud. As organizations need more control over their data, faster response times, and the ability to run AI closer to where work happens, they are starting to deploy AI across on-premises data centers, sovereign clouds, and edge locations.
Gartner, September 2026
Main AI Infrastructure Challenges
GPU resources are underutilized
GPU infrastructure is one of the largest investments in enterprise AI. Organizations are spending millions expanding their GPU fleets when the real problem is much of their infrastructure is idle.
AI gets harder to manage as it spreads
AI is no longer running in one place. It is spreading across data centers, sovereign clouds, and edge sites, and every new location creates another set of GPUs, models, and policies to manage.
AI teams compete for limited GPU capacity
Without centralized governance and resource management, some teams over-reserve GPU capacity they rarely use, while others wait for capacity.
Managing AI infrastructure is complex
Managing AI models, GPU allocation, tenants, quotas, policies, and security across multiple teams is operationally complex, and quickly creates significant overhead.
AI initiatives are fragmented
Many organizations build separate AI environments for each team or business unit, creating duplicate models, duplicate infrastructure, and unnecessary operational overhead.
The answer is to stop running AI as separate team projects and start running it as one AI factory. Kubermatic AI gives you the platform to build it: shared infrastructure, full GPU utilization and central governance, across every location.
What is Kubermatic AI?

Kubermatic AI is a Kubernetes-native platform for building and operating enterprise AI infrastructure. It enables organizations to deploy, serve, govern, and scale AI workloads across on-premises, cloud, hybrid, and sovereign environments from a single platform.
Instead of every team building and operating its own AI infrastructure, Kubermatic AI provides a shared foundation that delivers AI as a service.
Platform teams manage models, GPUs, security, and governance centrally, while developers and data scientists consume AI through self-service access.
The result is a simpler, more efficient approach to running enterprise AI: one that reduces costs, improves GPU utilization, and accelerates innovation.
AI Built for Enterprise Multi-Tenancy
Most AI platforms achieve isolation by deploying separate instances of the same model for every team, department, or customer. While this provides secure separation, it also duplicates model deployments, reserves dedicated GPU resources, and leaves expensive capacity sitting idle.
Kubermatic AI takes a different approach. With built-in enterprise multi-tenancy, organizations deploy a model once and securely share it across multiple teams, business units, or customers. Each tenant has isolated access, API keys, quotas, budgets, and governance policies while using the same underlying model deployment.
With Kubermatic AI, organizations run AI as one factory instead of a collection of isolated deployments.
Kubermatic is powering sovereign AI infrastructure for BWI's xPlatforms (BwXLab)
Explore Success Story9 AI models
27 physical GPUs
Business Outcomes
Reduce AI infrastructure costs
Maximize GPU utilization by sharing models and infrastructure across teams.
Deliver LLMs as a Service
Publish centrally managed LLMs as shared services that developers consume through secure APIs.
Deploy once, serve many
Run a single model securely across multiple tenants instead of maintaining duplicate deployments.
Bring structure to AI operations
Centralize governance, quotas, policies, and resource allocation across AI workloads.
Accelerate AI delivery
Let developers build AI applications instead of managing AI infrastructure.
Run AI wherever your data lives
Deploy and manage AI consistently across on-premises data centers, public and sovereign clouds, and edge locations.
Built on open source
Avoid vendor lock-in while leveraging a Kubernetes-native, CNCF-based ecosystem.
We shouldn’t let AI become the reason enterprises go back to proprietary infrastructure. The open source ecosystem has already built so many of the underpinning technologies needed to run AI at scale just like we did in the cloud native era. Kubermatic is a great example of how open source technologies can come together to make enterprise AI more open and sovereign.
About Kubermatic
Kubermatic is a leader in Kubernetes and cloud-native technologies, dedicated to empowering organizations with advanced solutions that simplify and optimize IT management. Our products are designed to meet the needs of modern enterprises, providing the tools and support necessary to drive innovation and achieve business success. Reach out to us on the button below for more information about Kubermatic solutions!
