For most organizations embracing AI, infrastructure is still the bottleneck. In this clip, Mirantis CTO Shaun O’Meara and VP Randy Bias break down how their k0rdent AI platform helps devs and data scientists stop worrying about plumbing—and start building.

Eliminate Infrastructure Drag

“Data scientists don’t have the background—or the time—to deal with infrastructure setup,” says O’Meara. Mirantis’ strategy is simple: remove barriers, accelerate access, and let AI teams focus on delivering business value.

That means provisioning GPU-based infrastructure should be fast, composable, and secure by design. With k0rdent AI, organizations can deploy AI workflows with less friction, fewer delays, and minimal DevOps overhead.

Composability at the Core

k0rdent isn’t just an automation tool—it’s a repeatable architecture. As Bias explains, “Cloud made infrastructure disappear for developers. AI needs the same abstraction.”

By blending CPU and GPU environments, layering in policy enforcement, and baking in identity, observability, and CI/CD integrations, k0rdent delivers a ready-to-use infrastructure model that supports the real-world workflows of AI teams—without forcing them to understand everything under the hood.

From Platform Engineering to Productivity

Whether you’re building agentic AI applications or managing radiology workloads, the infrastructure underneath should just work. That’s the power of k0rdent: giving teams the tools they need, while letting the complexity fade into the background.