AI platforms in regulated sectors like insurance demand not only performance and scalability, but governance, auditability, and trust built directly into the runtime.

This session explores how k0s, a single-binary k8s distribution, combined with Kata Containers, provides a minimal yet powerful foundation for governed AI workloads.
By embedding isolation, attestation, and policy enforcement at the cluster core, we demonstrate how governance is not an add-on, it's intrinsic.
Each model or inference workload runs inside a micro-VM, ensuring data isolation and verifiable execution and aligning with emerging CNCF AI Conformance principles.

Attendees will learn how to build reproducible, secure AI environments, from data center to edge. where governance starts at the infrastructure layer, not the application tier.

Takeaway: A practical blueprint for secure, compliant, and observable AI in insurance.