As AI-powered cloud-native applications evolve, ensuring trust, compliance, and robustness requires dynamic governance mechanisms that operate seamlessly across distributed environments. This keynote introduces a multi-layered cloud-native framework that enforces AI guardrails at three critical stages: pre-processing (input validation), inference (real-time bias mitigation), and post-inference (output validation).

By leveraging Kubernetes orchestration, Istio service mesh, and knowledge graphs, the framework enables scalable AI governance that integrates multi-agent coordination, real-time intervention, and traceability to ensure AI decisions remain transparent, auditable, and aligned with compliance requirements.

Attendees will gain insights into cloud-native AI governance patterns, practical deployment strategies, and the role of multi-agent oversight in ensuring compliant, production-ready AI workflows within Kubernetes environments.