As AI agents move beyond demos, the real challenge becomes giving them reliable, structured access to enterprise systems. This talk walks through how we evolved a unified data platform into an agent-ready platform using a semantic layer, knowledge graph principles, and MCP-based tool abstractions. We'll cover how structure—not just models—enables reasoning, governance, and cross-system workflows. The focus is on practical design patterns that make agents usable in real production environments.
Sunil is an Engineering Architect focused on building production-grade AI and data platforms at scale. With over 20 years of experience across companies like Harness, Traceable AI, Cisco (AppDynamics), Aruba, and Juniper, his work spans distributed systems, knowledge graphs, API security, and real-time analytics. He currently leads enterprise Data and AI Platform initiatives at Harness, including knowledge graph–driven RAG systems and agentic AI workflows. He has contributed to multiple U.S. patents and writes about bridging traditional systems engineering with modern AI architectures.
