Naveen Punjabi

Building a production-ready AI strategy requires more than just a model; it requires a unified foundation that handles massive scale without sacrificing governance. In this session, we’ll deep dive into the technical framework powering the next generation of data intelligence.We’ll explore how to build a unified platform that bridges the gap between massive-scale data engineering and downstream AI-driven insights. We'll focus on: 1. How to optimize TCO using Google Cloud’s auto-scaling compute for Databricks workloads. 2. How the Knowledge Catalog and Unity Catalog federation enables a "single pane of glass" for governance, allowing teams to query sensitive records across platforms without data movement. 3. Leveraging Vertex AI and Databricks to move from raw data to intelligent document processing and risk assessment. 4. Why an open-source foundation is the key to avoiding vendor lock-in and maintaining multi-cloud flexibility.

This session unveils Google Cloud's Agent2Agent (A2A) protocol, ushering in a new era of AI interoperability where diverse agents collaborate seamlessly to solve complex enterprise challenges. Join our panel of experts to discover how A2A empowers you to deeply integrate these collaborative AI systems with your existing enterprise data, custom APIs, and critical workflows. Ultimately, learn to build more powerful, versatile, and securely managed agentic ecosystems by combining specialized Google-built agents with your own custom solutions (Vertex AI or no-code). Extend this ecosystem further by serving these agents with Databricks Model Serving and governing them with Unity Catalog for consistent security and management across your enterprise.