Architecting Enterprise AI Agents: Secure, Governed, and Interoperable
Everyone is building "Chat with your data" applications, but moving them from a simple prototype to a secure, reliable enterprise-grade service is a monumental challenge. How does an agent navigate a labyrinth of hundreds of datasets to find the right one for a user's query? How does it integrate a growing ecosystem of specialized data tools alongside those datasets? And critically, how do you ensure it respects user permissions and interacts with other systems safely?
This talk presents a practical blueprint for building robust AI agents in a large enterprise environment. We will demonstrate a solution that allows users to chat with structured data to get answers, insights, and visualizations. Crucially, we will dive deep into the architecture that enables the agent to dynamically discover the most relevant datasets and tools for a given task, all while inheriting and restricting permissions based on the end-user's identity, preventing unauthorized data access. You will learn how to build a controllable, interoperable, and observable ecosystem of agents using standard protocols for dynamic tool discovery and governed communication.