sessionTrack B

Building Data Infrastructure for Agentic AI

Day 1
10:45-11:45
Track B

About This Session

Essential data infrastructure patterns and architectures needed to support autonomous AI agents at scale, including storage, pipelines, and real-time processing.

AI agents have unique data infrastructure requirements that differ from traditional applications. They need access to real-time data, historical context, structured and unstructured information, and the ability to write back insights and decisions.

This session covers the essential components of agent-ready data infrastructure, including streaming data pipelines, event-driven architectures, vector stores, graph databases, and data governance frameworks that enable autonomous operation while maintaining security and compliance.

Speakers

ST

Speaker TBA

Role to be confirmed

Speaker details will be announced closer to the conference date.

Learning Objectives

  • Design data architectures for autonomous agents
  • Implement streaming and real-time data pipelines
  • Choose appropriate storage solutions for agent memory
  • Build governance frameworks for agent data access

Who Should Attend

Data EngineersData ArchitectsPlatform EngineersBackend Engineers

Prerequisites

  • Experience with data engineering
  • Knowledge of databases and data pipelines

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