[Webinar] From Fire Drills to Zero-Loss Resilience | Register Now

Online Talk

Why Real-Time Data Streaming is the True Foundation for the AI era

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March 25th, 2026

10:30 AM IST | 1 PM SGT | 4 PM AEDT

AI is only as intelligent as the data that feeds it, and in today's fast-paced digital landscape, relying on stale, batch-processed data is a recipe for hallucinations and missed opportunities.

This session explores how Confluent’s modern data streaming platform serves as the central nervous system for Enterprise AI, bridging the critical "context gap" that holds traditional architectures back. We will unpack how shifting to a real-time, event-driven data foundation empowers organizations to build highly accurate Retrieval-Augmented Generation (RAG) pipelines and deploy autonomous, context-aware AI agents.

Join us to discover how leveraging real time data through Confluent ensures your AI models are grounded in trustworthy, up-to-the-millisecond data, transforming static information into immediate business impact.

What You Will Learn

  • The right way to look at your Data Architecture for AI Readiness
  • Building Trustworthy AI from Development to Production
  • Improving Data velocity and accuracy for servicing your AI model
  • Modernizing Legacy Infrastructure
  • Operationalizing AI at Scale

Who Should Attend

  • CTOs & IT Strategy Leaders looking to modernize legacy systems and reduce the "tool sprawl" that slows down AI delivery.
  • Data Architects & Engineers tasked with building the "central nervous system" for enterprise data to support real-time inference.
  • AI/ML Product Managers aiming to improve model accuracy and move from reactive copilots to proactive, autonomous business agents.
  • Digital Transformation Officers focused on delivering immediate business impact through high-fidelity customer experiences and automated workflows.

Justin is a Principal Solutions Engineer with a background in networking and infrastructure, and now spends his days helping businesses design and architect complex distributed data systems.