Agentic Beam YAML Pipelines for Real-Time Predictive Intelligence on Streaming Data

This talk demonstrates how declarative Beam YAML pipelines, combined with LLM-powered agentic architectures, unlock real-time predictive intelligence on high-velocity sensor streams — using UAV flight telemetry as a live use case. We show how parameterized Beam YAML templates dynamically reconfigure processing logic at runtime without code changes, while AI agents perform anomaly detection, predictive trend analysis, preemptive failure reasoning, and adaptive alerting — all orchestrated within the pipeline itself. Attendees will learn practical patterns for embedding agentic workflows into Beam, wiring streaming data sources to ML inference transforms, and building pipelines that don’t just react to problems but anticipate them. The session highlights how Beam’s unified model powers the next generation of intelligent, self-reasoning data applications.