Tore Notland

Formula 1 teams rely on a constant stream of telemetry and race data to make critical decisions during a race. In this hands-on workshop, you'll build a real-time AI application that ingests live race data with Apache Kafka, detects anomalies using Apache Flink, and uses AI agents to recommend pit stop strategies as race conditions evolve.

Through a series of guided exercises, you'll implement stream processing, stateful event analytics, anomaly detection, and agent-driven decision making. You'll also explore how AI agents can consume live event streams to generate race updates and social media content grounded in real-time race events.

Designed for developers, platform engineers, architects, and data engineers, this workshop focuses on building an end-to-end intelligent application where streaming data directly drives AI-powered actions.