We’ve all heard that “the customer is always right”. But let’s be honest, some customers are just impossible to please. What if we could detect them before they turn into ALL-CAPS review bombers, in real-time?

In this talk, we’ll walk through how to build AI-powered streaming pipelines using Apache Kafka and Apache Flink that can detect frustrated users and respond in real time at massive scale. We’ll explore how to embed AI models directly into data streams for live inference, discuss the trade-offs between using Large Language Models (LLMs) and Small Language Models (SLMs), and tackle the real-world challenges of latency, scale, and cost optimization in streaming AI architectures. Finally, we’ll demo a live end-to-end example, from data ingestion to AI scoring and visualization, that you can later run on your own setup.

Whether you’re experienced in streaming systems or just curious about applying AI to real-world problems, this session will leave you with the needed practical foundation, insights, inspiration, and hopefully a few laughs along the way.