Many teams use Kafka to power real-time analytic sinks to solve one-off use cases—but what happens when real-time insights become a company-wide expectation? In this session, we’ll explore how companies like Uber, Nubank, and Stripe have moved beyond corner cases to build a true real-time analytics platform using Kafka and Apache Pinot. You’ll learn how Pinot’s extreme concurrency, low-latency query performance, and multi-tenant architecture make it ideal for powering dozens of use cases—from operational dashboards and fraud detection to funnel analytics and system observability—without spinning up separate end-points for each. We’ll walk through architectural patterns, lessons learned, and practical tips for building a scalable, unified platform that delivers continuous insights at scale.