Systems | Development | Analytics | API | Testing

See how an airline company can use Confluent to build a Streamhouse that powers a real-time flight operations dashboard and AI agents to rebook passengers using current flight and hotel data. Explore Lightning Tables, Confluent Intelligence (Streaming Agents), and Tableflow.

See how Lightning Tables in Confluent Cloud serves the current state of of the business as a fully managed read-only layer—so AI agents and applications can query fresh context at low latency and high concurrency, without ETL, separate databases, or caches. The demo shows how to enable Lightning Tables on Kafka topics for instant querying.

AI is changing what businesses need from their data. Applications and AI agents need access to current, governed business context as events unfold, not after another refresh cycle. Enter the Streamhouse: an architectural approach designed to continuously capture and govern live data, keeping business context current across applications, analytics and AI. Built on three core principles—always current, mission-critical and decentralized—a Streamhouse provides the foundation for making real-time data usable across the enterprise.

A $6,000 laptop could change the math on a $60,000 AI token bill. That fact makes Patrick Moorhead question how businesses calculate the cost of AI. For suitable workloads, running an open model locally could make an expensive-looking hardware purchase a worthwhile investment. His focus is the cost of producing a reliable result.

Tricentis’ VP of Products explains what’s next for Tosca 2026 has been a turning point for software testing, and for Tosca in particular. In this conversation, Magda Neagu, Lead Product Marketing Manager for Tosca, talks with David Landsberg, Tricentis’ VP of Products, about where Tosca is headed, how agentic AI is changing quality engineering, and what the testing world could look like a year from now.