Systems | Development | Analytics | API | Testing

Technology leaders share how they process streaming events end-to-end in sub-second latency, secure sensitive data through immutable and governed pipelines, power secured real-time systems in regulated environments, and enable multi-agent AI systems built on fresh, continuously streaming data.

In 2025, real-time data moved from important to mission-critical. From billion-event pipelines to AI agents reasoning over fresh data streams, the conversations this year revealed just how fast organizations are rethinking their data infrastructure and what’s possible when data streaming becomes the foundation.

Mohamed Ahmed Anwar shares why “shifting left” to process data closer to its source is key to AI agent performance, speeds RAG knowledge updates, And eases the move from legacy on-prem to scalable cloud architectures.

See how Tableflow converts data to Apache Iceberg or Delta Lake format, and how it can be integrated with Amazon Redshift to query and analyze customer activity snapshots.

In this video, we're breaking down the complex world of Apache Kafka and showing you how to gain deep visibility into your event streaming architecture using Speedscale. Kafka is the backbone of modern, cloud-native systems, but understanding what's happening in production—which topics are receiving traffic, where messages are going, and how services are interacting can be a real challenge. We'll cover how Speedscale makes Kafka visualization and debugging simple by.

Ramon Cidade shares why Apache Flink was a game changer at Current 2025 in New Orleans, and gives his take on what makes the data streaming event so special: the community, the people, and the technology they’re innovating with.