Why Streamhouse: mission-critical data and AI need infrastructure built for live data

Streamhouse is proposed as a vendor-neutral architecture for real-time operational systems that continuously capture, process, govern, and serve live business data for production applications and AI agents. While lakehouses remain important for analytics, historical analysis, and model development, the initiative argues that agents acting in production require current data rather than delayed batch outputs, along with performance, controls, and auditable visibility. Redpanda, Aiven, Confluent, StreamNative, and Ververica have formed the Streamhouse Working Group to establish a shared industry model built on existing technologies such as streaming, event processing, SQL databases, APIs, and analytics. The architecture emphasizes a control plane spanning the data, operational systems, databases, and SaaS applications that agents use, enabling organizations to govern agent actions and maintain records of their activity.

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