Towards Interoperable Intelligence: Streaming Foundations for Multi‑Agent Systems

As enterprises begin deploying AI agents at scale, agent sprawl is inevitable. Without governance infrastructure, unmanaged autonomy cascades: agents cannot reliably discover existing tools, so teams unknowingly rebuild functionality; data quality drifts between systems; conflicting decisions emerge; lineage goes missing; and hallucinated actions execute at machine speed, before any human can audit or stop them. A governance nightmare.

In this talk, we show how a self‑service event streaming platform provides the missing foundation to govern multi‑agent systems. Event stream processing delivers real‑time aggregation, explicit data contracts, and end‑to‑end observability - so agents can reason in a clean, auditable state instead of ad‑hoc APIs and shadow IT. Our position: taming this sprawl does not require a new AI stack. It requires treating your existing event streaming platform as governance infrastructure.

At E.ON / Essent, we're building a self‑service streaming platform on top of Confluent Cloud for enterprise AI operations. Key capabilities – EventCatalog for discovery, Flink for real‑time aggregation, and validation gates – are proving essential for agent governance. The hardest part, however, is not platform engineering; it is helping teams understand when and how to use it, and to think in streams, not just events.

Our strategic framework - the Agentic AI Interoperability Target Picture - addresses the autonomous systems challenge: the identity and policy layer enforces safe execution boundaries, the control plane coordinates agent activity, and the agent gateway validates all requests. This enables bounded autonomy at scale. The streaming platform forms that foundation, enabling agents to reason on curated, validated, aggregated state instead of stale snapshots. Three concrete capabilities operationalize this:

Discovery & Registry: Searchable data contracts enable agents to know what exists

Real‑Time Aggregation: Flink materialized views provide timely state

Upstream Validation: Quality gates enforce schemas so agents act only on trusted data

By combining self‑service access with centralized governance, we've found a path from agent sprawl toward orchestrated autonomy at scale.

Attendees will not only learn our platform patterns and governance approach, but discover the real challenge: organizational transformation. E.ON's SAP case - 500+ topics, real-time aggregation replacing blind batches - proves shifting teams to stream thinking is what unlocks AI autonomy at scale.