Current London 2025: Unleashing Event-Driven AI with Kafka and Seldon Core 2

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Remember when streaming data felt like the next big thing but the market wasn’t quite ready for the actual complexity of AI? Current London 2025 (formerly Kafka Summit) made it clear that event-driven AI is no longer an idea for tomorrow as it’s already transforming how organizations operate today. Kafka is central to this evolution but how exactly, and what makes Seldon Core 2 its perfect partner?

The New Era of Event-Driven AI

Current London 2025 spotlighted the rise of autonomous, agentic systems, or intelligent software that proactively perceives, learns, and takes action in real time. Richmond Alake from MongoDB described Event-Driven Agentic AI as “a system design paradigm that merges event-driven architecture with autonomous AI agents. It empowers applications to continuously ingest and process data streams, instantly triggering AI-powered workflows.” Imagine a travel assistant AI that checks flights, negotiates upgrades, and manages itineraries without human intervention. These seamless, intelligent interactions are only possible with infrastructure that supports real-time responsiveness and dynamic decision-making.

To realise this vision, event-driven AI demands infrastructure capable of:

  • Immutable memory to maintain accurate, replayable histories.
  • Real-time responsiveness enabling agents to react within milliseconds.
  • Exactly-once data delivery for precise, reliable interactions.

Kafka 4.0 and Confluent Cloud: Innovations for AI Readiness

‘The modern software problem is a data problem,’ Confluent CEO Jay Kreps also noted, businesses today are becoming software-defined, and streaming data is the engine behind this shift. AI, powered by tools like Kafka and Seldon, transforms traditional batch logic into continuous, automated decision-making, reshaping how modern organizations operate.

Specifically, Kafka 4.0 is bringing major upgrades in scalability and performance like self-balancing clusters and low-latency tiered storage. These innovations make Kafka even more reliable for real-time, high-volume AI workloads.

Confluent Cloud further simplifies adoption by offering enterprise-grade connectors to tools like Salesforce, enabling seamless data movement without the typical integration hurdles. Its introduction of Tableflow, powered by Apache Iceberg, bridges real-time streams with historical lakehouse data, perfect for AI agents that need both live and contextual insight to act intelligently.

Seldon Core 2: Kafka’s Perfect Companion

  • Effortless construction of inference graphs, combining classical ML, Large Language Models (LLMs), and autonomous agents through Kafka topics.
  • Dynamic scaling of Kubernetes clusters, instantly adapting to AI workloads and traffic spikes.
  • Comprehensive observability with full traceability, explanations via Alibi Explain, and drift monitoring with Alibi Detect.
  • Streamlined governance and compliance, ensuring real-time, data-centric transparency and accountability.

Your Next Steps: Streamline Your AI Strategy

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  • Current and potential use cases
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