Streaming data and generative AI: Confluent's approach
Description
In this episode of the Targeting AI podcast from AI Business, Shaun Sutner and Esther Shittu interview Sean Falconer of streaming data platform vendor Confluent. They discuss Confluent's AI strategy, the importance of real-time data management, and the integration of generative AI and multi-agent systems into business processes. Falconer emphasizes the need for high-quality data and the advantages of open source technologies like Apache Kafka and Flink. The conversation also touches on the challenges of implementing AI systems and the future direction of AI technology at Confluent.
Featuring: Sean Falconer, senior director of AI Strategy at Confluent.
In today's episode, we cover how:
- Confluent focuses on real-time data processing and management.
- Generative AI requires fresh, relevant data to be effective.
- Data quality should be enforced at the source, not downstream.
- Multi-agent systems can operate continuously and autonomously.
- Confluent partners with major AI model providers for integration.
- Reliability and testing are critical challenges in AI development.
- The future of AI at Confluent includes building support for ambient agent experiences.
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References:
- Confluent, streaming data and agentic AI
- Confluent and Databricks work together to simplify AI development
- What is data streaming?



