Federated Learning: Rethinking AI Infrastructure with Scalytics

As AI agents begin to influence how businesses operate, there's growing urgency around building infrastructure that supports their complexity without adding new risks. In this episode of IT Infrastructure as a Conversation, I speak with Alexander Alten, Co-Founder and CEO of Scalytics, about the architecture powering the next generation of AI and machine learning systems.

Alexander’s journey includes leadership roles at Cloudera, Allianz, and Healthgrades, and a deep commitment to building scalable, privacy-respecting technologies. At Scalytics, he's helping organizations avoid the limitations of centralizing data by building distributed systems that support federated learning. Rather than extracting and duplicating data across systems, Scalytics enables analysis directly at the source, making it easier for businesses in regulated industries to innovate with confidence.

Recorded live at the IT Press Tour in Malta, our conversation dives into the origins of Scalytics Connect, the company's AI agent infrastructure that leverages open-source frameworks like Apache Wayang. We explore why ETL pipelines often create fragility instead of flexibility, how decentralization supports both compliance and collaboration, and why open-source technologies continue to outperform closed systems over the long term.

For any CIO, CTO, or data architect looking to align AI capabilities with real-world constraints, Alexander’s perspective offers a refreshingly pragmatic path forward. His framework simplifies the complexity of federated machine learning while preserving data sovereignty, auditability, and future-proof flexibility.

If your organization is struggling with data silos, regulatory friction, or the scaling of AI models, this episode offers insight into a model that avoids duplication, improves trust, and accelerates results by treating infrastructure as the foundation for intelligent systems.