In safety-critical and regulated environments, committing to a single AI model or vendor introduces fragility where reliability matters most.

This session makes the case for a flexible data integration layer as the foundation of any trustworthy AI strategy. By decoupling data from models, organizations can match the right model to each task across cloud, on-premises, and hybrid environments, without sacrificing uptime or compliance. We'll show how unifying geospatial, operational, and external data improves context and retrieval quality, turning AI from a promising experiment into a reliable operational tool.

We'll also introduce Model Context Protocol (MCP) as a practical path toward this architecture, letting organizations adopt new capabilities without re-architecting the systems beneath them.

For organizations where AI trust is earned through consistent, auditable outcomes, the data foundation is not an implementation detail. It is the strategy.

Kurzvita:

Christian Berger is the Team Lead for the Customer Solutions team at Safe Software, playing a key role in promoting the efficient use and adoption of the FME Platform. His journey with Safe Software began as a practicum student while pursuing an Advanced GIS Diploma in 2018, and he has since made significant contributions to the FME Form Support team and the Customer Solutions team. With a solid grounding in GIS from his studies and a strong interest in emerging technologies, Christian is committed to enhancing customer ROI through strategic support and engagement. He actively leads webinars, presents at conferences, and engages directly with customers and partners, ensuring that users of the FME Platform are well-equipped to navigate and effectively tackle their data challenges.