Webinar Overview
Presented by: Michael Smart, Innovation and Client Solutions, Astrix & Kelly Maddison, Sapio Solution Engineer, Sapio Sciences Modernizing scientific systems is rarely about the systems themselves – it’s about the data trapped inside them.
Years of ELN, LIMS, ERP, and bespoke-tool entries hold critical institutional knowledge, but without semantic structure that knowledge can’t be reused, integrated, or made AI-ready. Most modernization programs underdeliver on AI for exactly this reason: they migrate the systems but not the meaning. In this joint webinar, Astrix and Sapio share a combined point of view on what it actually takes to bridge legacy environments to AI-native lab operations.
Astrix will walk through the foundational work harmonized vocabularies, domain-aligned ontologies, and pragmatic methods for elevating legacy data during transformation.
Sapio will then show what that foundation unlocks when the destination platform is designed to use it: AI agents that don’t just talk about science but do it running searches, building experiments from SOPs, analyzing results, and acting as a scientific co-worker. You’ll leave with a clear framework for sequencing your modernization work, an honest view of where AI delivers value (and where it doesn’t), and concrete examples of foundational data work translating into real scientific outcomes.
