Episode 67: Is Your Lab Sitting on a Data Goldmine? AI, Deep Learning, & Mass Spectrometry with mzio

Welcome back to another episode of Concentrating on Chromatography! In this episode of  @ChromatographyTalk  host David Oliva sits down with Dr. Ansgar Korf, CEO and Co-Founder of mzio GmbH, to explore how their vendor-agnostic platform is fundamentally changing how researchers and industrial users extract value from complex mass spectrometry data.Historically rooted in the open-source academic community as mzmine, Bremen-based mzio has evolved into a powerhouse for multimodal data analysis—spanning LC-MS, GC-MS, ion mobility MS, and MS-imaging. Ansgar pulls back the curtain on how laboratories can break free from proprietary vendor software stacks to streamline workflows across mixed-instrument fleets.We dive deep into their massive announcements from ASMS 2026, including FAIR-MS—an AI-powered initiative utilizing deep learning embeddings to automatically search and match new measurements against archived, historical data sets. We also break down the LIMMIC calibration project, their new small molecule and lipidomics dashboards, and how AI agents will shape the next 5 years of automated, real-time MS data acquisition.Whether you are an industry veteran or an early-career chemist, this episode is packed with insights on avoiding the "black box" of automated analysis while unleashing the true power of your lab's data.Mass Spectrometry, Chromatography, mzio, mzmine, FAIR-MS, LIMMIC, Lipidomics, Metabolomics, Open-Source Science, Analytical Chemistry, AI in Chemistry, Deep Learning, LC-MS, GC-MS, PFAS Analysis, Vendor-Agnostic Software, ASMS 2026