🟢 LIVE WEBINAR - TUESDAY, NOV. 17, 2026 | 12 PM ET
Trusted industrial AI starts with industrial data your teams can find, trust, and govern. Manufacturers have spent years connecting plant-floor data, yet many still can’t say what it means, where it came from, or who owns it. That’s what keeps AI stuck at one site. Join Litmus CEO Vatsal Shah and Verdantix Senior Analyst Jatinder Devgun for the launch of Litmus Data Catalog. The session opens with new Verdantix research on where industrial data management is heading, then shows why industrial data now needs a catalog of its own.
Problem
IT data got a catalog. Industrial data got a spreadsheet.
Enterprise and cloud catalogs were built for databases, warehouses and business apps. They were never designed to understand a PLC tag, a historian point, or an equipment hierarchy. So the context behind plant-floor data, what a tag means, where it comes from, who owns it and what depends on it, still lives in spreadsheets, tag lists and the heads of a few engineers. That was manageable when the data fed a dashboard. It isn't when the data feeds AI. Litmus Data Catalog was built to close that gap.
Insight
The gap is context, not connectivity
Litmus Data Catalog adds a metadata and governance layer to the Litmus platform. It documents definitions, tag structures, equipment hierarchies, ownership, lineage, and change history across OT and IT systems, including sources outside Litmus.
It reads metadata and leaves operational data where it is, and it works alongside the enterprise catalog you already run. Every site gets a shared understanding of its industrial data before that data reaches analytics or AI.
An analyst’s view of the new category
Jatinder Devgun opens with new Verdantix survey data on why industrial AI stalls, from data quality and compliance to knowledge that never gets written down.
Inside Litmus Data Catalog
Vatsal Shah shares the story behind Litmus Data Catalog and where it fits alongside the catalogs and platforms you already run.
What defines an industrial data catalog
The capabilities to look for: metadata discovery across OT and IT, equipment hierarchies and tag relationships, lineage to the source, clear ownership, and support for segmented sites.
Litmus Data Catalog in practice
See how teams search metadata across sites, trace a KPI back to the tags behind it and check what breaks before a change, without moving operational data.
Vatsal Shah
Jatinder Devgun
Rahul Kulkarni
Quick answers to your industrial data questions.
