New metadata visibility and governance layer unifies discovery, lineage, governance, and AI-driven context across OT and IT systems
This is a Press Release edited by StorageNewsletter.com on May 6, 2026 at 2:00 pmLitmus announced the private preview of Litmus Data Catalog, a new product designed to help manufacturers gain visibility into industrial data assets and apply governance across systems, sites, and teams.
As industrial organizations expand investments in automation, cloud, and AI, a persistent challenge remains: teams lack visibility into how data is defined, structured, and used. Dependencies are difficult to trace, ownership is unclear, and data is hard to trust for analytics and AI at scale.
“Industrial companies don’t have a data volume problem – they have a data and systems trust problem,” said Vatsal Shah, co-founder and CEO, Litmus. “Litmus Data Catalog gives teams the visibility and governance needed to understand their data, establish consistency across systems, and apply governance at scale.”
Litmus Data Catalog introduces a unified context layer within the industrial data architecture – complementing Litmus Edge and Litmus Unify (UNS) – to give teams visibility into what data exists, where it comes from, and how it’s used. The product automatically discovers and organizes metadata from OT and IT systems, mapping relationships and lineage across data assets.
With Litmus Data Catalog, teams can:
- Discover and catalog industrial data assets across systems and sites
- Trace lineage across OT-to-IT pipelines
- Add contextual understanding to data through AI-driven enrichment and summarization
- Apply governance with ownership, permissions, and classification
- Monitor schema drift and maintain metadata quality
- Use AI-driven search and summarization to interpret data faster
As industrial ecosystems grow more complex, Litmus Data Catalog brings structure and visibility – enabling more reliable analytics, consistent KPIs, and scalable AI outcomes. With this release, Litmus extends its Industrial Edge Data Platform to include data asset visibility, lineage, governance, and observability – delivering a complete foundation for enterprise-scale Industrial AI.
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