We’ve got big news: Gartner has named Litmus a Challenger in the 2025 Gartner® Magic Quadrant™ for Global Industrial IoT Platforms (Sept. 8).
For years, we were categorized as a Niche Player—recognized for solving tough industrial data problems but not yet in the same weight class as the giants. That’s changed. In 2025, Gartner elevated Litmus to a Challenger. Translation? We believe we’ve proven we can execute at enterprise scale—and we’re not afraid to take on the largest players in the market.
This is how Gartner defines Challengers:
“Challengers have excellent IIoT platform technical abilities and the Ability to Execute, predominantly built for manufacturing use cases, but they have a growing expansion to other submarkets. The Challenger brings to market a consistent set of technologies across cloud-based and on-premises deployments. Three vendors are evaluated as IIoT platform Challengers this year.
Challengers have an emerging and coalescing vision of the market’s direction. Challengers develop competencies expressed more in adjacent, value-added application capabilities, such as digital business, use-case-specific analytics ‘applets,’ rather than end-to-end horizontal IIoT platforms/suites. Challengers choose a narrower path to sell their IIoT platforms to a targeted number of asset-intensive subsectors, rather than a broad cross-industrial focus. They transfer knowledge to customers, partners and prospects through a deep and broad library of sector-specific use-case frameworks and methodologies.
Challengers have the organizational capabilities and scale to consistently pursue and win multinational IIoT opportunities. These opportunities are global in terms of supporting referenceable enterprises that build digital solutions using the provider’s IIoT platform in at least three regions.”
For Litmus, being positioned here is a signal of our proven ability to execute across multi-plant, edge-to-cloud deployments at scale. We’ve moved beyond the niche use cases where we were recognized in the past, and we’re now validated as a platform that we believe global enterprises rely on for production-level outcomes.
At the same time, Gartner’s definition challenges us to continue showing how our roadmap and vision for industrial AI align with where the market is heading. That’s exactly what we’re investing in next—continuing to bridge the IT-OT divide, embedding context at the edge, and enabling safe, governed industrial AI at scale.
The market is littered with pilots that never scale. Manufacturers don’t fail for lack of ideas—they fail because their data isn’t ready, governed, or contextual. Litmus fixes our industry’s data connectivity problem and pipeline journey head-on.
We believe this shift to the Challenger quadrant highlights our ability to:
Scale edge-to-cloud deployments across dozens of plants and enterprise systems
Collect and contextualize data at the edge with our broad connectivity with 250+ OT protocols and seamless integration with leading cloud and AI platforms
Publish one semantic source of truth to the cloud, UNS, historians, analytics, and AI pipelines
Enforce trust and governance with quality checks, lineage, and operator guardrails
Support operator-safe, auditable decisions that meet compliance and quality standards
For manufacturers, this recognition reduces risk. We believe it’s third-party recognition that the platform you’re considering—or already running—works at enterprise scale.
Many programs stall in the pilot phase. The gap isn’t ideas—it’s data readiness and repeatability.
Litmus helps close that gap by:
Unifying live OT data with context at the edge (cell/line/plant), so downstream systems can trust and act on it
Publishing a consistent, semantic view to enterprise consumers (UNS, cloud, historians, analytics, AI/ML) with clear ownership and governance
Shortening time-to-value with out-of-the-box integrations and proven rollout patterns that scale across sites and use cases
When data is complete, correct, and contextual, AI stops being a demo and starts being a reliable part of day-to-day operations.
Recognition is not the finish line. Here’s where we’re investing:
More context at the edge: Faster time-sync, enrichment, and quality scoring to increase trust in every downstream decision.
Deeper governance & lineage: End-to-end traceability—from signal to action—to simplify audits and speed root-cause analysis.
AI in production, safely: Tooling to operationalize models at the edge with guardrails, rollback, and performance monitoring.
Ecosystem momentum: Continued collaboration with hyperscalers, data lakehouse providers, and UNS leaders to meet customers where they are
Our goal: make it radically easier to go from connected data to confident decisions—and to scale those decisions across your network.
To our customers and partners: thank you for the trust, the tough problems, and the bar you set. This milestone belongs to you as much as to us.
Want to talk about scaling your deployments? Book a call with a Litmus expert.
Gartner, Magic Quadrant for Industrial IoT Platforms, 2025. Gartner does not endorse any vendor, product, or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER and MAGIC QUADRANT are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.