Litmus Named in 2021 Gartner Magic Quadrant for Industrial IoT Platforms

Litmus evaluated among leading Industrial IoT Platforms for the third consecutive year

Litmus, the Intelligent Edge Platform for Industrial IoT, announced the company was named in the 2021 Gartner Magic Quadrant for Industrial IoT Platforms for the third consecutive year. In the report, Gartner recognized Litmus among 18 other leading vendors evaluated based on their ability to execute and completeness of vision.

Litmus focuses on enabling Industrial IoT at the edge. The platform is purpose-built for OT data collection, machine analytics, enterprise data integration and application enablement. Scale is enabled via a centralized edge management platform that manages all IIoT devices and services across all locations from a single point of control.

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We are proud to be included again in this year’s report and we believe that our success is due to our strong focus on providing a rapid-to-deploy Industrial IoT edge platform.

“We continue to see widespread adoption of Industrial IoT at the edge – organizations like Google Cloud and Dell Technologies work with Litmus to address the complexity of collecting data from all OT assets and using that data at the edge as well as the cloud to improve industrial operations at scale,” said Vatsal Shah, co-founder and CEO of Litmus. “We are proud to be included again in this year’s report and we believe that our success is due to our strong focus on providing a rapid-to-deploy Industrial IoT edge platform. Customers use the Litmus platform to create a foundational industrial data layer that is used to drive intelligence at the edge and data lake, ML, AI and advanced digital twin use cases in the cloud.”

According to the report, “Gartner defines the industrial Internet of Things (IIoT) platform market as a set of integrated software capabilities to improve asset management decision making within asset-intensive industries.” Further it adds, “The IIoT platform is differentiated from legacy operational technology (OT) by its ability to cost-effectively collect higher volumes of high-velocity, complex machine data from networked IoT endpoints. The IIoT platform also orchestrates historically siloed data sources to enable better accessibility and improve insights and actions across a heterogeneous asset group through specialized analysis of the data.”

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