Jan. 18, 2021 - Litmus , the Intelligent Edge Computing company, today announced the release of Litmus Edge 3.0, a modern edge platform to collect and analyze data, build and run applications, and integrate edge data with any cloud or enterprise system. Litmus Edge 3.0 adds more device drivers to bring the industry-leading total to more than 250, with enhanced analytics, improved integration connectors, digital twin support, and expanded device management features.
“Litmus Edge is the only modern edge platform on the market that connects to all industrial assets and provides a complete data picture to improve industrial operations,” said Vatsal Shah, co-founder and CEO of Litmus. “Version 3.0 expands upon the product that already leads the industry with more device drivers, pre-built analytics and OT/IT integration capabilities, so customers can capture edge data and use it to perform local analytics or advanced use cases like machine learning and AI in the cloud.”
New features of Litmus Edge 3.0 include:
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Launched second generation industrial communication drivers focusing on security and scalability for southbound communications
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Enhanced Ready Analytics which now includes the ability to run Tensorflow and other machine learning algorithms natively on real-time ingested data
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Flows Manager updated to allow multiple instances of Flows – which can be tightly integrated or scaled or isolated with sandbox and production logics
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Enhanced cloud and enterprise Integration connectors including support for Splunk, Oracle DB, and other databases
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Improved user interface for application marketplace for one-click application orchestration
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Device management improvements including security, backup/restore and digital twin templates
Litmus Edge is a modern edge platform that collects data from any industrial asset, offers pre-built applications, KPIs and analytics, provides the ability to build and run custom applications, and integrates data with any cloud or enterprise system. Litmus Edge is easy to use and easy to deploy, offering the edge connectivity and data intelligence needed to power industrial use cases ranging from predictive maintenance to machine learning.