Litmus Edge handles data collection, analytics and integration, while Pluto7 specializes in data science and machine learning on Google Cloud
Litmus, the Intelligent Edge Computing company, today announced a partnership with Pluto7 to enable artificial intelligence in manufacturing with a complete edge-to-cloud solution. Litmus Edge collects data from any industrial asset and normalizes it for immediate use by Pluto7 for data science and machine learning applications on Google Cloud. The combined solution gives manufacturing customers immediate value from their edge data to build machine learning models and improve operations.
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“Manufacturers know they want to do AI and advanced analytics, but many of them need a simple and secure way to feed GCP with good data, which is where Litmus comes in,” said Manju Devadas, Founder and CEO of Pluto7. “Working with Litmus, we can provide a more complete solution for Industry 4.0 implementation. We look forward to working with customers to build AI and ML models built on Google Cloud with intelligence from their factory data.”
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. Pluto7 is a Premier Google Cloud Partner for AI Services and Solutions, allowing businesses to speed up and scale sophisticated machine learning models for digital transformation. Litmus Edge integrates seamlessly with GCP so customers can accelerate their data-driven digital transformation from edge to cloud.
“Our partnership with Pluto7 allows us to work with customers to not only set the right foundation for digital transformation, but to gain additional value from the data we collect,” said John Younes, Co-founder and COO of Litmus. “With Litmus and Pluto7 our customers can extract more value from the data that we collect from their equipment to enable use cases such as predictive maintenance and AI-based vision detection systems.”
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