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GTM Research Ranks Grid4C as the #1 Vendor for Predictive Analytics & Load Forecasting 2016 Business Wire Grid4C

Grid4C announced today that it has been ranked as the #1 vendor in Predictive Analytics & Load Forecasting for utilities by GTM Research in its latest report. Grid4C was voted a top provider of both grid-side and customer-side analytics solutions.

This Smart News Release features multimedia. View the full release here: http://www.businesswire.com/news/home/20160105005564/en/

Grid4C was selected as the leading vendor solution out of world class vendors due to its proven capability to be deployed across all nine customer and operational analytics use cases identified in the study. Grid4C was also rated highly in the study for providing differentiated configurations in terms of adopted methodology, ability to be customized, and ability to implement both bottom up load forecasting, as well as non-intrusive top down load disaggregation – from the meter level to the appliance level, and detect malfunctioning patterns. All prediction and anomaly detection methods are based on patented Machine Learning algorithms.

GTM Research reports are an industry recognized and reputable assessment of the market landscape for the energy industry. GTM Research is the market intelligence arm of Greentech Media.

“Grid4C’s selection as the #1 vendor solution, in the same analysis of solutions by other world class businesses, is a great honor and another sign of the industry’s recognition of Grid4C’s market-leading algorithms and Machine-Learning based software to improve utilities’ operational efficiency and to increase customer engagement,” states Dr. Noa Ruschin-Rimini, Founder and CEO of Grid4C. “Grid4C is deployed in a wide range of electricity markets, analyzing billions of meter reads from 3 continents, producing more than 10 million predictions for utilities production and customer systems every day and transforming the way utilities interact with their customers,” she adds.

Full report can be found at http://www.greentechmedia.com/research/report/predictive-analytics-for-utility-load-and-der-forecasting-2016




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