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Flutura Announces Strategic Partnership & Scale Agreement with TechnipFMC

Flutura Business Solutions LLC, a Houston based Industrial IoT Intelligence provider, announced a multi-year agreement with TechnipFMC (Surface Division) a leading technology provider to the traditional and new energy industries, delivering fully integrated projects, products, and services. This agreement is the logical culmination of pathbreaking work done together over the last few years in the Energy digitalization space.

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Flutura, a rapidly growing Industrial AI company, powers large scale operational transformation using its industry pioneering Cerebra Cognitive Digital Twin solution. Flutura’s Cerebra Portfolio of Industrial AI solutions, ranked #1 by customers in Gartner Voice of Customer research, leverages deep verticalized Artifical Intelligence/Machine Learning capabilities to impact operational efficiency improvements and system reliability to support organizations through their digitalization and Energy Transition journey.

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“We are elated to announce our agreement with TechnipFMC,” says Srikanth Muralidhara, Co-founder & Chief Customer Officer, at Flutura, “With its core software product UCOS, digital solution ‘InsiteX’ and deep domain depth, TechnipFMC is in an excellent position to transform digitization efforts in the Energy industry. With the impending emphasis on energy transition, the industry is at an inflection point, and this agreement will help in smooth execution during this period of rapid scaling.”

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TechnipFMC has conceptualized and created InsiteX, a solution designed to drive efficiencies, making products smart and digital practical for their customers in the new digital era, combining the deep domain understanding and a scalable technical foundation of Flutura’s Cerebra Cognitive Digital Twin, hosted on an infinitely scalable infrastructure. The collaboration has been seamless, and the solution has been deployed very successfully over the past years with several energy operators in the completion and production segments.

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