Ambisense

www.ambisense.net

Since 2014 Ambisense has been driving innovation within the geo-environmental space. Our vision is to transform how geo-environmental risks are assessed and managed through the use of advanced analytics. To deliver this, we empower our clients with the best in class geo-environmental insights harnessed through automated data collection, analysis, machine learning and AI. These enable our customers to make evidence-based decisions in-real time at significantly lower cost. Ambilytics, our technology platform optimizes the delivery of geo-environmental risk assessment on some of the world’s largest infrastructure projects across industrial, oil & gas and waste verticals. It encompasses both IoT and machine learning solutions, combining information from remotely deployed field devices with contextual data sources such as weather, satellite, geophysical and operational data to build machine learning models. These models identify the relationships, patterns, and drivers hidden within the data and allow our customers to forecast and predict the behaviour of targeted environmental pollutants.

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Since 2014 Ambisense has been driving innovation within the geo-environmental space. Our vision is to transform how geo-environmental risks are assessed and managed through the use of advanced analytics. To deliver this, we empower our clients with the best in class geo-environmental insights harnessed through automated data collection, analysis, machine learning and AI. These enable our customers to make evidence-based decisions in-real time at significantly lower cost. Ambilytics, our technology platform optimizes the delivery of geo-environmental risk assessment on some of the world’s largest infrastructure projects across industrial, oil & gas and waste verticals. It encompasses both IoT and machine learning solutions, combining information from remotely deployed field devices with contextual data sources such as weather, satellite, geophysical and operational data to build machine learning models. These models identify the relationships, patterns, and drivers hidden within the data and allow our customers to forecast and predict the behaviour of targeted environmental pollutants.

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Country

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City (Headquarters)

Dublin

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Employees

11-50

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Founded

2014

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