Discover how’s automated machine learning platform helps energy managers leverage predictive analytics in their daily operations.


Making Energy Companies More Predictive

Predictive analysis in the energy sector makes it possible to offer its customers better services with better profitability. The collection of customer data by electrical sensors allows companies to gather information on energy demand, load forecasting, equipment defect. Yet, those are hard to predict as they are strongly influenced by changing demand and external conditions such as weather.


Leveraging Machine Learning Models

Using machine learning models allows anticipating the production, distribution of energy and maintenance in response to customer demand. Smart cities also want to predict their electricity and gas consumption to better anticipate the needs for maintenance and resources allocated to it. Organizations in the energy sector are building smarter energy supply networks and observing improved energy management.


Why for Energy?

We believe in building highly efficient predictive models that are immediately deployable, scalable, and accessible by users without a data science background. helps energy companies accelerate their data science projects by empowering energy managers with machine learning models while reducing time spent in implementation.

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Energy Consumption Prediction

Energy Consumption Prediction

Large-scale predictive analytics are critical to transforming raw consumption data into actionable insights to optimize gas and electricity consumption. Our platform automatically generates models to help energy managers leverage state-of-the-art machine learning for energy consumption prediction. They access new insights from analytical forecasts and can better scale maintenance operations. View the use case

Load Forecasting

Load Forecasting

Load forecasting requires real-time customer data and improved energy management. Energy firms are already using automated machine learning platform for load forecasting and are thus able to reduce waste. can forecast energy loads by using buildings’ consumption metrics to build accurate predictive models. View the use case

Predictive Maintenance

Predictive Maintenance

Predictive maintenance electrical equipment is based on the actual condition of equipment rather than on a predetermined schedule.’s predictive maintenance solutions can perform maintenance at a time when maintenance activity is most profitable. System failures are thus better detected, which allows for a faster intervention of operators. View the use case allowed us to integrate all of our data streams to accurately predict energy consumption of several buildings in our service territories. Their machine learning platform quickly became an essential tool for our operational teams.

– Deputy Head of Information Technology Programs, French Electricity Company –

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