What is special about Precognize...

Abnormalities in a plant are frequent events.

Faulty sensor readouts and functional imperfections show up as alerts, distracting operators from detecting events that cause equipment failure.   


Through machine learning and conceptual modeling, Precognize eliminates statistical anomalies, while singling out critical events long before they happen.

 

Combination of Technologies

Machine Learning

Precognize’s advanced machine learning methods separate between normal and abnormal data points. Using a year's worth of historical data as the plants "baseline", the software creates a statistical model to inspect new data in real-time.

Conceptual Modeling

Precognize captures the way systems are built and behave. Precognize's drag and drop interface allows operational experts with no modeling training to accurately describe their systems. The software creates a complete model in a matter of a few hours to a few days, depending on the number of sensors.

Graph Theory

Precognize converts the conceptual model of the plant into a graph. Abnormal data points are compared using several graph techniques to detect where problems in the system originate. Once discovered, operators are presented with clear, specific true alerts.

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