Presenso predictive maintenance solution has Auto-ML technology

Haifa, Israel-based Presenso offers machine-learning-based solutions for predictive asset maintenance which incorporate the latest advances in automated machine and deep learning (Auto-ML).

Presenso says its system collects immense amounts of data at very high speed from hundreds of machines (thousands of sensors) and streams the data to the Cloud in real-time. Using unique, proprietary deep neural-network architectures, Presenso’s analytic engine autonomously interlinks events with components within the machines and ultimately predicts evolving failures. In addition, it provides information about the remaining time to failure and its origin within the machine.

A beta product, launched in early 2017, was extensively tested in a range of production environments. In the last 12 months Presenso has successfully tested its solution in the plants of over 20 end-users in the pulp & paper, energy production, chemical processing and oil & gas.

Presenso believes that its predictive maintenance solution can address a major challenge faced by industrial producers — how to scale a predictive maintenance solution across an organization; it says that Auto-ML has now been fully integrated into its predictive maintenance solution to solve that problem. Presenso automates machine learning processes and provides a software-as-a-service AI solution that requires no interaction with the plant’s engineers and no data scientist to perform the application engineering tasks.


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