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Presenso Releases New Predictive Maintenance Solution

Presenso’s advanced analytics tools for predictive maintenance don’t require big data experts.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Presenso, provider of machine-learning-based solutions for predictive asset maintenance, has released a predictive maintenance solution that incorporates the latest advances in automated machine and deep learning (Auto-ML).

Presenso's 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 analytics engine autonomously interlinks events with components within the machines and ultimately predicts evolving failures. In addition, it provides valuable information about the remaining time to failure and its origin within the machine.

Auto-ML has now been fully integrated into Presenso's solution. 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.

According to Deddy Lavid (Ben Lulu), Presenso co-founder and CTO, AutoML can automate many of the time-consuming and repetitive machine learning tasks such as big data preprocessing, feature engineering, and model selection and validation, accelerating customer adoption.

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