ENLYZE
Deniz Saner has a diverse work experience in various roles. In 2015, they completed their Bachelorarbeit at Forschungszentrum Jülich. In 2016, they co-founded Berries, a FinTech company, where they played a crucial role in developing and launching the alpha version of their application. Deniz utilized React Native, Django, Django Rest Framework, Celery, Simple fabric deployment scripts, and Fastlane for the project. However, due to uncertainties surrounding the impact of PSD2, the venture was discontinued. In 2017, Deniz worked on their Master's Thesis on Deep Reinforcement Learning at ZLW-IMA. Later in the same year, they co-founded ENLYZE.
Deniz Saner completed their Abitur degree at Maria-Wächtler-Gymnasium from 2001 to 2010. Subsequently, they pursued a Master of Science in Energietechnik at RWTH Aachen University from 2010 to 2017.
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ENLYZE
ENLYZE considers industrial power consumption as a universal indicator for predicting the condition of machinery, equipment and manufactured product quality. This approach enables us to realize Predictive Maintenance and Predictive Quality Use Cases from the specially developed current sensor "FLUX". Thus, we create the first universaland scalable implementation of predictive maintenance in the heterogeneous machinery of the manufacturing industry. The FLUX is currently patented and features a non-invasive multiphase power cable measurement methodology (no electrician required for installation). The high-frequency recorded data is then analyzed in the cloud using proprietary AI models.