Software and sensors to manage company assets

FRANCESCA TOSI, HEAD OF GROWTH AT QUICK ALGORITHM, EXPLAINS HOW THE BUSINESS OF THE STARTUP INCUBATED BY B4I HAS EVOLVED

Diversifying the services offered and also after-sales support policy, with the intention of strengthening the positioning of Quick Algorithm, a startup born in February 2018 and incubated by B4i-Bocconi for innovation, the University's acceleration program. Initially, Quick Algorithm only offered the Artificial Intelligence service to optimize the management of a company's physical assets, such as production machinery or even company buildings. All thanks to Scops.ai, a cloud-based proprietary software which analyzes big data from different sensors and sources, including those generated by human maintenance activities. The business advantage proposed: reducing industrial costs. For example, energy ones. Now, however, "we also supply the sensors for detection, which for the moment we do not produce ourselves", says Francesca Tosi, Head of Growth at Quick Algorithm and corporate board member. «We started from the needs of some companies that did not have the necessary sensors in the field or, if they did, the data was collected from different data sources or platforms that were not integrated with each other». Therefore, the business has expanded in parallel with the commercial plan that allows you to purchase, as rental or leasing, Quick Algorithm sensors.

«With the increase in energy costs, the number of requests we receive has increased», adds Tosi. «With Scops.ai, companies can not only monitor and predict the numerous and varied anomalies of their plants, but also and above all discover unknown phenomena that would have been difficult to identify without the support of machine learning». An unexpectedly large and detailed environment, the boundaries of which range from incorrectly tightened clamps to the cold room door left open. Moreover, «AI based on machine learning learns from data and is able to take into account "normal" anomalies due to factors such as seasonality and the type of production. In these cases, the system does not send any alerts», concludes Tosi.

by Camillo Papini
Translated by Alex Foti