Monitoring and analysis of electrical infrastructure

Case study

Given the novelty of machine learning algorithms in industry, you know that marketing AI technology to potential clients can prove challenging. The Clean Tech/AI start-up, BluWave AI, approached Zetane with such a problem.

BluWave develops machine learning algorithms to facilitate the incorporation of clean energy sources within existing electrical infrastructure. Selling their innovations to municipalities was difficult because only AI professionals could understand and appreciate the quality of their algorithms and their predictions in energy consumption patterns. The founders of the start-up used Zetane to bring their technology “to life”, producing rich visuals of algorithms and their outputs for each client. Officials from municipal governments could now see and better understand the use of machine-learning predictions in electrical infrastructure. Government officials could see and understand how the company used client data to develop an original model. A key selling point is the presentation of key metrics, like cost and energy savings, juxtaposed to the neural network.

Prior to Zetane, the founders struggled with abstract Python code and presentation slides with predicted numbers of energy consumption that “appeared out of thin air”. Strong visuals made their projects tangible and trustworthy.