Article

EV Charge Point Operators Gain a New Tool for Siting Decisions

Stable was created by former MIT researchers Rohan Puri and Jamie Schiel to accelerate investments in EV infrastructure by making them predictable and effective, paving the way for EV adoption in every corner of the globe. They built a straightforward enterprise software platform powered by comprehensive datasets and precision machine learning under the hood, to make it easy for anyone to use. Stable is currently working with major utilities, consulting firms, and pure-play charging operators of all sizes across the U.S. and has raised $7M from Trucks, MIT E14, Ubiquity Ventures, & Upside. 

Stable’s team of Data Science/Machine Learning, Big Data, and UX/UI experts carefully optimized energy cost, incentives, equipment size, and location and built those capabilities into an Enterprise SaaS platform, applying precision machine learning and using comprehensive data including driver patterns and charging behavior, performance of nearby stations, EV density and more factors. The Stable Site Score uses a proprietary machine learning model to predict and categorize site utilization. Site comparisons and rankings make it easy to gauge new sites against millions of historical charging events, and test real build-out scenarios—including tariffs and incentives. 

Related Content