PRNewswire has recently published an article describing PowerScout’s announcement it has secured $5.2 million in funding for technology that lowers the price of clean energy by predicting which homes are most likely to adopt it. The Bay Area company has developed machine learning technology that can predict which homeowners will go solar. The funding was provided by a mix of private and public sources including the U.S. Department of Energy, which awarded PowerScout a total of $2.5 million in grants via its SunShot Initiative.

“We’re excited to bring the same technologies that are revolutionizing the retail, transportation, and financial services industries to the residential energy market,” said PowerScout CEO Attila Toth. “Today when you go solar through a traditional provider, you often end up paying more to cover marketing expenses than for the panels themselves. By pinpointing which homes are most likely to adopt solar we avoid wasteful spending and pass the savings on to the consumer.”

The company’s Foresight platform uses advanced image recognition technology, LIDAR data collected by planes, and in-depth consumer data to analyze entire neighborhoods at a time— tagging each home with over 1200 data points ranging from income and education levels to political affiliation and even the type of car an individual drives.

In addition to predictive analytics, PowerScout aims to expand the connected economy category by creating value around the process of shopping for and buying clean energy.

Read more at PRNewswire.