We use machine learning to support the removal of lead and other dangerous materials from communities, maximizing public health while minimizing costs.
We believe all communities should be able address hazardous infrastructure in an affordable, time-efficient manner.
In 2016, a team of researchers from the University of Michigan began working with Flint’s service line replacement program. By that time, it was understood that the city’s lead service lines were the main source of lead in the drinking water but two key questions stood in the way of their progress: how many lead pipes are in the city and which homes have lead pipes? The researchers applied fundamental statistical methods to this problem and built a machine learning model to help the city dig where the lead actually was. In 2019, the University of Michigan researchers who worked in Flint formed BlueConduit with the mission of supporting the large-scale removal of lead and other dangerous pipe materials from cities.