With lead leaching from aging pipes, Flint, Michigan, rushed to replace the pipes that posed a serious public health danger but was slowed by the lack of reliable data. They simply didn’t know where the aging pipes were located. The city of Flint needed a way to extract data from hundreds of thousands of handwritten plumbing records and ensure high levels of accuracy on the data being extracted. They couldn’t just use “predictive AI” to help them, and they had to make sure no houses fell through the cracks.
A beta version of Captricity’s READ engine was deployed in Flint late last year when Captricity was brought in to help Michigan extract and digitize 140,000 handwritten service line records and plumbing invoices as accurately and efficiently as possible. Flint needed data from the records to use as a basis for deciding if and when to excavate and when teams could start replacing pipes. Even despite difficult and aging handwritten documents, Captricity extracted the data which was then enriched with 3rd party data so that business intelligence could recommend which sections of pipe should be replaced first to impact the largest number of homes.