Climate change is increasing the risk, frequency and cost of sewer failures. Flooding is becoming more frequent, causing backflows that frequently shut down wastewater treatment systems. Compounding this problem is that America's infrastructure is severely outdated. The EPA estimates that nearly $700 billion in investments will be needed over the next 20 years just to maintain existing sewer, storm water and other clean water pipelines.
Matthew Rosenthal and Billy Gilmartin, both from the wastewater treatment industry, saw an opportunity to use technology to help alleviate some of this problem, and five years ago they co-founded SewerAI, a company that uses AI to automate the collection of data needed for sewer inspections and the tagging of defects.
“Most infrastructure was built after World War II and is nearing the end of its useful life, with frequent failures and increasing costs,” Rosenthal told TechCrunch. “SewerAI is revolutionizing the inspection and management of underground infrastructure with our AI-driven SaaS platform.”
SewerAI began as a side project for Rosenthal, who began taking online courses on AI after co-founding two wastewater analysis and services companies. While experimenting with an AI model that would predict sewer defects from inspection videos, Rosenthal enlisted Gilmartin, who was working for a sewer inspection company at the time.
Image credit: SewerAI
Currently serving municipalities, public utilities, and private contractors, SewerAI sells a cloud-based, AI-powered subscription product designed to streamline on-site inspection and data management of sewer infrastructure.
One such product, Pioneer, allows field inspectors to upload inspection data to the cloud and tag issues that project managers can use to plan pipe repairs. Another tool, AutoCode, automatically tags pipe and manhole inspections and creates 3D models of infrastructure from video captured by cameras such as GoPros.
“Longer established incumbents offer on-premise or on-track software that has seen little innovation in the last 20 years,” Rosenthal said. “SewerAI's technology increases revenue and profits by increasing the number of inspections per day at a lower cost.”
SewerAI is not the only player in the emerging market of AI-assisted pipe inspections: competitors include Subterra, which maps, analyzes and predicts pipeline problems; Clear Object, whose software analyzes footage from pipe inspections for damage; and Pallon, which develops algorithms to spot potential problems in sewers from still images.
Image credit: SewerAI
Rosenthal argues that what sets SewerAI apart is the quality of its data, specifically its model training data. He says SewerAI has collected inspection footage of 135 million feet of pipe from municipalities and independent contractors. While that's only a fraction of the 6.8 billion feet of sewer pipe in the U.S., it's a substantial dataset to train a competitive defect-detection AI, he says.
“Our products streamline field inspections and data management, empowering our customers to proactively manage their infrastructure rather than react to emergencies,” Rosenthal said.
SewerAI's pitch won over investors like Innovius Capital, which, along with other investors, pumped $15 million into SewerAI's latest funding round, bringing SewerAI's total funding to $25 million, which the company plans to use to expand go-to-market, train AI models, recruit, and expand SewerAI's product portfolio beyond inspection tools.
“As SewerAI continues to grow and customers are able to do more with their existing budgets, the demand for our platform has accelerated, resulting in our first seven-figure contract,” Rosenthal said.