Climate change is increasing the risk, rate, and cost of sewage failures. Flooding is becoming more common, causing backups that often overwhelm wastewater treatment systems. Making the problem even worse, America’s infrastructure is very old; the EPA Estimate An investment of about $700 billion is needed to maintain existing wastewater, rainwater and other clean water pipelines over the next 20 years.
Matthew Rosenthal and Billy Gilmartin, who both come from the wastewater treatment industry, saw an opportunity to help solve the problem with technology — at least in a small way. Five years ago, the pair co-founded SewerAIwhich uses AI to automate the types of data capture and defect tagging used in sewer inspection.
“Most of the infrastructure was built after World War II and is now reaching the end of its useful life, leading to frequent failures and rising costs,” Rosenthal told TechCrunch. “SewerAI revolutionizes the inspection and management of underground infrastructure with its AI-powered software-as-a-service platform.”
SewerAI began as Rosenthal’s side project; he had begun taking online courses on AI after co-launching two wastewater analysis and services firms. While experimenting with AI models to predict sewer defects in inspection videos, Rosenthal enlisted the help of Gilmartin, who was working at a sewer inspection company at the time.
Today, SewerAI — whose customers include municipalities, utilities, and private contractors — sells cloud-based, AI-powered subscription products designed to streamline field inspections and data management of sewer infrastructure.
One of these products, Pioneer, allows field inspectors to upload inspection data to the cloud and tag problems — data that project managers can use to plan how to fix pipes. Another tool, Autocode, automatically tags inspections of pipes and manholes, creating 3D models of infrastructure from video captured on a GoPro or other camera.
“Legacy incumbents offer on-premise or on-truck software that has seen very little innovation in the last 20 years,” Rosenthal said. “SeaverAI’s technology increases the top and bottom line by performing more inspections per day at a lower cost.”
SewerAI is not alone in the nascent market for AI-assisted pipe inspection. The company’s competitors include Subterra, which maps, analyzes, and predicts problems with pipelines; Clear Objects, which provides software that analyzes footage from pipe inspections for damage; and Palon, which develops algorithms to spot potential problems inside sewers from still images.
Rosenthal claims that what sets SewerAI apart is the quality of its data – specifically the quality of its model training data. Rosenthal says SewerAI has footage of 135 million feet of pipe inspections from municipalities and independent contractors. Rosenthal says that while this is a small portion of the 6.8 billion feet of sewer pipe in the US, it is a large enough data set to train a competitive defect-detection AI.
“Our products streamline field inspections and data management, allowing customers to proactively manage infrastructure rather than reacting to emergencies,” Rosenthal said.
SewerAI’s sales pitch won over investors like Innovius Capital, which, among others, put $15 million into SewerAI’s most recent fundraising round. This brings the total amount raised by SewerAI to $25 million, with the cash to be used for market expansion, AI model training, recruitment, and expanding SewerAI’s product portfolio beyond inspection tools.
“SeaverAI continues to grow, and we’re seeing demand for our platform accelerate as we enable people to do more with existing budgets, resulting in us closing our first seven-figure contracts,” Rosenthal said.
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