San Francisco: SewerAI, a startup that uses artificial intelligence and computer vision to inspect, identify and analyze sewer infrastructure defects before they reach catastrophic levels, announced that it has secured $2 million in seed funding led by venture capital firms Builders VC and EPIC Ventures.
SewerAI was established by sewer infrastructure inspection technology veterans to address the massive problem of aging pipe infrastructure—with over 6 billion feet of sewer pipe in just the U.S. alone, approximately 3 billion feet are in need of repair or replacement. US municipalities spend approximately $50 billion each year maintaining this infrastructure, mainly using manual inspections, data delivered via physical disks, and desktop-based software. SewerAI harnesses the power of artificial intelligence and computer vision, along with a cloud workflow platform to automatically detect pipeline defects, allowing sewer inspections to be completed in a fraction of the time with increased accuracy.
“The cost to state and local communities to maintain and repair aging pipes, and the cost of system failures, are in the billions of dollars,” explained SewerAI CEO Matthew Rosenthal. “Utility companies and engineering firms help to manage the problem of aging pipes by deploying robotic cameras to identify defects, collecting tens of thousands of hours of video each day that are manually reviewed and assessed in a painstaking and time consuming process. This inspection process is typically slow, expensive, and inconsistent—not to mention subject to human error.”
Matt Rosenthal and Bill Gilmartin have separately been working in the industry for more than 10 years and have a unique combination of technical capability and real-world operational experience. They have prior experience and seeing the problems for 10+ years and that is what led to this AI that is solving real industry problems.
SewerAI’s groundbreaking AI, cloud-based software AutoCode™ significantly enhances and accelerates this sewer infrastructure inspections.
“With our technology, sewer inspection crews in the field can now change their workflow to survey significantly more feet of pipe per day,” continued Rosenthal. “Machine learning training dataset consists of millions of feet of labeled video inspection data, all reviewed and validated by our expert labelers. This training dataset grows every day, allowing SewerAI AutoCode to gain intelligence with every foot of inspection processed through the SewerAI IMP. As the data comes in, our clients save money, accelerate their work flows, and receive more accurate asset information than ever before.”