AI computer vision for sewer pipeline inspection and asset management
SewerAI sells a cloud platform that uses computer vision to auto-code sewer pipeline inspection video for utilities, contractors and engineers. The stack pairs PyTorch, TensorFlow, SageMaker and MLflow with PostGIS for geospatial pipe data, while a sales-heavy hiring mix plus Salesforce, Outreach, Gong and ZoomInfo signals a push to scale go-to-market, with RevOps pain around data discrepancies, routing gaps and quota alignment.
Notable leadership hires: Product VP
SewerAI, founded in 2019 and headquartered in Walnut Creek, California, builds software for condition assessment of underground sewer infrastructure. Its web platform, Pioneer, lets contractors, utilities and engineering firms upload inspection footage, review condition reports, exchange submittals and coordinate capital planning. AutoCode AI detects defects in footage captured by CCTV crawlers, side scanners, drones and other cameras. The privately held company employs 51–200 people and hires within the United States.
SewerAI runs TypeScript, React and Node.js on AWS with EKS, Kubernetes and Terraform, stores data in PostgreSQL/PostGIS and ClickHouse, and builds ML with PyTorch, TensorFlow, SageMaker, MLflow and Weights & Biases.
Yes. Sales is the dominant hiring area, alongside operations, product, support and an executive Product VP role, all based in the United States.
Current initiatives include AI-assisted RevOps tooling, territory design, quota and capacity planning, a customer evidence engine, and standardizing professional services intake and delivery visibility.
Other companies in the same industry, closest in size
SewerAI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.