Mach9 Raises $34M to Accelerate AI Civil Engineering

Mach9 has successfully secured $34 million in Series A funding to enhance its AI-powered civil engineering software. The round of investment was jointly led by First Round Capital and Bessemer Venture Partners, with Prudence joining as an additional investor. Mach9, a San Francisco-based company, specializes in creating computer-aided design software for surveying and infrastructure projects.

Their technology converts 3D scans into digital blueprints, enabling engineering teams to work more efficiently. The software can complete this process up to 10 times faster and at a fifth of the cost of traditional methods. Emerging from a hardware-focused startup founded in 2021, Mach9 initially aimed to improve visual inspection technology but found a more pressing issue among customers.

The need for accurate as-builts to prevent costly rework in infrastructure projects is significant. The Infrastructure Investment and Jobs Act allocated $1.2 trillion for infrastructure investment, highlighting the urgency of addressing aging assets and surveying shortages. Mach9's AI-powered platform captures reality-capture surveys, which are then used to generate initial drawings with centimetre-level accuracy.

The software is utilized by various customers, including transportation agencies, engineering firms, and telecommunications providers. Notable users include WSP, HNTB, NV5, Caltrans, Minnesota Department of Transportation, Maryland State Highway Administration, and Fibersmith. Public-sector users like Caltrans and the Maryland State Highway Administration employ Mach9 to inventory road-safety features and plan maintenance.

In San Francisco, Kier + Wright leverages the platform to support pedestrian safety around schools. By automating the process of converting 3D scans into digital blueprints, Mach9 aims to modernize how infrastructure is surveyed, designed, and maintained. The company plans to use the new capital to expand its software capabilities and team, ultimately working towards improving the efficiency of infrastructure projects from data collection to design.