Mach9 Raises $34M Series A to Turn 3D Scans Into Engineering Drawings 10x Faster
Mach9 has raised $34M in Series A funding co-led by First Round Capital and Bessemer to scale AI software that converts 3D infrastructure scans into engineering drawings.

The most expensive line item in a civil engineering project is rarely the concrete or the steel. It is the waiting. Before a road can be widened or a utility network upgraded, someone must survey what is already there and convert those measurements into drawings engineers can build from — a hand-plotting exercise that can stretch across weeks or months. Mach9, a San Francisco company, has just raised $34 million in Series A funding to compress that timeline with AI, and the round says as much about where infrastructure capital is flowing as it does about the software itself.
The Series A was co-led by First Round Capital and Bessemer Venture Partners, with Prudence participating alongside existing investor Quiet Capital. Mach9's platform takes 3D scans of roads, construction sites and utility networks and uses AI to detect physical objects — curbs, sign posts, poles, lane markings, wires — then generates initial engineering drawings with claimed centimetre-level accuracy. The company says the work is completed up to 10 times faster, at one-fifth the cost, of manual methods. The new capital is earmarked for enhancing the software, expanding the team and deepening capabilities for surveying and civil engineering customers.
Mach9 did not start out in civil engineering. It emerged in 2021 as a hardware-focused startup, and co-founder and chief executive Alex Baikovitz was initially working on visual inspection technology. Customer conversations pulled the company toward a bigger problem: much of America's infrastructure is nearing the end of its intended service life, and roads, utility poles and power lines must be replaced or maintained. The $1.2 trillion Infrastructure Investment and Jobs Act sharpened the urgency, but accurate as-builts — the records of what is actually in the ground — remain the bottleneck before any modification can be planned. Mach9's customer list shows the commercial pull: engineering firms WSP, HNTB and NV5, and public agencies including Caltrans, the Minnesota Department of Transportation and the Maryland State Highway Administration. Caltrans has used the platform in San Diego to inventory road-safety features along Interstate 8, mapping rumble strips and flagging improvement opportunities; Kier + Wright has applied it to pedestrian safety around San Francisco schools; Louisiana-based Fibersmith has used it for broadband planning aimed at connecting 125,000 homes and businesses.
For readers tracking African infrastructure capital, the relevance is structural rather than direct. Mach9 is a American company selling into American agencies, and nothing in this round points to African operations. But the same arithmetic that made the company fundable — ageing assets, surveying shortages, pressure on engineering teams — describes much of the continent's project pipeline, where roads, power networks and fibre routes are being built and rebuilt at pace. African governments and developers increasingly lean on reality-capture surveys and digital design tools to avoid costly rework, and the firms that supply those workflows are attracting venture money abroad. First Round Capital partner Bill Trenchard framed the software as a way to turn physical infrastructure into actionable information — a pitch that travels well beyond one market.
The obstacles are real. Engineering drawings demand high accuracy, and AI-generated outputs require careful validation before professionals will stake projects on them. Mach9 also competes with established CAD providers, and adoption hinges on whether its tools slot into existing workflows and hold consistent accuracy across different environments. Surveying shortages and ageing assets keep the pressure on engineering teams, which is precisely the constraint the funding is meant to address. The longer-term ambition is to improve how projects move from data collection to design. For a sector where the costliest input is often time, that is a bet worth watching.


