Full-Time
Automates LiDAR scans into 2D/3D models
$200k - $250k/yr
San Francisco, CA, USA
In Person
Must be willing to travel up to 50%.
Mach9 provides geospatial software that converts large-scale mobile LiDAR scans into 2D and 3D engineering models. It operates as a software-as-a-service where clients upload project data and Mach9’s AI-powered processing converts image and point cloud data into actionable maps and models. The product differentiates itself from competitors by delivering faster processing (up to 30 times faster) and lower costs (about half the traditional manual methods) through automated AI workflows on scalable cloud processing. The company’s goal is to help surveying, engineering, and construction firms generate accurate, ready-to-use models efficiently so they can focus on core tasks and project delivery.
Company Size
11-50
Company Stage
Seed
Total Funding
$14.4M
Headquarters
Pittsburgh, Pennsylvania
Founded
2021
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Professional Development Budget
Mach9 unveils an ai-assisted workflow focused on trust and control at scale. For surveyors working on sprawling transportation projects or complex utility corridors, the promise of AI comes with a catch. When the AI finishes processing and presents a lengthy dataset extraction, how do you verify it's correct? Where do you even start? This tension between automation's efficiency and a surveyor's desire for preciseness has shaped the evolution of Mach9's latest release of Digital Surveyor, which will debut at Geo Week 2026. Following a year of customer feedback - especially from teams overseeing complex, extended projects - the company chose to reimagine AI usability and strengthen confidence in its outputs by redesigning their workflow to center on interactive collaboration between AI and surveyors. "If ChatGPT just spits out a 40-page essay and you have to read the whole thing in order to understand all the places it's hallucinated to fix it, it's overwhelming," explains Alex Fischer. "It's not how you want to work. You'd rather work with AI to write that essay in real time, incorporating and accepting suggestions and also incorporating your own work along the way." That analogy captures the core challenge Mach9 set out to solve. Even when automated extractions were technically accurate, reviewing the entire output felt like archaeology, sifting through results to find potential errors rather than building the deliverable with confidence from the start. Bridging the gap from reality capture to production. The shift in workflow philosophy addresses a problem that extends beyond any single software tool: interoperability. Reality capture technology has advanced dramatically, with surveyors collecting increasingly rich datasets in the field. Yet translating that data into usable CAD and GIS models for engineers, designers, and construction teams remains a persistent bottleneck. That gap puts added pressure on surveyors to validate and shape data before it reaches downstream teams. "There's a huge challenge between taking reality capture data or geospatial data and turning it into usable CAD and GIS models," says Alexander Baikovitz. "There's all this great data that people are collecting out in the field, but often, rarely does it get to those that are making the designs themselves." Mach9's approach positions surveyors not just as creators of preliminary design maps, but as stewards of spatial lidar data, responsible for transforming it into actionable maps and models that different parts of an organization can actually use. This requires more than just extraction algorithms; it requires workflows that let surveyors maintain quality control while moving at the pace modern projects demand. From output review to real-time collaboration. The rebuilt workflow represents a fundamental rethinking of how AI assists during the process. Rather than generating complete automated outputs for later review, the system now works alongside surveyors as they build deliverables, offering suggestions and intelligent assistance at each step. Key improvements include clearer feedback during data selection, smarter snapping that helps geometry land where surveyors expect it, and quality assurance integrated directly into the work process. The result is a production environment where surveyors can create finished deliverables with confidence, then export them to CAD and GIS systems for downstream processing. This release specifically targets professionals working on corridor and site projects, transportation corridors, utility infrastructure, and DOT work where extraction has long been a major bottleneck. These projects are often massive in scale and complexity, with deliverable requirements that demand both speed and precision. The trust problem at scale. "Once automation works, the hard problem becomes trust, control, and usability at scale," Baikovitz emphasizes. "That's what this release is really all about, providing surveyors with the ability to create maps really fast while having control for what those maps look like and how they're delivered." It's a problem that only becomes apparent when automation starts working well enough to handle real production work. The technology can extract features accurately, but if surveyors can't easily verify that accuracy or adjust results to meet client specifications, the automation creates as many problems as it solves. Trust requires transparency, understanding what the AI is doing and maintaining control over the final product. Experience the new workflow at Geo Week. Geo Week 2026 will mark the first public demonstration of this rebuilt approach. The Mach9 team recognizes that the new workflow and integrated quality assurance are difficult to appreciate through screenshots or written descriptions alone. They need to be experienced hands-on, with real data and real project scenarios. The company plans to sit down with surveyors and geospatial professionals throughout the event, walking through actual projects and allowing attendees to work directly with the new tools. For those managing large-scale extraction projects or struggling with the transition from field data to final deliverables, it's an opportunity to see how the balance between AI assistance and human control is being recalibrated. About Digital Surveyor Digital Surveyor provides AI-assisted software solutions for surveying professionals, focusing on transforming reality capture and geospatial data into actionable CAD and GIS models for engineering, construction, and operations professionals. 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Earlier this month, the Pittsburgh Business Times reported that Mach9, a geospatial software startup that was headquartered in Bloomfield, had raised $14.4 million per Securities and Exchange Commission filings and Pitchbook data.
Mach9 has raised $12 million in a seed funding round led by Quiet Capital, with participation from investors like Overmatch Ventures and Kyle Vogt. The funding will support team growth and product development for their AI-powered geospatial mapping solution, Digital Surveyor. This tool converts LiDAR scans into digital maps, significantly speeding up mapping processes. Mach9's technology is already aiding infrastructure partners like Michael Baker International and POWER Engineers.
Listen to this articleFaster production of mapping data can cut costs for the construction industry, says Mach9. Source: Mach9 Robotics. Autonomous vehicles, delivery robots, and aerial drones all rely on geospatial data, as do construction and utility firms. Mach9 Robotics Inc. said it takes 3D data from lidar scans and turns it into 2D and 3D engineering models faster and cheaper than with conventional methods. “Just as CAD software allowed GPS to revolutionize the surveying industry, we set out to build powerful tools that could unlock the potential of mobile mapping,” said the company
The Securities and Exchange Commission has not necessarily reviewed the information in this filing and has not determined if it is accurate and complete.The reader should not assume that the information is accurate and complete.