Autonomy software and hardware for off-road industrial vehicle fleets
ASI builds autonomy systems for off-road vehicles, pairing ROS 2, LiDAR and GPS/GNSS with a C++, C# and Java codebase managed in Azure DevOps and Jama Connect. Hiring is overwhelmingly senior engineering, and repeated pain points around validation efficiency and test scaling show verification is the bottleneck as autonomous dozer and commercial mowing programs move toward field deployment.
Notable leadership hires: Chief Engineer
Autonomous Solutions, Inc. (ASI) develops robotic hardware and software that make industrial vehicles operate autonomously, including its Mobius fleet management system. The company serves operators in heavy construction, agriculture, logistics and landscaping. Founded in 2000 and privately held, ASI employs 201–500 people and is headquartered in Mendon, Utah, where it runs a proving ground, with additional offices in Salt Lake City and Dallas/Fort Worth. Current hiring is concentrated in the United States.
ASI uses C++, C#, Java and Python with ROS 2, LiDAR and GPS/GNSS for autonomy, plus Azure DevOps, Jira and Jama Connect for engineering, and SolidWorks, CATIA and Pro/ENGINEER for mechanical design.
Yes. Engineering dominates ASI's hiring, skewed toward senior roles, with a Chief Engineer search underway and smaller openings in sales, product, support and construction, all in the United States.
ASI is developing autonomous vehicle platforms including an autonomous dozer, path planning for agricultural operations, its Mobius autonomy software, and expanding autonomous commercial mowing in the Southeast.
Other companies in the same industry, closest in size
Autonomous Solutions, Inc. (ASI)'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.