4D volumetric mapping platform using LiDAR, HD imaging, and sensor fusion
Voxelmaps builds high-resolution geospatial datasets through mobile mapping—LiDAR and HD imagery combined with GNSS and IMU fusion. The engineering-heavy hiring mix (6 roles) and active projects on SLAM pipelines, sensor fusion, and point-cloud registration suggest they're scaling data collection and localization accuracy. Pain points around drift reduction and multi-session alignment point to core technical challenges in large-scale, repeatable mapping operations.
Voxelmaps develops a 4D volumetric digital twin platform for mapping and machine perception, drawing on 16+ years of geospatial experience through its parent company Navmii. The product combines high-resolution mobile mapping data (650,000+ linear miles collected in 2020 alone) with LiDAR, HD imaging, and sensor fusion to serve large technology companies and autonomous vehicle applications. The company operates with 201–500 employees and is actively hiring across engineering, data, and operations roles in the US, Portugal, and UK.
Python, C++, ROS/ROS 2, .NET/C#/ASP.NET Core, React, AWS, Docker, PostgreSQL/MySQL/SQL Server, plus geospatial libraries: GTSAM, Open3D, OpenCV, GDAL, and LiDAR/GNSS processing tools.
SLAM pipelines, sensor fusion (LiDAR/camera/GNSS/IMU integration), point-cloud registration, multi-session localization, and operationalizing cross-border data collection workflows for autonomous vehicle and robotics applications.
Voxelmaps'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.