LiDAR Annotation – Solvitude

Solvitude

Our teams can label and classify a wide range of elements within 3D environments:

Vehicles and cyclists
Pedestrians
Roads and lanes
Buildings and structures
Traffic signs and signals
Trees and vegetation
Road barriers and infrastructure
Terrain and surfaces
Indoor environments
Custom objects based on project requirements

Raw LiDAR data contains millions of points, but without meaningful labels, AI cannot effectively learn from them. Solvitude transforms complex 3D sensor data into structured datasets that help intelligent systems perceive, interpret, and navigate real-world environments.

Mapping the World in Three Dimensions

Accurately identify and classify vehicles, pedestrians, structures, roads, and other objects within complex 3D environments.

Capture object dimensions, distance, position, and spatial relationships to help AI systems understand real-world environments.

Create structured 3D datasets for autonomous vehicles, robotics, mapping, smart cities, and advanced computer vision applications.

Transform raw LiDAR and point cloud data into structured 3D datasets by accurately identifying objects, surfaces, boundaries, and spatial relationships for advanced AI and computer vision systems.

What We Annotate

From Point Clouds to AI-Ready Intelligence

Drive efficiency
& performance with Solvitude