LiDAR, sensor fusion and real-world driving scenarios.
Overview
AI in Autonomous Vehicles
Autonomous vehicle AI needs the most demanding annotation pipelines in the industry: 3D point clouds, multi-camera sensor fusion, temporal tracking and complex urban scenarios. Safety-critical AI needs safety-critical data.
Key challenges
- 3D LiDAR point cloud annotation at scale across diverse environments
- Multi-sensor fusion alignment across camera, radar and LiDAR
- Long-tail scenario coverage for rare edge cases critical to safety
- ASIL-B automotive safety standard compliance
Our solutions
How we help
- 01Specialized 3D bounding box and semantic segmentation pipelines
- 02Cross-sensor annotation with consistency validation across modalities
- 03Curated scenario libraries for rare event and edge case coverage
- 04ASIL-aligned QA with full traceability documentation
Results
94%Model accuracy improvement
3MImages annotated
6 wksFaster deployment
Power yourautonomous vehicles AI
Start with a scoped pilot: results in weeks, not months.