Case Study: SmartCity achieves 99.7% annotation accuracy and accelerated AV deployment with Shaip

Shaip's LiDAR Annotation Project for SmartCity Autonomous Vehicles

SmartCity engaged Shaip to supply large-scale LiDAR and camera data annotation for its autonomous vehicle rollout, needing accurately labeled 2D and 3D sensor data from 15,000 frames (3 Velodyne VLP-32C LiDARs and 4 high‑resolution cameras). The project faced tight timelines (4 months), high data volume and complexity, diverse urban environments, the need for consistent object IDs across sensors and frames, and strict privacy masking requirements.

Shaip staffed a 50-annotator team with 10 quality controllers and 3 project managers, deployed proprietary integrated 2D/3D annotation tools, AI-assisted pre-annotation, multi-stage quality checks, and targeted training on privacy rules. Shaip finished in 3.5 months (two weeks early), delivered 99.7% annotation accuracy, labeled over 450,000 unique objects with 98% ID consistency, properly masked plates and faces, and helped SmartCity reduce real-world AV testing time by 30%.

SmartCity