Robotics
AI.
Specialized data annotation for robotic perception, embodied AI, and autonomous systems — LiDAR, sensor fusion, manipulation video, and action labeling at production scale.
What we do for Robotics teams
LiDAR Point Cloud Annotation
3D bounding boxes, instance segmentation, and ground plane labeling on LiDAR scans for robotic perception.
Robot Action Labeling
Action sequence annotation, task segmentation, and goal state labeling for imitation learning and behavior cloning.
Embodied AI Datasets
Scene understanding annotation, object affordance labeling, and spatial relationship tagging for embodied agents.
Sensor Fusion Annotation
Cross-modal labeling combining camera, LiDAR, radar, and depth sensor data for robust perception pipelines.
Manipulation Video Labeling
Frame-level annotation of robot manipulation tasks — grasp events, contact points, and trajectory labeling.
Model Evaluation
Human assessment of robot perception and decision outputs against ground-truth performance benchmarks.
Use Cases
Robotics and embodied AI require annotation teams that understand 3D space, temporal sequences, and sensor modalities. Our annotators are calibrated specifically for robotic data types and trained on your task taxonomy before production begins.
Building a robot that learns?
Tell us your data modality and task type — we'll propose a calibration-first pilot.