Physical AI Training Data
End-to-end physical AI data: LiDAR annotation, 3D sensor fusion, in-cabin automotive intelligence, biometric human-centric data, and world model collection at scale.
Data Capabilities
Four specialised services for teams training embodied, physically-grounded AI systems.
3D Sensor Fusion & LiDAR Annotation
Precise 3D bounding boxes, point cloud segmentation, and multi-sensor fusion labeling for autonomous vehicles, drones, and robotic systems. Appen's annotators are trained to label across LiDAR, radar, and camera feeds with the consistency that safety-critical applications require.
Biometric Human-Centric Data
Ethically collected motion capture, facial expression labeling, gaze tracking, and gesture annotation that teach AI to understand human behaviour and physical intent. All collection operates under responsible AI consent frameworks.
In-Cabin Automotive Intelligence
Multi-sensor annotation for driver monitoring systems, occupant detection, gaze and gesture recognition, and voice command integration. Appen supports automotive OEMs and Tier 1 suppliers building the in-cabin AI layer for next-generation connected vehicles.
World Model Data Collection
Large-scale egocentric video, environmental scene capture, and interaction data for teams training world models and embodied AI agents. Appen's global field operations collect in diverse physical environments at the scale and diversity that world model training demands.
Case Studies
How leading AI organisations trust Appen for multimodal & physical ai data.
How Nearmap Scaled AI Data Labeling for Aerial Imagery
Computer vision annotation pipeline for high-volume aerial and 3D imagery, enabling precision geospatial AI models.
Training an LLM Image Generator for Graphic Design in 20+ Languages
Multimodal dataset creation enabling image generation that is contextually accurate across language and cultural dimensions.
How Onfido Optimized AI Fraud Detection
Identity document and facial recognition data to power robust, bias-mitigated fraud detection at global scale.
Ready to build with confidence?
Talk to our team about physical AI training data, from LiDAR annotation and sensor fusion to world model data collection at scale.