Data Annotation

Don't make your AI model fail because of inaccurate or incomplete training data. We assist you in developing effective, production-grade machine learning models with extremely accurate and scalable data annotation solutions. From 2D bounding boxes to 3D LiDAR point cloud annotation, we provide pixel-perfect labels that help machines see, interpret, and predict real-world situations.

We possess a seasoned annotation team with deep experience in automotive AI datasets, particularly vehicle detection, tracking, and classification. Whether you're developing models for autonomous driving, fleet management, or traffic analysis, our workflows are designed to satisfy your project's toughest requirements.

  • Annotating vehicles (cars, trucks, buses) in 3D point clouds across multiple frames

  • Precise pedestrian and cyclist detection in dense urban and mixed traffic environments

  • Frame-by-frame object tracking to capture object movement and continuity over time

  • Applying 3D bounding boxes to define object dimensions, location, and orientation

  • Annotating LiDAR point clouds frame-wise for accurate temporal labeling

  • Differentiating objects by class (e.g., car, truck, pedestrian, cyclist, traffic cone, etc.)

  • Handling occlusions and partial detections with expert labeling standards

  • Labeling static and dynamic scenes in varied lighting, weather, and road conditions

  • Syncing annotations across multi-sensor data (LiDAR, camera, radar)

  • Conducting quality assurance checks on every frame for consistency and accuracy