I will annotate lidar point clouds, 3d data and images using cvat

I help AI and machine learning teams get clean, accurately labeled training data the kind that actually improves model performance instead of introducing noise.

Ideal for startups, AI labs, and ML teams needing anywhere from a few hundred to several thousand annotated frames.

With close to 4 years of hands-on experience through Scale AI's Remotasks platform, I specialize in:

• 2D/3D image and video segmentation (polygon, cuboid)
• LiDAR point cloud annotation for autonomous systems
• Semantic segmentation and bounding box labeling using CVAT and Label Studio
• Data quality review and consistency checks

I've maintained a 98% accuracy rate across annotation projects while following detailed, project-specific guidelines. I provide clear written updates throughout the project, so you always know exactly where things stand.

If you're building a dataset for computer vision, autonomous vehicles, robotics, or any ML application, I can help you get it labeled accurately and on time.

Check out my portfolio link in my profile to see real annotation samples.

Check my packages below, or message me with your project details (image count, format, complexity) for a custom quote.