Autonomous driving data loop
Cover 2D images, 3D point clouds, low-confidence fallback, human review, KITTI/YOLO export, and model delivery.
Keep annotation, review, training, and delivery in one workflow
Start from uploads, API tasks, or automated jobs, then move through AI pre-labeling, human review, cloud training, export, and delivery without switching systems.
Start projects from uploads, APIs, or shared workflows
Combine AI speed with human review for quality control
Keep training, export, and delivery connected
Add security, audit, permissions, and private deployment when needed
One workflow for autonomous driving, robotics, and embodied AI
Robot video and perception tasks
Fit robot-video, scene-understanding, and grasping pipelines where agent tasks need human review and training handoff.
Embodied AI dataset production
Focus on dataset production, orchestration, version tracking, and delivery acceptance instead of one-off labeling.
Industrial vision and enterprise rollout
Support industrial-vision and enterprise projects with secure access, review controls, delivery summaries, and private deployment options.
Keep annotation, review, training, and delivery in one workflow
Start from uploads, API tasks, or automated jobs, then move through AI pre-labeling, human review, cloud training, export, and delivery without switching systems.
01
Bring uploads, API tasks, and automated jobs into one workspace
Manage manual uploads, API requests, and automated tasks in the same workflow so every project stays visible and organized.
02
Let AI move first, then hand key checkpoints to humans
Pre-labeling and automation move fast, while low-confidence items and key checkpoints return to the pro editor for human review.
03
Chain training, export, and artifact handling automatically
Once review is complete, training, export, and model delivery continue automatically so customers do not have to stitch the flow together themselves.
04
Make the delivery summary the acceptance object
The end result is not just a download link, but a traceable summary with metrics, versions, and delivery entry points.
What a standard delivery summary should include
Workflow state, current phase, and timeline
Human-review outcome and approval notes
Training metrics, export formats, and model versions
Download entry, handoff link, and shareable summary page