Robot video and scene understanding
Put video decoding, AI pre-labeling, human review, and training handoff in one workflow instead of across multiple systems.
One platform for 2D/3D annotation, review, training, and export
TjMakeBot helps autonomous-driving, robotics, and embodied-AI teams manage 2D/3D annotation, human review, cloud training, model export, and delivery in one platform.
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
Solutions for autonomous driving, robotics, embodied AI, and industrial vision teams
Autonomous driving and vehicle perception
Build a closed loop around 2D images, 3D point clouds, low-confidence fallback, human review, training/export, and delivery summaries.
Embodied AI dataset production
Upgrade embodied-AI dataset work from one-off labeling into a reusable production asset with review, versions, delivery, and acceptance.
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