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Embodied AI dataset production

Upgrade embodied-AI dataset work from one-off labeling into a reusable production asset with review, versions, delivery, and acceptance.

Embodied AI dataset production3D point-cloud workflowDelivery summary

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

Embodied AI dataset production

Upgrade embodied-AI dataset work from one-off labeling into a reusable production asset with review, versions, delivery, and acceptance.

Embodied AI dataset production

Focus on dataset production, orchestration, version tracking, and delivery acceptance instead of one-off labeling.

Delivery summary page

A standard summary for acceptance, reporting, and customer handoff instead of a raw link.

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
Vertical Focus

Recommended next step

Start with 2D/3D Studio for fast hands-on work, move to Workflow Cloud for shared review and training, or choose Enterprise options for private deployment and advanced controls.