Target coverage
A production integration should know whether it needs animation output, robot output, custom-avatar workflows, or a mix of target types.
MOCAP API
AI mocap API for production pipelines
Use AIMoCap API v-credit, async jobs, and target-aware outputs to add AI video mocap to production tools.
For product teams evaluating an AI mocap API with public documentation.
Short answer
An AI mocap API should turn uploaded source video into structured motion outputs while keeping target selection, usage accounting, and result downloads explicit.
When to use AIMoCap
Use AIMoCap when a product needs upload-based video mocap for Default animation output, Unitree G1 robot output, or both, with API v-credit separated from Studio credits.
When not to use AIMoCap
Do not use AIMoCap's API when the integration needs real-time live capture, undocumented private targets, or a one-call synchronous solve that blocks until all artifacts are ready.
People searching for an AI mocap API are usually evaluating whether a video-to-motion capability can become part of a product workflow, not just whether a demo page exists.
AIMoCap's public API is intentionally target-aware. A client can request animation-oriented Default output, Unitree G1 robot-oriented output, or both when the account and job limits allow it.
The important boundary is product fit. API v-credit, supported targets, trim fields, export FPS, queue behavior, and downloadable artifacts should be reviewed before the API becomes a production dependency.
AI mocap API product-fit facts
- The public API is upload-based and asynchronous.
- Default and Unitree G1 are the supported public API target families.
- API v-credit is separate from web Studio credit.
- A single API job can request multiple supported outputs when allowed.
- Trim fields and export FPS are integration controls, not promises that every source clip produces clean motion.
- Source video quality, occlusion, camera motion, and downstream cleanup still affect result usefulness.
- AIMoCap returns motion artifacts; it is not a real-time capture SDK or robot controller.
What to evaluate before adopting an AI mocap API
Use these facts to decide whether this workflow matches your output, integration, and cleanup needs.
Usage accounting
API v-credit makes automated jobs visible separately from web Studio usage, which matters for billing, quota, and account ledgers.
Failure boundaries
Upload, validation, queue admission, processing, and result download are separate states, so clients should handle retries and terminal failures explicitly.
AI mocap API evaluation workflow
01
Choose the output target
Decide whether the integration needs Default FBX-oriented motion, Unitree G1 robot-oriented artifacts, or a combined job for review and robotics workflows.
02
Estimate usage and limits
Plan around API v-credit, trim duration, file size, export FPS, and concurrency before sending user video into an automated pipeline.
03
Integrate the async lifecycle
Create the job, upload source video, complete upload, poll status, and download artifacts only after the job reaches a terminal completed state.
Common questions
What makes AIMoCap an AI mocap API instead of only a web tool?
The API exposes an upload, complete-upload, status polling, and result download workflow so a product can automate supported video mocap jobs instead of requiring manual Studio-only operation.
Which outputs should an AI mocap API integration request?
Use Default for animation-oriented FBX review and Unitree G1 for robot-oriented motion output. Request both only when the integration needs both artifact families from the same source clip.
Does API usage share web Studio credits?
No. API jobs use API v-credit so automated product usage can be tracked separately from web Studio credits.
Can AIMoCap guarantee clean motion from any uploaded video?
No. AIMoCap processes source video into motion artifacts, but source quality, occlusion, framing, and downstream cleanup still matter.
Related AIMoCap guides
Continue through this topic cluster to compare output formats, API options, and workflow boundaries.
Sources reviewed
Competitor details are summarized from public official pages and public community or review discussions. Community feedback is treated as directional signal, not as a universal product claim.