Dark Motion AI dashboard showing robot instruction and modality panels

Context retrieval for physical work

Turn motion into process understanding

Motion AI recognizes patterns in human movement, connects them with formal work steps, and creates usable execution context without frame-by-frame manual annotation.

More than recognition

Understand what happened—and what it meant

Motion becomes valuable when it is connected to the task, the object, and the documented process.

01

Detect

Identify grasping, repetition, and customer-trained motion patterns.

02

Align

Connect observed actions with a checklist or formal process document.

03

Enrich

Add spoken expert descriptions, visual context, and object handling.

04

Structure

Create reviewable work steps and execution records.

Motion AI platform with dataset upload, process timeline, and annotation tools

The Motion AI workspace

Manage processes, models, and captured sessions

The platform connects devices, sets up processes, maps AI models, and receives raw and annotated motion data—the operational layer between capture hardware and customer workflows.

DevicesConnect gloves and supporting capture hardware.
ProcessesDefine steps, review sessions, and link documentation.
ModelsTrain and deploy focused recognition models.

How it works

From capture to deployment

  1. Capture

    Collect motion from Mimetik gloves and optional body, camera, or external systems.

  2. Interpret

    Models identify action patterns while process documents supply task semantics.

  3. Review

    Teams correct detected steps and add missing context in the platform.

  4. Deploy

    Use the model for assistance, documentation, analysis, or dataset preparation.

Worker using a Mimetik glove while action data is visualized

Reduce annotation effort

Retrieve work context while the data is created

In Mimetik pilots, motion recognition automatically translated about 60% of hand motion into work steps. Alignment with formal documentation completed the process context.

This is pilot evidence, not a universal performance guarantee. Results depend on the process, model, sensors, and quality of the available documentation.

Motion AI process recording demonstration

Process demo

Motion AI process recording

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Operational outcomes

One motion layer, multiple uses

Worker assistance

Recognize the current step and surface concise, relevant guidance.

Process intelligence

Document actual execution, variation, and potential bottlenecks.

Training data

Build structured action context for selected humanoid-training datasets.

Give motion meaning

Show us one representative workflow

We will outline the smallest useful Motion AI pilot and the context sources it needs.