We source hands-on POV and workbench footage from real production environments, then build the filtering, segmentation, annotation, metadata, and event-tagging workflows that turn raw video into training-ready datasets. We provide the footage and build the pipeline that makes it usable.
First-person and workbench footage of skilled operators performing real, repetitive, multi-step tasks — the behavior robotics and CV models actually need to learn from.
Our engineers build the workflow that converts hours of raw capture into filtered, segmented, tagged, annotated, and metadata-rich datasets — designed for your model under training.
The same dataset can feed several downstream model objectives, from imitation learning to operational analysis.
Delivery includes the footage, the structured outputs, and the documentation so the workflow keeps producing data after the engagement.
Operational footage and worker imagery are sensitive. We handle them under NDA-default workflows and capture only what the task needs.
Tell us the environment, the tasks, and your model objective. We'll scope a capture-and-pipeline plan for a first dataset.
