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// field_data_capture

Real-world data from the environments where your AI must perform.

Physical AI needs data from warehouses, factories, farms, retail stores, roads, facilities, and messy real-world operating conditions. The Field Data Capture Network is how Datafy Lab designs and runs that capture — with consent, metadata, QA, and delivery standards across every program.

// standards

Consent, metadata, QA, delivery.

Every capture program runs on documented standards so the data is usable, defensible, and training-ready — not just footage on a drive.

field_program.standards
01Consent & rights framework
02Capture spec & site coordination
03Sensor-assisted collection
04Metadata & environment tagging
05QA & delivery standards
// faq

Common questions

Yes. We design and execute field capture programs across warehouses, factories, retail, farms, roads, and facilities with consent, metadata, QA, and delivery standards.
First-person, human point-of-view footage of tasks — a core part of field capture for embodied AI and imitation learning.
Object tracking, segmentation, keypoints, temporal/action labels, defect labels, scene metadata, and failure categorization on captured field data.
Every program runs on a documented consent and rights framework with privacy review, reflected in the Model-Ready Data Certificate.
Yes — we can extend or fill gaps in your data with targeted field capture aimed at your model's failure clusters.
Book a scoping call or a Data Failure Audit, and we'll design a field capture program around the data your model needs next.
Not sure what data your model needs next?Book a Data Failure Audit