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Egocentric data collection · Agriculture & outdoor work

Real-world data from the field.

We collect egocentric video, hand interaction and motion data from real agricultural and outdoor work (harvesting, planting and everyday field tasks) for teams building Physical AI and robotics.

Changing daylight, uneven ground and unstructured surroundings, captured as they actually happen.

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Proof of value

Real hours,
delivered.

Across the environments we work in (agriculture included), we don't argue data quality on a call. We ship footage, teams run it through their own pipelines, and the next order follows.

80,257

hours of first-person footage delivered

Shipped to teams and running in their pipelines today, and counting.

What we capture

Field and outdoor tasks,
as they're actually done.

Picking and harvesting, stripping and sorting plant material, and the walking, reaching and ground-handling that surrounds every outdoor task.

Picking marigold and chrysanthemum blooms into a crate, seen from the picker's own viewpoint.
Two hands stripping leaves from a stem in a field.
Walking through tall grass, looking down at the ground ahead.
Standing over uneven stone ground at an outdoor work site.

Sessions are recorded from the worker's own point of view, so models see the hand positioning, tool grip and terrain judgment involved, not a fixed third-person camera looking on.

Why outdoor data

Outdoor conditions don't repeat themselves.
Field data has to reflect that.

  • 01

    Changing light

    Field work happens across a full day, in daylight that shifts constantly, not a controlled indoor rig.

  • 02

    Uneven, unstructured ground

    Terrain, crop rows and loose surfaces change how people move, reach and balance.

  • 03

    Real plant and material variation

    No two plants, stems or crates are identical: the variation a model needs to generalize.

How it works

From real-world task
to structured data.

  1. 01

    Define

    We agree the tasks, environments, modalities and scale with your team.

  2. 02

    Collect

    Trained participants record real work in real places, to a written protocol.

  3. 03

    Synchronize

    Visual and motion signals are aligned to one timeline for every session.

  4. 04

    Review

    Sessions are checked against the brief before they move any further.

  5. 05

    Deliver

    Structured, documented data lands in your storage in the format you train on.

Get in touch

Tell us what your
model needs to learn.

Tell us the task, environment, modalities and scale. We'll design the collection around your requirements.

Start a paid pilot
Talk to us