Realset Body

Structured real-world data for physical policy models

Expert human demonstrations captured in real homes, kitchens, warehouses and assembly lines, then structured into training data for VLA and manipulation research.

Our approach

Three ways to get physical-world data, run as one pipeline with QC on every episode.

Capture network

Egocentric demonstrations at work

Skilled workers wear head-mounted rigs while doing their actual job. Synchronized stereo video, IMU and audio, task-labeled at the shift level and segmented after.

Studio

Teleoperation in controlled environments

Bimanual teleop stations in a controlled studio with kitchen, shelf and bench scenes. Action logs, multi-camera video and depth per episode, with retake rules agreed up front.

Structuring

Annotation built for policy learning

Temporal segmentation, hand-object interaction, 2D/3D tracking and step-by-step natural language labels. Delivered in LeRobot, RLDS or your schema.

Use cases

What robotics teams buy from us today.

What you get

Every delivery ships with the same spec sheet, so your training pipeline never changes between batches.

ModalitiesStereo RGB, IMU, audio; teleop adds joint states, gripper commands and depth
Frame rate30 fps video, 50 Hz action logs on teleop episodes
LabelsTask, sub-task segments, language instructions, success flag per episode
FormatsLeRobot v2, RLDS, or a schema you provide
QCTwo-pass review, resample rate published per batch on a live dashboard
PrivacyFaces, plates and text de-identified before the data leaves the capture site
HostingDelivered to a US-region bucket of your choice; nothing stored elsewhere after delivery

How a project runs

From scoping call to first batch in about three weeks.

01

Scope

Task family, embodiment, environments, volume and the success criteria your model is judged on.

02

Pilot batch

A small paid batch in one environment so you can validate format and quality before scaling.

03

Scale

Capture network and studio run in parallel; pipeline dashboard shows velocity, QC pass rate and cost per episode.

04

Iterate

Your eval results steer the next batch toward the failure modes that matter.

Tell us what your model needs

Three questions. We reply within one business day with a sample set and a quote.

Looking for capture or annotation work? Go to the Experts page instead.

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