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solutions · embodied AI & robotics

the data that teaches robots how the real world works.

The data embodied AI and humanoid robots need most isn't on the internet. It's the first-person viewpoint, the contact-rich hands, and the messy real environments of people doing ordinary tasks — captured by real people, framed and audited, and traceable end to end.

what a robot has to learn

from everyday human activity to a trained policy.

egocentric & movement First-person POV and full-body motion — the viewpoint and movement a robot learns from. dexterous manipulation Contact-rich hands — picking, placing, tool use — the fine-motor data sim can't fake. multimodal perception Synced video, audio, and image — grounded perception, not single-sensor guesses. aerial & navigation FAA-certified aerial passes for autonomous navigation and perspectives ground can't reach. expert judgment Credential-checked specialists for the evals, RLHF, and red-teaming your models run on. provenance & consent Every asset framed, consent-clean, and traceable — data you can defend.
why physical-AI teams choose matchpoint

real, traced, and fairly made — so you can train on it and defend it.

data that doesn't exist online

Real people doing real tasks in real homes, workplaces, and outdoor settings — the long-tail, contact-rich distribution your robot actually operates in, captured to your spec.

neutral by design

We're independent — never owned by an AI lab — so your data isn't quietly training a competitor.

provenance you can defend

Framed, timestamped, consent-clean, and traceable end to end — auditable for your board and for regulators.

fairly made means consistent

A published rate, paid on time, and contributors who stay — low attrition is what makes the data consistent instead of a churn-and-burn lottery.

get started

tell us what your robots are missing.

We'll scope a capture program for your embodied-AI roadmap and show you sample data — usually within a week.