The working knowledge of the skilled trades, captured for the machines that will need it.

WHAT WE CAPTURE

Consider a single, ordinary moment of skilled work: an electrician torquing the neutral lug in a residential panel. It takes perhaps eight seconds. In those eight seconds there is more useful information than in an hour of the staged household video that today's robot models are fed — if you know how to capture it.

We record that moment four ways at once, on one clock. A head-mounted camera sees exactly what the electrician sees. A microphone hears him explain, in his own words, what he is doing and why — “setting the driver to forty-five inch-pounds, per the panel schedule.” The instrumented screwdriver reports the actual torque curve as the lug seats, peaking at 45.2 inch-pounds, squarely inside the specification band. And every one of those signals lands, timestamped, in a single training-ready record.

The result is what we call behavior-grade data: not sparse clips of finished work, but a continuous, synchronized account of how skilled hands actually do the job.

WHY FORCE MATTERS

Most of the video data available to robotics developers today has no force in it. A camera can show a hand turning a screwdriver; it cannot show how hard. Yet published research is unambiguous on this point: on contact-rich manipulation tasks, adding a genuine force and tactile signal has lifted success rates from roughly thirty percent to over seventy.

Compare that to the gig-sourced video collections on the market today, which capture household chores by the hundred thousand hours — with no force signal, no expert narration, and no trade skill in the hands being filmed. That data is abundant precisely because it is easy. Ours is valuable precisely because it is not.

A CLEAN CHAIN OF TITLE

Just as important as the data is where it comes from. Every hour we capture is collected under a signed consent and royalty agreement with the individual electrician, so the professionals whose skill trains these models are compensated participants, not unwitting subjects. Their licenses are verified; their identities are protected; their royalties continue as the data earns.

For the laboratories that license our datasets, this is not a courtesy — it is the chain of title their counsel will insist upon. We built it in from the first hour of capture, because provenance cannot be added to data after the fact.

FOR CONTRACTORS

The same capture that produces training data produces something an electrical contractor can use the very same day: photographic and video job documentation, a task log, and torque-compliance records that satisfy NEC 110.14(D) — the panel-lug torque documentation inspectors actually ask to see. Our contractor partners receive these records for every captured job. Nobody calls a foreman a traitor for keeping good records; we simply make the records worth more.

ABOUT THE FOUNDER

TradeMotion Labs was founded by Anthony C. Materna, who has spent three decades building companies around instrumentation hardware and data — from handheld network test instruments deployed across the banking industry, to robotic vending systems, to molecular diagnostics. He has assembled the technical teams, negotiated the exclusive rights, and raised the capital for nine ventures. This one exists because he believes the coming generation of robots will need teachers, and that the best teachers in the world currently carry licenses, not PhDs.

— Tony Materna, Founder and CEO

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