Preload builds the data layer for physical AI. Robots learn mostly from video, but human interaction is much richer: touch, force, and muscle activity. We build a wearable multimodal stack (egocentric video, tactile gloves, EMG) to capture how people actually interact with the physical world, and turn it into datasets robotics teams can train on. We're a YC (F26) team of PhD founders from Johns Hopkins and Caltech with backgrounds at Neuralink, Paradromics, and other neurotech companies.
You'll design and iterate the wearable sensors at the heart of our stack, making them reliable, comfortable, and cheap enough to deploy at scale across very different workflows, from surgery to industrial tasks.
Early, in-person team in San Francisco. You'll own the hardware that everything else is built on.