Preload
Preload pairs everyday video with synchronized multimodal sensing—tactile pressure from a sensor glove and forearm EMG signals—to capture how human hands hold, press, and let go. The platform turns these synchronized human demonstrations into training data for robots, enabling frontier AI labs and manufacturing teams to develop physically capable robotic applications.
- Robotics
- Artificial Intelligence
- Manufacturing / Industry 4.0
- Industrial Automation
- Hardware
Funding
Founders
Founder details are not available yet.
Product
Problem
Video captures only a flat projection of the physical world, missing the dense cloud of force, contact, and motion that defines real-world interaction. Better model architectures cannot recover what was never measured, limiting the physical capability of robots trained on visual data alone.
Solution
Preload provides an end-to-end platform that captures synchronized video, tactile pressure from a sensor glove, and forearm EMG signals to record how humans grip, press, and release objects. By turning these multimodal measurements into training data, the system teaches robots to replicate human dexterity. The workflow spans sensing, collection, training, evaluation, and deployment, enabling teams to move from human demonstrations to automated robotic action. The full stack is built in-house, from sensor hardware to policy training and real-hardware testing.
Target Audience
Primary customers are frontier AI labs and manufacturing teams working with physical-world robotic applications that require human-like dexterity and force sensitivity.
Features
- Sensor glove measuring pressure across fingers and palm for tactile force capture
- EMG band on the forearm reading muscle activation behind every grip
- Synchronized recording of video, touch, and force signals for multimodal human demonstrations
- End-to-end pipeline covering data collection, model training, evaluation, and deployment
- In-house full-stack capability from sensor design to policy training and real-hardware testing