As embodied AI accelerates, high-quality manipulation data has become a critical bottleneck in robotics. Addressing this, US-based bionic prosthetics company PSYONIC is pioneering a real-to-real transfer approach by harnessing operational data from approximately 300 amputees who use its FDA-approved Ability Hand. Unlike traditional teleoperation or motion-capture methods that suffer from high costs, limited scenarios, and unnatural user states, the Ability Hand records natural, daily-life interactions. The prosthetic captures precise contact points, grip force, finger velocity, and torque distribution, creating a complete sensory-motor loop. PSYONIC founder and CEO Aadeel Akhtar emphasizes that tactile feedback is irreplaceable for dexterous manipulation. By synchronizing proprioceptive data with multimodal vision, the system captures essential handling nuances. This strategy deliberately bypasses the sim-to-real pipeline, directly transferring human manipulation experience from domestic settings to industrial automation. The hardware leverages myoelectric control, compliant mechanical designs, and integrated vibration feedback to deliver real-time tactile cues to wearers. The company has rapidly pivoted from prosthetics toward robotics as physical AI demand surged. In March 2026, PSYONIC announced at the NVIDIA GTC conference that the Ability Hand has been integrated as a native asset into the open-source Isaac Lab framework. The company will collaborate with NVIDIA to train Vision-Language-Action models and world models using the GR00T platform, demonstrating that high-quality multimodal datasets significantly reduce the volume of data required for effective training. Isaac Lab will handle policy simulation, while physical hardware validates deployments, creating a closed loop where real-world human data continuously improves robotic models. Industrial integration is already underway. In June, PSYONIC partnered with ABB Robotics to mount the Ability Hand on its GoFa collaborative robot. The GoFa will serve as a precision validation platform, testing human-derived manipulation policies in automotive manufacturing, warehousing, and laboratory automation. PSYONIC aims to achieve over 99 percent operational reliability within six to twelve months, while concurrently pursuing next-generation neural and musculoskeletal interfaces with academic and military partners to enhance independent finger control and realistic haptic feedback. Despite its innovative methodology, the approach faces practical hurdles. The dataset of 300 users falls short of the hundreds of thousands of trajectories typically required for large-scale robotic learning. Additionally, the domain gap between household chores and factory tasks introduces distribution shift challenges. Achieving the stated reliability target may also prove insufficient for high-stakes industrial environments that demand 99.9 percent consistency. Nevertheless, PSYONIC cross-platform design, compatible with cobots, quadrupeds, and humanoid robots, positions it as a pivotal player in bridging human dexterity with machine automation. The company has expanded from seven to fifty employees and expects rapid scaling as it aligns prosthetic innovation with robotic precision.