This paper presents UniDex, a robot foundation suite addressing the challenges of dexterous manipulation by combining a large-scale robot-centric dataset with a unified vision-language-action (VLA) policy. The system transforms egocentric human videos into robot-executable trajectories across eight dexterous hand embodiments through a human-in-the-loop retargeting procedure. By operating on explicit 3D pointclouds with human hands masked, the approach narrows kinematic and visual gaps between human and robot domains. The introduced Function-Actuator-Aligned Space (FAAS) provides a unified action space for universal dexterous hand control.