Closing the alignment gap.

Our research is built to close the alignment gap between human intent and machine understanding. Three directions:

• The Large MUAP Model (LMM) — a shared "alphabet" of neuromuscular patterns enabling token-style prediction of intent; developed on our highest-fidelity research hardware.
• Cardiac–locomotor coupling — fusing EMG, IMU, and PPG to read engagement and state.
• AR as the feedback channel — making the machine's understanding visible and correctable in real time.

Status: Active research and roadmap, not current product claims.

Whitepapers: Designing a Neural Input Wristband for XR (2023) · Interaction Beyond Boundaries (2024) · From Intention to Action (2026).