Problem Statement

The Challenge

Why Training Physical AI Is So Hard

Humanoid robots don't just navigate — they manipulate objects, coordinate limbs, understand context, and learn from watching others. Current data falls short.

The Perspective Problem

Humanoids need egocentric views (what they see) and exocentric views (how they appear to others). Traditional capture misses half the picture. DreamVu's synchronized dual-stream capture — Alia 360° exocentric + GoPro egocentric — gives you both simultaneously.

The Multimodal Gap

Physical AI models need vision + language + action data together. Most datasets provide vision only — leaving teams to stitch together incomplete signals. DreamVu delivers all three, synchronized.

The Sim-to-Real Gap

Humanoids trained in simulation fail when deployed in real environments. DreamVu captures the real world in formats that translate directly into Isaac Sim and back — closing the sim-to-real loop.