PHYSICAL AI // RECURSIVE CO-IMPROVEMENT

VIRTUAL FIRST PHYSICAL NEXT

Powered by efficiency-native AI models and infrastructure, we drive the collaborative improvement of environments and embodied agents, bringing intelligence from virtual worlds into the physical world.

RCI CORE ONLINE
WORLD MODEL | EMBODIED AGENT
PH-RCI v1.0

0%

TRAINING COST

MODEL-INFRA CO-DESIGN

0%

INFERENCE COST

STREAMING EFFICIENCY

0X

DATA COLLECTION COST

DECREASE

TECHNOLOGY ARCHITECTURE

RCI: RECURSIVE CO-IMPROVEMENT

RCI Core

Connects world models and embodied agents through active exploration and verifiable feedback. Agents expose weaknesses; environments generate harder, more realistic curricula.

RCI Infra

Unified infrastructure spanning data, training, evaluation and deployment. Supports cross-world parallel rollouts, streaming inference, and heterogeneous hardware.

RCI Platform

End-to-end physical intelligence platform: multi-embodiment access, co-training, evaluation, verification, and cross-world deployment for enterprise customers.

RCI ARCHITECTURE

WORLD MODEL × EMBODIED AGENT

World models generate experience and curricula for embodied agents; agents discover the limits and flaws of world models through active interaction. Both evolve recursively through verifiable feedback.

WORLD MODEL EMBODIED AGENT RCI CORE
WM
AGENT
CO-IMPROVEMENT ACTIVE