The Neural
World Model
for Physical AI.

Grounded in real 4D human interaction data.

AXON closes the sim-to-real gap — from human experience to any robot morphology.

We built the data toolkit. We trained the model.

21 DoF
Hand Pose Resolution
162 /hand
Tactile Data Points
<10ms
Data Capture Latency
4D Native
Multimodal Streams

Neural World Model Grounded in Real 4D Human Interaction Data

Arcomni builds AXON — a high-consistency neural simulation engine trained on real human interaction. To capture that data at the fidelity we needed, we built AWEAR ourselves. Together they form ASCENT: our full-stack architecture for physical AI.

ASCENT Architecture AWEAR Data Capture AXON World Model Fix Sim-to-Real Gap
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AWEAR Kit — gloves and glasses
Full-Stack Architecture

The integrated platform connecting data capture, world modelling, and cross-embodiment deployment into one coherent system.

Native 4D Data Acquisition

Hardware we built because it didn't exist. Tactile gloves + smart glasses capturing the richest real-world human interaction data available.

High-Consistency Neural Simulation

Our neural world model trained on AWEAR data. Closes the sim-to-real gap and transfers human-grounded policies to any robot morphology.

AWEAR — Built Because the Data Didn't Exist

To ground AXON in reality, we needed 4D multimodal human interaction data at a scale and fidelity that no existing hardware could deliver. So we built AWEAR: tactile gloves and smart glasses designed specifically to feed our world model.

Gloves
21 DoF Hand Pose

16 IMU/hand · 9-axis · 100 Hz · <1.5° static accuracy

Dense Tactile Sensing

162 sensors/hand · 100–600 Hz · full-palm pressure map

<10 ms Latency

End-to-end · real-time robot imitation learning

Glasses
Dual RGB Vision · 4D Native

2x 1600×1200 · 30 Hz · first-person 4D streams

WiFi + Bluetooth

2.4/5 GHz · BT · USB-C · >15 m indoor range

Flexible Integration

USB · UART · on-board MCU · touchscreen status display

AWEAR — Data Acquisition System

The data capture layer of ASCENT. Standard gloves · tactile gloves · smart glasses. Use independently or as a full system.

Gloves — Standard
21 DoF hand pose
  • Core: 16 IMU sensors/hand · 9-axis IMU
  • 100 Hz full-channel data
  • Accuracy: <1.5° static · <2.5° dynamic
  • Latency: <10 ms
  • Connectivity: WiFi (2.4/5 GHz) · Bluetooth
  • USB-C (data + charging) · Range: >15 m indoor
  • Hardware: 1000 mAh · >2 hr runtime
  • USB-C charging (5V/1A)
  • Touchscreen (status, battery, ID)
  • Weight: <180 g/hand
Gloves — Tactile
Standard + dense tactile sensing
  • Adds 162 tactile sensors per hand
  • Tactile sampling: 100–600 Hz (wired)
  • Interface: USB or UART
  • Integration: inter-board (prototype)
  • On-board MCU (production)
  • All other specs same as Standard
Glasses
Dual RGB · 4D native · Head-mounted option available
  • Dual RGB cameras (glasses-mounted)
  • Resolution: 1600 × 1200 @ 30 Hz
  • Battery life: ~3 hours
  • Simultaneous charging + data transmission
  • Weight: <50 g

From Human Experience to Any Robot

Capture → model → deploy. The full pipeline.

Step 01
Wear

Human puts on AWEAR gloves and glasses. Auto-connects over WiFi or Bluetooth.

Step 02
Capture

21 DoF · dense tactile · dual RGB 1600×1200. Rich 4D multimodal streams grounded in real interaction.

Step 03
Model

AXON processes human interaction data into a high-consistency neural world model with physics and contact awareness.

Step 04
Deploy

Transfer to any robot morphology. Human-grounded policies. Sim-to-real gap closed.

Where AXON Works

Any domain where a human-grounded world model and physics-consistent simulation create value.

Medical Training

Expert technique → AI simulation

Robotics & AI

Human demos → robot manipulation

Industrial Training

Skilled workflows → reproducible training

Sports Science

Grip · reaction · visual attention analysis

Rehabilitation

Fine motor recovery tracking

XR & Metaverse

Avatars · haptic XR · authentic motion

Research

Ground-truth perceptual datasets

Education

Expert perspective · immersive skill transfer

Get in Touch

Demo · integration · partnership