Building the Robotic Foundation Model for Defense

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Multi-Domain Embodied AI

Our product is an onboard foundation model that turns every robotic asset into an autonomous agent

Robot to robot communication via natural language for swarm coordination

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What is embodied AI?

A vision-language-action (VLA) model is a multi-modal large language model that takes real-time camera data and a text prompt as inputs and outputs robot actions.

Introducing

FURY

A first-of-its-kind foundation model for multi-domain defense.

G01
A01

Unmanned Ground Vehicle with Physical AI

Unmanned Ground Vehicle with Physical AI

Our Technology

Camera Stream and Text Prompt to Direct Robot Control

Warfighter

G01, fix enemy forces along route Tango

Fury G01

Roger. Moving out. 12 minutes to Tango

Intelligent Autonomy at the Edge

  • Operates in real time in comms & GPS-denied environments without reliance on external connectivity or cloud infrastructure.
  • Pre-trained, generalized decision-making across diverse platforms and missions.
  • Reinforced safety and alignment to support complex, dynamic operations.

Platform-Agnostic AI for Any Robotic System

  • Deployable across all robotic form factors in all domains.
  • Foundation model family supports varying compute and power needs.
  • Controls learned from real-world imitation data or in simulated environments.

Lightweight & Scalable Hardware Integration

  • Built entirely from commercial off-the-shelf (COTS) hardware components.
  • Enables high-rate, low-cost manufacturing pipelines.
  • Optimized for low-power inference and lightweight sensor configurations.

Vision-Based Passive Sensing

  • Requires as little as one camera stream to operate—RGB or thermal camera for day or night missions.
  • Eliminates dependence on active sensors like LIDAR or radar.
  • Designed for stealth, simplicity, and reduced power usage.

Intuitive Human-Machine Integration Commanded by Natural Language Interface

  • Issue commands via voice, text, or map-based inputs—no special training required.
  • Robot can respond to commands in natural language and understands commander intent.
  • Ability for robot to robot communication via natural language.

Self-Improving at the Tactical Edge

  • Adaptive learning allows for retraining on the edge.
  • Secure over-the-air (OTA) model deployments.