AI models and autonomous systems often struggle to generalize and perform safely in complex, unpredictable real-world environments. Validating these systems requires extensive testing, which can be time-consuming, expensive, and potentially dangerous when conducted in the physical world.

Duality provides a digital twin simulation platform that enables users to create high-fidelity virtual environments for testing and validating AI models and autonomous systems. The platform leverages the Unreal Engine to generate realistic simulations, allowing for the creation of diverse scenarios and edge cases. By simulating real-world conditions, Duality enables users to fine-tune their models, accelerate development timelines, and reduce the risks associated with physical testing. The platform supports both open-loop simulation for synthetic data generation and closed-loop simulation for autonomous systems validation.

Unreal Engine-based editor for creating custom simulation environments

Catalog of simulation-ready system, item, and space twins

Open-loop simulation for synthetic data generation

Closed-loop simulation for autonomous systems validation

Python API and Falcon middleware for integration with ROS/ROS2 and AI models

Secure, cloud-based workflow

Tunable system twins and virtual sensors

The primary target audience includes AI/ML engineers, robotics developers, and researchers working on autonomous systems, particularly in industries such as manufacturing, aerospace, and logistics.