Duality AI

Founded 2019

Build digital twin environments to test autonomous systems and generate synthetic data

You can use Duality AI to build high-fidelity digital twins and simulate physical environments for testing autonomous systems. It lets you create virtual spaces using an Unreal Engine editor, generate synthetic datasets for machine learning models, and validate robotics algorithms before real-world deployment. You can run open-loop and closed-loop simulations directly in the cloud, connect through Python APIs, and integrate with standard robotics frameworks like ROS and ROS2. This setup lets engineers evaluate aerial, off-road, and manufacturing automation systems safely without hardware constraints.

What Duality AI does

Build photorealistic 3D simulation environments using digital twin assetsGenerate synthetic imagery and sensor data to train machine learning modelsConnect autonomy algorithms via Python APIs and ROS messaging protocolsSimulate complex lighting and weather conditions for sensor validationRun multi-agent robotics simulations distributed across cloud infrastructureCalibrate virtual camera and lidar sensors to mirror physical hardwareUnreal Engine based editor for creating photorealistic digital twin scenesFalcon middleware connecting simulation workflows to ROS and ROS2 messagingSynthetic data generation pipelines for training computer vision modelsClosed-loop testing environments for validating autonomous vehicle algorithmsPrompt-driven agentic co-pilot for on-demand synthetic data creationCloud-based simulation execution with distributed computing support