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Synthetic data just got real
Testing AI in the real-world is hard, risky, and expensive
Parallel Domain offers an API for machine learning, computer vision, and perception teams to generate high-fidelity synthetic camera, lidar, and radar data.
This data is used to train and test perception models by simulating scenarios in procedurally generated worlds or replicas of any location on Earth.
We support perception use cases across industries
Synthetic data, real impact
Parallel Domain Data Lab offers the highest quality synthetic data needed to train and test perception models
Rich scenario diversity
Procedurally generated scenarios to easily “collect” synthetic sensor data at scale
Industry leading content fidelity
Curated and generative high quality content library with supporting a variety of regions, agents and environmental conditions
Highly accurate custom annotations
Pixel perfect annotations that can be customized to meet your workflow needs
Accurate sensor simulation
Select from a wide variety of common camera, LiDAR, and radar sensors, or tune your own configuration
Thanks to its high degree of realism, flexibility and scalability, the Parallel Domain platform enables rapid exploration of cutting-edge machine learning ideas. Its cost effectiveness enables accelerated paths to deployments at scale. This combination makes the platform really unique and a huge advantage for us to develop the future of robot autonomy.
Senior Machine Learning Manager, Toyota Research Institute