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Testing AI in the real-world is hard, risky, and expensive
Parallel Domain offers an API, SDK, and Web Tools for machine learning, computer vision, and perception teams to programatically test and analyze perception system performance at scale.
Supporting open or closed-loop simulation to stream high-fidelity camera, lidar, and radar data with full annotations.
PD Replica Sim - Closing the sim-to-real gap with real environments
Generate digital twins at scale from your capture data. Simulate lidar, radar, and camera sensors with unprecedented realism and control. Ensuring simulation performance matches real-world performance.
Collecting emergency vehicle data is a huge challenge. We were able to achieve significant performance improvements in our emergency vehicle detection algorithms by using the Parallel Domain platform to generate synthetic datasets that matched our operational domain here in Japan.
ML Tech Lead, Woven Planet
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
Parallel Domain data boosted the machine learning model performance of our traffic light classification system. Their platform provided us with a diverse dataset with edge cases and accurate annotations that would not have been possible with our real world data operations.
Industry Leading Level-4 Autonomy Team
Collecting emergency vehicle data is a huge challenge. We were able to achieve significant performance improvements in our emergency vehicle detection algorithms by using the Parallel Domain platform to generate synthetic datasets that matched our operational domain here in Japan.
ML Tech Lead, Woven Planet
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
Parallel Domain data boosted the machine learning model performance of our traffic light classification system. Their platform provided us with a diverse dataset with edge cases and accurate annotations that would not have been possible with our real world data operations.
Industry Leading Level-4 Autonomy Team
Collecting emergency vehicle data is a huge challenge. We were able to achieve significant performance improvements in our emergency vehicle detection algorithms by using the Parallel Domain platform to generate synthetic datasets that matched our operational domain here in Japan.
ML Tech Lead, Woven Planet
We support perception use cases across industries
Automotive
Aerial
Robotics
Agriculture
Warehouse
Security
