"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."
Sr. ML Manager
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
Why Parallel Domain?
Preparing your autonomous system for the real world is a slow, expensive and cumbersome process. Parallel Domain is the fastest way to train and test your machines and human operators.
Your virtual fleet - anytime, anywhere
Train and test your autonomous system to be ready for anywhere in the real world, without the overhead of actually being there.
Data variety, at your fingertips
Day and night, city and rural, LiDAR and camera, fog, rain, traffic lights, vehicles, pedestrians and animals: generate the scenarios you need.
Accuracy and detail like never before
Eliminate annotation mistakes and get richer metadata not available with manual annotation services.
Productivity for your team
Rapidly experiment with algorithms, try new sensor configurations, and make data-driven investment decisions with confidence.
We support major autonomy use cases.
Advanced Driver Assistance
L4 / L5 Autonomy
What will you do with your Parallel Domain?
Access our APIs today and begin generating your own data.