Parallel Domain Inc has developed a synthetic data generation platform for computer vision and autonomy designed to improve accuracy while reducing time and cost to train, test, and deploy the User's vision and perception systems. With facilities in the San Francisco Bay Area and Vancouver, British Columbia, the firm's platform is powered by a robust procedural generation pipeline with the firm's API having three modes which give Users the flexibility in how their data is captured whether for training ML models, interactive simulation and testing, or real-time sensor feeds. From self-driving cars to delivery drones, autonomous systems offer the potential of drastically improving the quality of life. Parallel Domain enables their clients to develop their technology in safe virtual environments, offering fast deployment atreasonable cost. The firm's platform is a data generation engine providing clients ready access to rich, labeled sensor data.
