Parallel Domain, a San Francisco, CA-based synthetic data platform for computer vision and perception, raised $30 million in Series B funding.
The round was led by March Capital, with participation from return investors Costanoa Ventures, Foundry Group, Calibrate Ventures, and Ubiquity Ventures.
This new funding will enable Parallel Domain to continue driving revenue growth, expand its team and products to service a broader customer base, and capitalize on the latest advancements in generative AI. It is doubling down on our mission: to accelerate machine learning development with synthetic data.
Parallel Domain works with perception, machine learning, data operations, and simulation teams at autonomous systems companies, from autonomous vehicles to delivery drones. It counts Google, Continental, Woven Planet, Toyota Research Institute, and many more as its customers.
Parallel Domain allows AI developers to generate synthetic data for training and testing perception models at a scale, speed, and level of control not possible with real-world data.
March Partner Julia Klein join Parallel Domain’s board of directors.
Company: Parallel Domain Inc.
Round: Series B
Funding Month: November 2022
Lead Investors: March Capital
Additional Investors: Costanoa Ventures, Foundry Group, Calibrate Ventures, and Ubiquity Ventures
Company Website: https://paralleldomain.com/
Software Category: Synthetic Data Platform
About the Company: Founded in 2017 by Kevin McNamara, Parallel Domain is a synthetic data platform powered by a robust procedural generation pipeline. Parallel Domain offers an API that allows the customer to control the placement of dynamic things in the world, which can then be hooked up to their simulator to test specific scenarios. The Parallel Domain platform, composed of a suite of APIs and developer tools, enables customers to generate synthetic sensor data on-demand, providing essential performance improvements while reducing developer iteration time. Parallel Domain's platform generates synthetic labeled data sets, simulation worlds, and controllable sensor feeds so the company can develop, train, and test its algorithms safely before putting these systems into the real world. It has over 80 employees across multiple countries to support our customers in North America, Europe, and Asia.