Parallel Domain
Parallel Domain is a USA AI & Machine Learning Platform company that generates synthetic sensor data to train autonomous vehicle and robotics perception AI.
Parallel Domain was founded in 2017 by Kevin McNamara and is headquartered in San Francisco, California. The company operates a synthetic data platform designed to accelerate the development and validation of AI-driven perception systems for autonomous vehicles, robotics, drones, and other autonomous systems. By generating high-fidelity synthetic datasets—including camera, LiDAR, and radar sensor feeds—Parallel Domain enables machine learning teams to train and evaluate perception models without relying exclusively on expensive, time-consuming real-world data collection.
The company's core technology is built on a procedural generation pipeline that constructs photorealistic 3D environments populated with realistic objects, weather conditions, lighting scenarios, and sensor noise models. A key product is Data Lab, a self-service API that allows engineering teams to programmatically generate on-demand synthetic datasets with deterministic sensor simulation, ensuring that perception systems experience in simulation exactly what they encounter in the real world. This approach supports both training and closed-loop validation workflows.
Parallel Domain's platform serves perception, machine learning, data operations, and simulation teams across the automotive, defense, logistics, and robotics sectors. Notable customers and partners include Google, Continental, Woven Planet (Toyota Group), and Toyota Research Institute. The company also partnered with Foretellix to integrate hyper-realistic digital twins into AV simulation workflows, and with Zenseact to support simulation-to-reality transfer for autonomous driving.
Parallel Domain has raised approximately $60 million in venture funding. The Series A was followed by a $30 million Series B led by March Capital, with participation from Costanoa Ventures, Foundry Group, Calibrate Ventures, and Ubiquity Ventures. The company argues that autonomous systems cannot scale safely without synthetic data, as real-world edge cases are rare and cannot be systematically captured at scale through fleet-based data collection alone.
Primary type & automation activities this supplier delivers:
Data Lab API
A self-serve API for on-demand generation of photorealistic synthetic sensor datasets (camera, LiDAR, radar) for AI perception model training.
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Contact Parallel Domain
WEBSITE
https://paralleldomain.comHEADQUARTERS
United States
Company Facts
Founded
2017
Primary Role
Software/Algorithm
Company Size
-
Primary Region
North America
Annual Sales
-
Funding Stage
-
Funding Total
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