Parallel Domain logo — Programmatically test and validate autonomous systems at sca...

Parallel Domain

Programmatically test and validate autonomous systems at scale. High-fidelity sensor simulation in digital twins.

Founded 2017 United States San Francisco, United States 52 employees Series B Total: $43.94M Big Data, VR/AR +2

General Information

Company Name Parallel Domain
Founded Year 2017
Location United States San Francisco, United States
Employees 52
Industries Big Data, VR/AR, Autonomous and Sensor Tech +1
Funding Stage Series B
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About Parallel Domain

Parallel Domain is a company that provides programmatically testing and validating autonomous systems at scale through high-fidelity sensor simulation in digital twins. Founded in 2017 and headquartered in the United States, the company aims to bridge the gap between simulation and the real world, ensuring flawless performance of autonomous systems when it matters most. Their mission is to empower industry leaders in autonomous driving, drone delivery, eVTOL, robotics, and beyond by offering a high-fidelity, fully controllable, software-in-the-loop sensor simulation API that provides unparalleled realism, accuracy, and confidence. Their most recent milestone includes a $30.00M Series B investment received on 16 November 2022 from prominent investors including March Capital, Costanoa Ventures, Foundry Group, Calibrate Ventures, and Ubiquity Ventures. With a focus on industries such as Big Data, VR/AR, Autonomous and Sensor Tech, and Machine Learning, Parallel Domain continues to be a trusted first line of defense for innovators in the field of autonomy, leaving no margin for error in their pursuit of excellence.

Business keywords: autonomous systems, sensor simulation, digital twins, synthetic data generation, computer vision, autonomous vehicles, delivery drones, software-in-the-loop simulation, eVTOL, machine perception, regression testing

Services & Products

Simulation API for autonomous systems testing
High-fidelity sensor simulation
PD Replica for generating digital twins
Synthetic dataset generation platform
Realism-focused simulation environment

Target Customers

Machine learning computer vision and perception teams in industries such as automotive aerial robotics agriculture warehouse management and security

Funding Rounds & Investors (3)

View All
Funding Stage Amount Investors Lead Investors Date
Series B $30.00M 5
March Capital, Costanoa Ventures +3
16 Nov 2022
Series A $11.00M 5
Costanoa Ventures, Foundry Group +3
09 Dec 2020
Seed Round $2.94M 4
RRE Ventures, Costanoa Ventures +2
01 May 2018

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FAQ About Parallel Domain

Programmatically test and validate autonomous systems at scale. High-fidelity sensor simulation in digital twins.
Parallel Domain was founded in 2017.
Parallel Domain is headquartered in San Francisco, United States.
Parallel Domain operates in Big Data, VR/AR, Autonomous and Sensor Tech and Machine Learning. Its work centres on autonomous systems, sensor simulation, digital twins and synthetic data generation. Its customers include Machine learning, computer vision and and perception teams in industries such as automotive.
Parallel Domain has approximately 52 employees.
Parallel Domain has completed 3 funding rounds, raising a total of $43.94M. The latest funding stage is Series B.
Parallel Domain offers: Simulation API for autonomous systems testing, High-fidelity sensor simulation, PD Replica for generating digital twins, Synthetic dataset generation platform, Realism-focused simulation environment.
Top alternatives and competitors to Parallel Domain include Algolux, NODAR, Playment, Anyverse, blackshark.ai. These companies operate in related industries and serve comparable markets. You can compare them side by side on Bounce Watch.
Parallel Domain and Algolux are both companies in similar industries. Compare their funding, team size, growth signals, and market position on Bounce Watch to see which one fits your needs.

Source: BounceWatch company record for Parallel Domain, https://bouncewatch.com/company/parallel-domain, updated 13 June 2025. When citing, please name BounceWatch and link this page.

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