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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

Cyngn and Global Mining Vehicle OEM Continue to Make Progress in Ongoing AV Commercialization Project

Cyngn, Inc. (the “Company” or “Cyngn”) (Nasdaq: CYN), a developer of AI-powered autonomous driving solutions for industrial applications, today announced that it has successfully completed Phase 2 of its multi-phase project with a global, large-cap company in the heavy machinery industry. The project focuses on implementing autonomous vehicle (AV) technology in the mining domain. Cyngn has achieved state-of-the-art results with elements of its AV technology that are not currently used by the mining industry but can introduce paradigm-shifting automation capabilities, primarily by increasing the uptime of automated mining vehicles. These novel results were achieved in the field, and the technology is expected to evolve into a commercial product after the project-based work is done.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230426005385/en/

Cyngn Autonomous Industrial Vehicle Mining Application (Photo: Business Wire)

Cyngn Autonomous Industrial Vehicle Mining Application (Photo: Business Wire)

Cyngn’s collaboration with this global company, whose name is being withheld for competitive reasons, spearheads the introduction of leading-edge AV and artificial intelligence solutions into the client's industrial vehicles, including the opportunity to address vehicles already in commercial use.

The mining industry is one of the most hazardous industries, with workers facing harsh, often remote work conditions with a higher risk of serious injury than workers in other industries. By leveraging the latest in autonomous industrial vehicle technology, mining companies can ensure the safety of their workers while increasing productivity and efficiency. With the successful completion of the previous two phases of this multi-phase project, Cyngn's DriveMod technology has already proven its ability to address multiple vehicles and applications in the mining sector and demonstrated the effectiveness of the technology.

The continued development of Cyngn's technology through this multi-phase project is expected to yield advancements to the fundamental capabilities of Cyngn's Enterprise Autonomy Suite (EAS) that will benefit the Company's already commercially available autonomous stockchasers, autonomous forklifts (in development, under a separate customer contract), and all future autonomous vehicles powered by DriveMod.

Cyngn expects to complete Phase 3 of the project by the end of summer 2023, and further announcements may be made at that time.

About Cyngn

Cyngn develops and deploys scalable, differentiated autonomous vehicle technology for industrial organizations. Cyngn’s self-driving solutions allow existing workforces to increase productivity and efficiency. The Company addresses significant challenges facing industrial organizations today, such as labor shortages, costly safety incidents, and increased consumer demand for eCommerce.

Cyngn’s DriveMod Kit can be installed on new industrial vehicles at end of line or via retrofit, empowering customers to seamlessly adopt self-driving technology into their operations without high upfront costs or the need to completely replace existing vehicle investments.

Cyngn’s flagship product, its Enterprise Autonomy Suite, includes DriveMod (autonomous vehicle system), Cyngn Insight (customer-facing suite of AV fleet management, teleoperation, and analytics tools), and Cyngn Evolve (internal toolkit that enables Cyngn to leverage data from the field for artificial intelligence, simulation, and modeling).

Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Any statement that is not historical in nature is a forward-looking statement and may be identified by the use of words and phrases such as “expects,” “anticipates,” “believes,” “will,” “will likely result,” “will continue,” “plans to,” “potential,” “promising,” and similar expressions. This press release also includes forward-looking statements with respect to Cyngn’s expectations of the efficiency of its solutions, the challenges it believes its solutions can address and the cost effectiveness of its solutions. These statements are based on management's current expectations and beliefs and are subject to a number of risks, uncertainties and assumptions that could cause actual results to differ materially from those described in the forward-looking statements, including the risk factors described from time to time in the Company’s reports to the SEC. No forward-looking statement can be guaranteed, and actual results may differ materially from those projected. Cyngn undertakes no obligation to publicly update any forward-looking statement, whether as a result of new information, future events, or otherwise. Readers are cautioned that it is not possible to predict or identify all the risks, uncertainties and other factors that may affect future results.

Find Cyngn on:

Website: https://cyngn.com

Twitter: http://twitter.com/cyngn

LinkedIn: https://www.linkedin.com/company/cyngn

YouTube: https://www.youtube.com/@cyngnhq

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