New Study: Cyngn Autonomous Industrial Vehicles Increased Productivity by 33%

MENLO PARK, Calif.–(COMMERCIAL WIRE)–Syngn (or the “Company”) (NASDAQ: CYN), a developer of innovative autonomous driving software solutions for industrial and commercial applications, today released a new case study quantifying the value that Cyngn’s autonomous vehicle (“AV”) technology brings to Global Logistics and Fulfillment (“GLF”). “), a leading company on the West Coast. third-party distribution, fulfillment and logistics services company (“3PL”). This is the first Cyngn study to quantify the return on investment an organization could expect from investing in AV technology.

According to Cyngn’s research, the deployment of an autonomous vehicle at GLF’s Las Vegas warehouse led to a dramatic increase in efficiency, almost immediately. The report found:

  1. a 64% reduction in human labor costs, compared to using forklifts.

  2. a 33% increase in productivity compared to using electric pallet trucks.

“The data speaks for itself,” says Cyngn CEO Lior Tal. “There are almost no other interventions that an organization can implement to increase productivity at these levels. Based on the organization’s performance, we estimate that this technology could easily save a third-party logistics organization more than $100,000 per vehicle per year.”

In addition to the increased productivity, Cyngn’s Autonomous Stockchaser provided additional benefits. The vehicle provided GLF management with real-time data and reports on operational analytics, created a safer work environment for GLF employees, and enabled further growth of GLF’s customer base. Ultimately, Stockchaser served as tangible proof of GLF’s commitment to innovation, allowing them to continue to exceed their customers’ expectations.

“Working with Cyngn on implementing an autonomous vehicle really opened our eyes to endless possibilities and is part of what we are trying to plan for the future,” added Kenn Morris, vice president of global logistics and fulfillment. “I didn’t realize how quickly my team would get used to the autonomous vehicle.”

As a result of the global e-commerce boom, the storage industry is experiencing rapid growth and even industry stalwarts are struggling to scale their operations to meet the growing demand. Consequently, traditional labor resources are becoming depleted and more expensive.

Global Logistics & Fulfillment (“GLF”) is no stranger to these trends. For more than 25 years, the company has been a leading provider of third-party logistics, fulfillment and distribution services. With warehouses in San Diego and Las Vegas, it maintains more than 300,000 square feet of accumulated space for storage, packaging and assembly. Like many others in the industry, GLF has a customer base that is constantly increasing its warehouse footprint. Today, your facility has never been busier, yet the pressure on your workforce and the risk of losing business to competitors has never been greater.

Facing rising labor costs, increasingly demanding customers, and an urgent need to scale its business, GLF sought an innovative solution to streamline its operations. Enter the new DriveMod-enabled Autonomous Stockchaser from Cyngn and Columbia Vehicle Group. After a brief integration period, Autonomous Stockchaser supplemented GLF’s workforce to transport pallets around its Las Vegas facility. In just a four-week pilot implementation period, the new Stockchaser was able to significantly increase labor productivity and deliver material cost savings.

The implementation of Cyngn’s DriveMod autonomous vehicle technology in GLF involved a set of simple but robust steps:

  1. Conduct a site assessment. First, Cyngn interviewed GLF operations managers to gain a complete understanding of GLF’s process flows. Cyngn field engineers then surveyed the GLF facility to document the operational design domain (“ODD”), including lighting, lane widths and the types of obstacles the vehicle might encounter. From this, Cyngn was able to identify transporting pallets from an order fulfillment station to outbound shipping as the optimal use case for implementation.
  2. Map the facility. For an AV to work, it must know where it is within its environment. To accomplish this, Cyngn scanned the entire GLF facility to create a detailed virtual map.
  3. Get the vehicle up. Once the map was created, Cyngn worked with GLF management to define the vehicle’s missions, which included the routes the vehicle would take and the stops where pallets could be loaded and unloaded on the vehicle.
  4. Train key personnel. Finally, before the vehicle went into fully autonomous operation, Cyngn trained GLF employees on the safe use of the vehicle. Then he was seamlessly integrated into his daily workflow.

To read the full report, click here.

About Cyngn

Cyngn is an autonomous vehicle technology company focused on addressing the industrial uses of autonomous vehicles. Cyngn believes that technological innovation is needed to enable the adoption of autonomous industrial vehicles that address the substantial industry challenges that exist today. These challenges include labor shortages, technological advances lagging behind incumbents, and high initial investment requirements. Cyngn addresses these challenges with its Business Autonomy Packagewhat includes DriveMod (modular software for autonomous driving of industrial vehicles), Cyngn perspective (customer-facing software suite for monitoring/managing AV fleets and aggregating/analyzing data), and Evolve (Internal toolkit that allows Cyngn to harness data from the field for AI, simulation, and modeling.)

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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. , amended. Any statement that is not historical in nature is a forward-looking statement and can be identified by the use of words and phrases such as “expects”, “anticipates”, “believes”, “will”, “is likely to result”, “will continue”, “plans”, “potential”, “promising” and similar expressions. These statements are based on the current expectations and beliefs of management 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 risks, uncertainties and other factors that may affect future results.

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