UNITED STATES

SECURITIES AND EXCHANGE COMMISSION

Washington, D.C. 20549

FORM 10-K/A

(Amendment No.1)

(Mark One)

☒ ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934

For the fiscal year ended December 31, 2024

☐ TRANSITION REPORT UNDER SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934

For the transition period from [____] to [____]

Commission file number 001-40932

CYNGN INC.

(Exact name of registrant as specified in its charter)

Delaware		46-2007094
State or other jurisdiction of incorporation or organization		(I.R.S. Employer Identification No.)

1015 O’Brien Dr., Menlo Park, CA		94025
(Address of principal executive offices)		(Zip Code)

Registrant’s Telephone number, including area code: (650) 924-5905

Securities registered pursuant to Section 12(b) of the Act:

Title of Class		Trading Symbol(s)		Name of each exchange on which registered
Common Stock, Par Value $0.00001		CYN		Nasdaq Stock Market LLC

Securities registered pursuant to Section 12(g) of the Act:

Title of Each Class		Name of Each Exchange On Which Registered
N/A		N/A

Indicate by check mark if the registered is a well-known seasoned issuer, as defined in Rule 405 the Securities Act.

Yes ☐ No ☒

Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or Section 15(d) of the Act.

Yes ☐ No ☒

Indicate by check mark whether the registrant: (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports), and (2) has been subject to such filing requirements for the last 90 days.

Yes ☒ No ☐

Indicate by check mark whether the registrant has submitted electronically every Interactive Data File required to be submitted pursuant to Rule 405 of Regulation S-T (§232.405 of this chapter) during the preceding 12 months (or for such shorter period that the registrant was required to submit such files).

Yes ☒ No ☐

Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, a smaller reporting company, or an emerging growth company. See the definitions of “large accelerated filer,” “accelerated filer,” “smaller reporting company,” and “emerging growth company” in Rule 12b-2 of the Exchange Act.

Large accelerated filer	☐	Accelerated filer	☐
Non-accelerated filer	☒	Smaller reporting company	☒
		Emerging growth company	☒

If an emerging growth company, indicate by a check mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting standards provided pursuant to Section 13(a) of the Exchange Act. ☐

Indicate by check mark whether the registrant has filed a report on and attestation to its management’s assessment of the effectiveness of its internal control over financial reporting under Section 404(b) of the Sarbanes-Oxley Act (15 U.S.C. 7262(b)) by the registered public accounting firm that prepared or issued its audit report. ☐

If securities are registered pursuant to Section 12(b) of the Act, indicate by check mark whether the financial statements of the registrant included in the filing reflect the correction of an error to previously issued financial statements. ☒

Indicate by check mark whether any of those error corrections are restatements that required a recovery analysis of incentive-based compensation received by any of the registrant’s executive officers during the relevant recovery period pursuant to §240.10D-1(b). ☒

Indicate by check mark whether the registrant is a shell company (as defined in Rule 12b-2 of the Exchange Act). Yes ☐ No ☒

The aggregate market value of the voting and non-voting common equity held by non-affiliates as of June 30, 2024 (the last business day of the registrant’s most recently completed second fiscal quarter), computed by reference to the closing price for the common stock on such date ($7.32), as reported on the Nasdaq Capital Market, was $12,956,005.

The number of shares of Common Stock, $0.00001 par value, outstanding on March 6, 2025 was 1,751,906 shares.

DOCUMENTS INCORPORATED BY REFERENCE

None

EXPLANATORY NOTE

Introduction

As previously announced in the Current Report on Form 8-K filed with the U.S. Securities and Exchange Commission (the “SEC”) on November 7, 2025, Cyngn, Inc. (“we,” “us,” “our,” the “Company” and “Cyngn”) determined that the Company’s previously issued consolidated financial statements and other financial data for the fiscal years ended December 31, 2024 contained in its Annual Report on Form 10-K (the “Affected Period”), should no longer be relied upon because of misstatements related to accounting for warrant liabilities with respect to the Company’s issuance of warrants pursuant to the terms of that certain Securities Purchaser Agreement dated December 20, 2024with respect to the Company’s issuance of warrants pursuant to the terms of that certain Securities Purchaser Agreement dated December 20, 2024. As a result of this misstatement, the Company is restating certain financial information for the Affected Period. All restated financial information is included in this Annual Report on Form 10-K for the year ended December 31, 2024 (the “Form 10-K”), and we have not filed, and do not intend to file, amendments to any of our filings that we have previously filed with the SEC.

Restatement Background

Management of the Company determined the warrant liabilities should have been recorded utilizing the residual fair value method, as opposed to the relative fair value method. In addition, the Company is adjusting for a correction on the statement of cash flows and for certain related issuance costs associated with the warrants that were not previously recorded as expense in the statement of operations. The Company restated its previously reported financial statements for the periods ended December 31, 2024, March 31, 2025 and June 30, 2025. The restatement resulted in an increase to liability by $12.7 million, a decrease in the equity balance by $12.7 million as of year-end and an adjustment from operating activities to financing activities on the statement of cash flow. As a result of the restatement, the Company recognized a loss on the issuance of warrants of approximately $2.3 million and offering-related issuance costs of approximately $1.7 million in its consolidated statement of operations. Additionally, the Company is adjusting for certain out-of-period errors that were not material, individually or in the aggregate, and are being corrected as part of the restatement.

Items Amended in this Filing

This Form 10-K/A includes the restated audited consolidated financial statements and related disclosures as of and for the years ended December 31, 2024.

Please refer to Note 15 “Restatement of Previously Issued Consolidated Financial Statements” in the notes to the consolidated financial statements in this Form 10-K for additional information, including a summary of the impacts of these adjustments.

This Form 10-K/A amends and restates the following items of the Original Form 10-K:

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Part I – Item 1A. Risk Factors.

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Part II – Item 7. Management’s Discussion and Analysis of Financial Condition and Results of Operations.

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Part II – Item 8. Financial Statements and Supplementary Data

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Part II – Item 9A. Controls and Procedures.

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Part IV – Item 15. Exhibits and Financial Statement Schedules.

In accordance with Rule 12b-15 under the Securities Exchange Act of 1934, as amended (the “Exchange Act”), the certifications specified in Rule 13a-14 under the Exchange Act from the Company’s Chief Executive Officer and its Chief Financial Officer, dated as of the date hereof, are being filed or furnished, as applicable, with this Form 10-K/A as Exhibits 31.1, 31.2, and 32.1, and an updated Consent of Independent Registered Public Accounting Firm is being filed as Exhibit 23.1. This Form 10-K/A also includes an updated Report of Independent Registered Public Accounting Firm and updated signature page.

This Form 10-K/A includes only those items and exhibits to the Original Form 10-K that are being amended and restated in connection with the matters described herein, and unaffected items and exhibits are not included herein. This Form 10-K/A should be read in conjunction with the Original Form 10-K and our filings with the SEC subsequent to the Original Form 10-K, together with any amendments to those filings.

Except as otherwise provided, the disclosures in this Form 10-K/A are made as of the date of the Original Form 10-K and do not reflect any events that occurred after the date of the Original Form 10-K or modify or update any other disclosures in the Original Form 10-K affected by subsequent events. As such, forward-looking statements included in this Form 10-K/A may represent management’s views as of the date of the Original Form 10-K and should not be assumed to be accurate as of any date thereafter.

TABLE OF CONTENTS

		Page
	PART I

Item 1.	Business	1
Item 1A.	Risk Factors	15
Item 1B.	Unresolved Staff Comments	36
Item 1C.	Cybersecurity	36
Item 2.	Properties	36
Item 3.	Legal Proceedings	36
Item 4.	Mine Safety Disclosures	36

	PART II

Item 5.	Market for Registrant’s Common Equity, Related Stockholder Matters and Issuer Purchases of Equity Securities	37
Item 6.	[Reserved]	37
Item 7.	Management’s Discussion and Analysis of Financial Condition and Results of Operations	37
Item 7A.	Quantitative and Qualitative Disclosures About Market Risk	44
Item 8.	Financial Statements and Supplementary Data	44
Item 9.	Changes in and Disagreements With Accountants on Accounting and Financial Disclosure	45
Item 9A.	Controls and Procedures	45
Item 9B.	Other Information	46
Item 9C.	Disclosure Regarding Foreign Jurisdictions that Prevent Inspections	46

	PART III

Item 10.	Directors, Executive Officers and Corporate Governance	47
Item 11.	Executive Compensation	51
Item 12.	Security Ownership of Certain Beneficial Owners and Management and Related Stockholder Matters	56
Item 13.	Certain Relationships and Related Transactions, and Director Independence	58
Item 14.	Principal Accountant Fees and Services	59

	PART IV

Item 15.	Exhibit and Financial Statement Schedules	60
Item 16.	Form 10-K Summary	62

FORWARD-LOOKING STATEMENTS

This Annual Report on Form 10-K (this “Annual Report”) contains forward-looking statements. These statements are based on our management’s beliefs and assumptions and on information currently available to our management. The forward-looking statements are contained principally under the headings “Risk Factors,” “Management’s Discussion and Analysis of Financial Condition and Results of Operations,” and “Business.” Forward-looking statements include statements concerning:

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our possible or assumed future results of operations;

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our business strategies;

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our ability to attract and retain customers;

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our ability to sell additional products and services to customers;

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our cash needs and financing plans;

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our competitive position;

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our industry environment;

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our potential growth opportunities;

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expected technological advances by us or by third parties and our ability to integrate and commercialize them;

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the effects of wars, such as the wars in Ukraine and the Middle East, natural disasters and pandemics, such as the Covid-19 pandemic;

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the effects of future regulation; and

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the effects of competition.

All statements in this Annual Report that are not historical facts are forward-looking statements. We may, in some cases, use terms such as “anticipates,” “believes,” “could,” “estimates,” “expects,” “intends,” “may,” “plans,” “potential,” “predicts,” “projects,” “should,” “will,” “would” or similar expressions that convey uncertainty of future events or outcomes to identify forward-looking statements.

The outcome of the events described in these forward-looking statements are subject to known and unknown risks, uncertainties and other factors that may cause our actual results, performance or achievements to be materially different from any future results, performances or achievements expressed or implied by the forward-looking statements. These important factors include our financial performance and the other important factors we discuss in greater detail in “Risk Factors.” You should read these factors and the other cautionary statements made in this Annual Report as applying to all related forward-looking statements wherever they appear in this Annual Report. Given these factors, you should not place undue reliance on these forward-looking statements. Also, forward-looking statements represent our management’s beliefs and assumptions only as of the date on which the statements are made. We undertake no obligation to publicly update any forward-looking statements, whether as a result of new information, future events or otherwise, except as required by law. Given these risks and uncertainties, readers are cautioned not to place undue reliance on such forward-looking statements.

Unless the context requires otherwise, references in this Annual Report to “we,” “us,” “our,” and Cyngn refer to CYNGN Inc. and its consolidated subsidiaries.

Unless otherwise expressly provided in this Annual Report, all historical per share data, number of shares issued and outstanding, stock awards, and other common stock equivalents set forth herein relating to our common stock have been adjusted to give effect to a reverse stock split of our common stock in a ratio of 1-for-150 effected on February 18, 2025.

PART 1

Item 1. Business

Company Overview

Cyngn Inc. is an autonomous vehicle (“AV”) technology company that is focused on addressing industrial uses for autonomous vehicles. We believe that technological innovation is needed to enable adoption of autonomous industrial vehicles that will address the substantial industry challenges that exist today. These challenges include labor shortages, high labor costs, and work safety.

We integrate our full-stack autonomous driving software, DriveMod, onto vehicles manufactured by Original Equipment Manufacturers (“OEM”) either via retrofit of existing vehicles or by integration directly into vehicle assembly. We design the DriveMod to be compatible with sensors and components from leading hardware technology providers and integrate our proprietary AV software to produce differentiated autonomous vehicles.

Autonomous driving has common technological building blocks that remain similar across vehicles and applications. By tapping into these building blocks, DriveMod is designed to deliver autonomy to new vehicles via streamlined hardware/software integration. This vehicle-agnostic approach enables DriveMod to expand to new vehicles and novel operational design domains (“ODD”). In short, nearly every industrial vehicle, regardless of use case, can move autonomously using our technology.

Our approach accomplishes several primary value propositions:

Provide autonomous capabilities to industrial vehicles built by established manufacturers that are already trusted by customers.

Generate continual customer value by leveraging the synergistic relationship of autonomous vehicles and data.

Develop consistent autonomous vehicle operation and user interfaces for diverse vehicle fleets.

Complement the core competencies of existing industry players by introducing the leading-edge technologies of Artificial Intelligence (“AI”) & Machine Learning (“ML”), cloud/connectivity, sensor fusion, high- definition mapping, and real-time dynamic path planning & decision-making.

We believe our market positioning as a technology partner to vehicle manufacturers creates a synergy with incumbent suppliers that already have established sales, distribution, and service/maintenance channels. By focusing on industrial use cases and partnering with the incumbent OEMs in these markets, we believe we can source and execute revenue-generating opportunities more quickly.

Our long-term vision is for our Enterprise Autonomy Suite (“EAS”)—which includes the DriveMod autonomous driving stack as well as the Cyngn Insight and Cyngn Evolve tools for fleet management, analytics, and data collection—to become a universal autonomous driving solution with minimal marginal cost for companies to adopt new vehicles and expand their autonomous fleets across new deployments. We have already deployed DriveMod software on more than ten different vehicle form factors that range from tow tractors and stand-on floor scrubbers to 14-seat shuttles and electric forklifts in a combination of commercially released products, prototypes, and proof of concept projects, demonstrating the extensibility of our AV building blocks.

Our recent progress contributes to the validation of EAS with OEM partners and end customers. We also continue to build upon our ability to scale our products and generate novel technological developments. The DriveMod Stockchaser with a 6,000-lb towing capacity became commercially available in early 2023 and was first commercially deployed with our partner-customer US Continental (“USC”), a California-based manufacturer of quality leather and fabric care products. We then launched the DriveMod Forklift and the DriveMod Tugger as we continued to expand our vehicle-type portfolio fleet through our OEM partnerships with BYD and Motrec, respectively. The DriveMod MT160 Tugger with a 12,000-lb towing capacity was commercially released in 2024 in partnership with Motrec and is now deployed with multiple customers.

We secured paid projects with leading global customers like Arauco, along with additional projects from big brands in the Global 500 and the Fortune 100. Paid development projects of this nature are selectively pursued to springboard new products or technology advancements, yielding promising outcomes such as the DriveMod Forklift. The primary focus of the company is to achieve and expand production deployments with its commercially released DriveMod vehicles. As of the end of 2024, those commercial deployments include the named accounts of John Deere, Coats Automotive, and USC, as well as other business awards that have not yet been publicly disclosed. Our patent portfolio expanded with 16 new U.S. patent grants in 2023 and 2 granted in 2024, bringing the total grants to 21.

Figure 0: Summary of recent Cyngn technical and commercial milestones

We intend to continue to pursue and win additional license agreements with companies that depend heavily on the use of material handling vehicles and that all recognize the need for automation to i) compete in today’s economy, ii) combat the significant labor shortages and escalating costs, and iii) improve safety. Our approach to securing these opportunities will be a continued direct sales effort coupled with increasing our network of industrial vehicle dealers that already have significant sales of industrial vehicles.

Overview: Automation and Autonomy in Industry 5.0

The fifth industrial revolution is upon us with self-driving industrial vehicles operating alongside with human workers and encompasses the benefits from the fourth industrial revolution of smart factories and automated supply chain logistics, with big data connectivity. According to Research Nester, they forecast the global industry 5.0 market to experience remarkable CAGR growth from 2022 - 2030 led by industrial internet of things, artificial intelligence with the alliance of humans and collaborative robots.

As automation proliferates, these industries will gradually shift to service-based models that will decrease upfront capital expenditures and create new revenue streams while unlocking new value in the supply chain. Our AV technology is uniquely positioned to capitalize upon these changes by offering a universal autonomy solution that can deliver self-driving capabilities and data insights to nearly every industrial vehicle on the market.

Automation has long played a role in industrial sectors. The larger industrial automation market has grown significantly by riding the wave of new technology and innovation experienced during Industry 4.0. This consists of a wide range of technology solutions that provide varying levels of automation for critical software control systems and industrial equipment. These components are essential to the operations and growth of global markets such as manufacturing, distribution, transportation, construction, and mining. However, Industry 4.0 has its limitations in industrial autonomy. With the convergence of AI/ML, robotics, connectivity, mapping and interoperability, autonomous vehicle technology is the next leap-frog advancement in materials handling and supply chain logistics efficiency and safety propelling manufacturing into the Industry 5.0 phase.

Figure 1: Illustration of the progression from Industry 1.0 to Industry 5.0.

Automation Solutions for Industrial Equipment

The Industrial Equipment market covers a broad range of use cases and product categories, with automation solutions targeting Material Transport Equipment (“MTE”) heavily utilized by the majority of industry market sectors. For our purposes, we can think of MTE to include all material handling equipment directly related to material transit (this includes conveying equipment, monorail, hoists, storage & retrieval, and industrial vehicles). According to a Grand View Research report, the material handling equipment market was valued at $213.4 billion in 2021. They expect the CAGR from 2022 to 2030 of 5.7% to be driven by increased worker safety awareness, rising requirements for managing bulk materials and further adoption of Industry 4.0 initiatives with the use of IoT. Further with the rising need for reducing downtime and focus on improving supply chain efficiency, self-driving industrial vehicles play an important role to achieve these objectives as manufacturing transitions to Industry 5.0. Our belief is that these strong growth indicators will drive increased need for more advanced technology that will address gaps in the current capabilities of automated MTE solutions.

Historically, MTE automation has been heavily weighted in solutions related to storage/retrieval systems and conveyors because more rigid and repetitive environments are better suited for the limited capability of existing automation solutions. By contrast, industrial vehicles in the MTE category are largely still driven manually. A March 2023 report released by MHI and Deloitte finds that 74% of supply chain leaders are increasing their supply chain technology and innovation investments with 90% saying they are planning to spend more than $1 million, an 24% increase from 2022 levels. Thirty-six percent plan to spend more than $10 million, up 19% from the prior year. This investment includes solutions for improved supply chain transparency and sustainability, according to the 2023 MHI Annual Industry Report, “The Responsible Supply Chain: Transparency, Sustainability, and the Case for Business.”

The World Industrial Truck Shipment statistics reported that 1.42 million industrial EV vehicles were shipped in 2022 worldwide. However, fewer than 1% of material handling vehicles shipped every year are automated, presenting a significant opportunity to automate industrial vehicles. The cost to operate a non-autonomous material transport vehicle is reported to have an annual salary of $47,244 for warehouse drivers in the U.S. based on Indeed.com, a career and jobsite provider. Although the wages are lower in Europe, Asia and rest of the world, there are more industrial vehicles outside the Americas, or about 83% of vehicle units, thereby an even greater total available market internationally than domestically. The global installed base of industrial EV vehicles with a 3-year life span or less is about 3.75 million vehicles. With a fully loaded, global weighted average annual labor cost of $47,674 with an assumed, on average, 1.5 work shift operations, our current market potential opportunity exceeds $268 billion.

Automating industrial vehicles will address the following challenges:

Labor shortages — The hiring and retention of qualified workers is a critical concern for the markets that material transport vehicles operate within. In fact, Deloitte’s 2020 and 2022 Material Handling Industry Report showed that over 50% of the 1,000 supply chain and manufacturing leaders surveyed rated hiring and employee retention as their biggest challenge (source: MHI Deloitte Industry Report).

Difficulty in scaling — The traditional approaches to vehicle automation make scaling vehicle automation solutions difficult due to strains caused by service lifecycle management and issues with dynamic deployability. Industrial automation customers are forced to coordinate operational components from a variety of different vendors and lack a unifying architecture that allows the technology to scale effectively within and across sites. Significant costs are also associated with expanding the scope of existing automation solutions as they are tightly coupled to specific vehicles and often require an overhaul of the site infrastructure to overcome shortcomings in the automation technology. This can be especially true in niche environments like mines, where the deployability challenges are compounded by unique sites that require heterogeneous fleets. Furthermore, customer service, workforce training, and repair fall under service lifecycle management and must be taken into account along with the technology in order to scale efficiently, according to the “Trends in Supporting and Scaling Modern Automation” report by Ricoh & ABI Research Report.

Lagging technological advancement — Manufacturers of material transport vehicles have core competencies in mechanical, electrical, and control systems while the end users of the vehicles typically specialize in logistics, manufacturing, and material moving. There is limited expertise throughout the material handling value chain in software algorithms, sensing, and high-performance computing. Considering the incumbents’ gaps in leading-edge AV and AI technologies and the pressure existing suppliers face to ship manually-operated vehicles that address the multi-billion dollar demand that already exists, we believe it is unlikely that existing stakeholders will be able to invest in the technological advancements that will solve the industry’s fundamental challenges.

High barriers to adoption — Many solutions for automated material transport require an all-or-nothing commitment from customers: either make a major upfront investment to overhaul operations for automation or postpone automation at the risk of falling behind competition. This all-or-nothing approach to unlocking future return on investment (“ROI”) can be problematic for risk-averse companies that seek to adopt automation solutions. Depending on fleet size, traditional automation solutions such as “robot-in-a-box” may command ROI horizons of up to 4 years. Factoring in ancillary costs like installation, maintenance, on-site testing, integration, and deployment, can also represent a significant annual cost burden, according to findings by Ricoh & ABI Research Report.

To combat these challenges, we have built an Enterprise Autonomy Suite for industrial vehicles that leverages advanced in-vehicle autonomous driving technology and incorporates leading supporting technologies like data analytics, fleet management, cloud, and connectivity. EAS provides a differentiated solution that we believe will drive pervasive adoption of industrial autonomy and create value for customers at every stage of their automation growth.

Business Model: The Enterprise Autonomy Suite for Industrial Vehicles

A number of business models have been developed to support industrial autonomy where software is the enabling technology that’s transforming supply chain logistics under Industry 4.0 and 5.0. Software as a Service (SaaS) is the initial working business model for the company but this is not entirely accurate as vehicle hardware plays an integrated role in automating materials handling. Autonomy requires both the movement of “bits” (or software) and the movement of “atoms” (or hardware). Robots as a Service (RaaS) is a useful business model given the high cost of AGVs and AMRs where industrial customers may want to explore different buying models for both software and hardware usage to align with their needs for capital expenditures and operational expenditures. In our served markets where customers primarily purchase and own their industrial vehicle fleet, we deliver the software that enables self-driving vehicle capability. As such, our EAS software is designed to provide level-4 “high automation”, fully autonomous driving without the need for a human in the vehicle. Cyngn’s business model is thereby more attuned to Driver as a Service (DaaS) as our EAS software integrated with the vehicle hardware enables the customer to remove the human driver for self-driving functionality.

Our unique value proposition stems from the concept that the growth of industrial autonomy requires an approach that deploys applied AV solutions within a system of supportive resources rather than a technology feature that is tuned to a specific industrial vehicle.

Some companies manufacture standard industrial vehicles then integrate industrial automation software for rigid tasks. Others develop new vehicle platforms to enable more advanced automation capabilities, limiting the AV technology to a narrow use case. We developed advanced autonomous vehicle software, DriveMod, for industrial vehicles. DriveMod is a component of EAS that is operationally expansive, vehicle agnostic, and compatible with indoor and outdoor environments. EAS centers around DriveMod’s on-vehicle AV software and is supported by our Cyngn Insight and Cyngn Evolve technology and tools.

Figure 2: The core components that make up our EAS product offering.

Our approach drives value at every stage of a company’s autonomy journey

EAS provides extensible industrial autonomy solutions that can include data-driven actionable insights, partial autonomy to augment existing workflows and support human drivers, and fully autonomous vehicle mobility. By offering flexible data and autonomous services through subscription-based business models, we assuage the industry’s existing challenge of all-or-nothing adoption for autonomous vehicles. Installing DriveMod onto any vehicle unlocks a collection of valuable product offerings that customers can activate over the air, creating lower barriers to entry and enabling customers to benefit from novel data insights while adopting industrial AVs at their own pace. Our solutions also do not require infrastructure investments to enable autonomous vehicle operation.

EAS galvanizes the relationship between AVs and data

Our EAS combines core autonomous vehicle technology with a suite of tools and products that strengthen the ties between industrial business operations and the positive network effects that underpin the relationship between data and AVs. DriveMod uses data from advanced sensors to navigate AVs, creating a de facto mechanism for rich data collection. Vehicles equipped with DriveMod provide the means for us to collect data then organize, analyze, and expose customers to novel insights. This makes the data collected during vehicle operation a new type of asset that adopters of AV technology can take advantage of. Data can be stored in cloud or on-premise servers, according to customer requirements. We intend to have our customers own the data collected at their facilities and for Cyngn to have the rights to use that data for certain purposes, such as testing simulation and development. These data assets present a new opportunity to reveal previously unknown insights about day-to-day operational processes that impact safety, efficiency, vehicle maintenance, and growth.

Figure 3: The EAS product flywheel

As the deployment of industrial vehicles with DriveMod scales up, the amount and diversity of data flowing through Cyngn Insight expands, creating an accelerated feedback loop and powers our ability to use Cyngn Evolve to further enhance DriveMod, and update the on-vehicle software over-the-air, resulting in an ever-improving EAS offering.

Continual Improvement Drives Technology Advancement

DriveMod’s building blocks enable a more consistent cadence of upgrades, improvements, and customer-specific feature development that can be deployed via over-the-air updates. These capabilities ensure that the deployed system stays in sync with the changing application demands while allowing customers to focus on monetary and operational ROI. Our EAS plugs into business operations by creating and collecting real-time data and aggregating it into configurable analytics dashboards that inform customer operations as well as future DriveMod releases, creating a data set specific to each customer from high-resolution data collected during their operations.

Our Approach Augments and Upskills Workforces

Industrial vehicle autonomy represents an opportunity to minimize the adverse impact that labor shortages, employee health, and safety have on a company’s core operations. Autonomous vehicles can be relied upon to fill the voids that commonly create human resource issues like executing repetitive tasks, working during undesirable hours, and operating in uncomfortable or hazardous environments.

Furthermore, existing employees can be exposed to cutting-edge technology and develop new valuable career development opportunities. For instance, a manufacturing community in Wisconsin successfully retrained their employees to be skilled in AMR maintenance after AMRs were introduced to replace traditional conveyors, according to the article “Are Autonomous Mobile Robots at the Tipping Point” by AutomationWorld.

We Designed for Scale

EAS provides a powerful solution to scalability issues, especially for dynamic deployability and service lifecycle management. DriveMod’s vehicle-agnostic capability to deploy AV technology on diverse vehicle fleets has been proven through its deployment on more than ten different vehicle form factors that we have operated autonomously. DriveMod solutions have been commercially released for the Columbia Stockchaser and Motrec MT160 Tugger, with BYD ECB50+ Forklift targeted next. Other autonomous vehicles were deployed as prototypes or as a part of proof-of-concept project. More than five past deployments have been at customer or beta customer sites. Other past deployments were part of our normal R&D activities and product validation that was performed with beta customers.

Our AV development and testing have included road vehicles that navigate complex dynamic environments. DriveMod is capable of perceiving more than 100 dynamic objects per second and then using that perception information to navigate autonomously. This capability has been proven via road testing in difficult driving settings like urban streets. In contrast, the industrial settings of our target market rarely encounter 100 dynamic actors per minute, let alone per second. Scalability is further strengthened by EAS creating common interfaces and experiences that unify customer data and AV operations within and across sites. Thus, proliferating our solutions with customers will be achieved by iteratively adding onto an existing EAS, which minimizes the marginal cost associated with expanding AV operations. Additionally, the deployment of EAS allows for all of the on-going administration, services, and vendors associated with managing the lifecycle of the system to be integrated.

Figure 4: Illustration of DriveMod’s ability to utilize key subsystems across multiple environments and vehicle platforms
(left: off-road utility vehicle; right: indoor material handling vehicle).

Our Products

EAS is a suite of technology and tools that consists of three complementary categories: DriveMod, Cyngn Insight, and Cyngn Evolve.

DriveMod: Industrial Autonomous Vehicle System

We built DriveMod as a modular software product that is compatible with various sensor and computer hardware components that are widely used throughout the autonomous vehicle industry. Our software combined with sensors and components from industry-leading hardware providers covers the end-to-end requirements that enable vehicles to operate autonomously with advanced navigation capabilities. The

Amendment: SEC Form 10-K/A filed by Cyngn Inc.