What changed in this filing

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Item 2. Management’s Discussion and Analysis

2026-08-06 compared with 2026-05-08 · 131 added, 98 removed, 84 unchanged (73% of the section changed)

6 unchanged sentences

Backlog and Pipeline

Backlog as of May 6, 2026 was approximately $4.6 million, representing firm fixed price contracts awarded in the first quarter of 2026 that will be shipped and invoiced through the remainder of 2026.

Our total validated pipeline as of March 31, 2026 was $165.3 million, consisting of single and multi-year opportunities for AI-driven edge, video, and sensor and data management platform across our customer verticals.

Backlog as of August 6, 2026 were approximately $6.9 million, representing firm fixed price contracts awarded in the first and second quarters of 2026 that are expected to be shipped and primarily invoiced in the third quarter of 2026.

Separately, our total validated pipeline as of August 6, 2026 was $206.1 million, consisting of single and multi-year opportunities for AI-driven edge, video, and sensor and data management platform across our customer verticals.

Our pipeline includes opportunities at varying stages of progression with expected award timeframes over the next 18-24 months.

We are a robust AI-driven data management platform that solves complex data challenges for large institutions operating in dynamic and mission-critical environments with rapidly increasing volumes of data being ingested from a similarly rapidly growing number of data sources.

We solve these challenges by structuring “dark” or unstructured data at the edge, the location at which the data is generated and collected, and leveraging purpose-built AI models.

Unstructured, or “dark” data, which is typically categorized as qualitative data, cannot be processed and analyzed via conventional data tools and methods.

Conversely, structured data, typically categorized as quantitative data, is highly organized and easily decipherable by machine learning algorithms.

Structuring and then analyzing data using AI models at the edge, versus transmitting the data from the edge back to a central processing location for structuring and analysis, enables real-time decision making and data-driven operational efficiency.

We specialize in ingesting all available metadata from edge-based sensors used by government and law enforcement agencies around the world, including surveillance cameras (video), audio, telemetry, acoustic, seismic, and autonomous devices, along with large commercial corporations with fundamentally similar capabilities and requirements.

Data generated by these edge-based sensors, including video, can then be run through our trained AI models to detect objects present within the video frame.

Once an object is detected, for example an automobile, additional identifying characteristics of the object can be extracted from the image including the license plate characters and the make, model, and color of the automobile.

This process of analyzing, logging and categorizing ingested data is referred to as “structuring” the data.

Airship AI’s software allows customers to view structured data both in real-time as well as to conduct searches on the structured data at a later point in time.

Real-time structured data use includes, for example, alarms on a specific license plate or a specific make, model or color of automobile.

Non-real-time structured data use includes, for example, searching a database of video data that has been previously ingested and stored to find instances of a particular license plate being visible, along with other logged vehicle characteristics such as make, model and color of an automobile.

Additional edge deployed AI models enable similar object detection and recognition of common and custom trained objects, such as an aircraft, boat, person, animal, bag, or weapon.

Airship AI’s models provide similar data points for these object types allowing analysts the ability to be notified in real-time of the detection of a specified object and similarly search for historically detected objects.

Examples include detecting aircrafts and boats along with their respective tail numbers and hull registration numbers.

Our AI modelling process starts with pre-trained AI models from our technology ecosystem partners which we then customize using proprietary datasets tailored towards our customers unique workflow requirements.

Where customers have pre-existing AI models or engines, we integrate those models or engines into our edge platform allowing customers to leverage proprietary models within the Airship AI software ecosystem.

Our primary offerings include Outpost AI, Acropolis, and Airship Command.

Our offerings allow customers to manage their data across the full data lifecycle, when and where they need it, using a highly secure permissioned based architecture.

Outpost AI is our edge hardware and software offering that is purpose built to structure and analyze data efficiently and effectively at the source using Airship AI trained models.

Once structured, Outpost AI securely encodes the data and streams it to Acropolis for further processing.

In the automobile example, Outpost AI will process the unstructured and unlabeled video data into structured data including images of vehicles, images of plates, make, model, color, locations and plate numbers, as well as confidence levels on the structured results.

Acropolis is our enterprise management software suite which serves as the backbone of our software ecosystem.

Acropolis allows customers with a handful of devices or hundreds of thousands of devices to manage their user and install base efficiently and securely from a single graphical user interface.

Acropolis can be installed and managed locally (on-premises) as well as in cloud/multi-cloud-based system architectures.

Acropolis can work with structured and unstructured data.

In the scenario where Outpost AI processes the unstructured video of vehicles into images, plate numbers and other structured data, Acropolis will compare the structured data against customer repositories of structured data in order to add labels to results for user attention.

Here, Acropolis leaves the initial processing of unstructured data to the edge device (Outpost AI) and handles additional labeling which requires bigger centralized datasets.

Where Acropolis is receiving unstructured data as input from devices, it will do the initial processing of unstructured to structured data similar to what Outpost AI does at the edge before any additional labelling.

This holistic approach allows customers to leverage the benefits of both edge and back-end data structuring and analysis in a “single-pane-of-glass” approach.

Airship Command then allows the customer to view the final labelled data which can be presented in real-time or as search results, as alerts, in automatically updating lists or on maps.

In the vehicle example, Airship Command can present alarms on specific filters such as specific plates, intelligent partial matches, make, model, color and any combination thereof, as well as searches using the same filters against character recognition and vehicle characteristics results.

Airship Command is our suite of visualization tools that allow customers to interact with their data and devices securely and efficiently.

Customer data interaction may include receiving and viewing an alarm triggered by an AI detected event at the edge on a mobile phone, or receiving and viewing events from thousands of edge devices spread across multiple different locations on a large video wall in a Security Operations Center (“SOC”).

Our visualization tools span applications for workstations, web-based browsers, and applications for mobile handheld devices ensuring our customers data is never out of their immediate reach.

We apply AI across the entire offering suite, ensuring that we are extracting as much value from our customers’ existing and emerging data as possible.

Whether it is using machine learning to train new models for deployment at the edge, or using a rules-based approach to detect anomalies based on data generated by machine learning models, we are constantly expanding and evolving our AI capabilities.

Our offerings are used by some of the largest government agencies and commercial organizations in the world.

While we are heavily focused on continuing to grow market share in the United States, our offerings are currently deployed around the world, with significant room to grow in both the governmental and commercial markets.

Our typical customer engagement is a multi-year contractual agreement, an agreement which includes our core offerings as well as professional services, technical support, and software maintenance, which we expect will result in predictable, long-term recurring revenue.

Our history shows that organizations that have chosen to partner with Airship AI stick with Airship AI.

Since our inception and until the Merger in December 2023, we have operated as a 100% employee-owned bootstrapped company with no outside investment, operating in a fiscally conservative model.

based company, we operate in high growth areas, namely the intersection of public safety and AI, with a combined $7 billion edge AI hardware and software addressable market.

Our customers trust us to collect and analyze vast amounts of data in real-time as well as make it available to their users when they need it, where they need it, as securely as possible.

We believe our offerings are purpose-built from the ground up to help ensure we continue to meet or exceed these expectations.

Backlog reflects awards already executed, whereas pipeline reflects identified and qualified opportunities that have not yet resulted in awards.

We can give no assurance as to whether, when, or in what amount pipeline opportunities will convert into backlog or revenue.

Federal Funding Environment

A substantial majority of our revenue is derived from U.S.

federal law enforcement and homeland security customers.

During 2025, uncertainty surrounding federal budget priorities and the pace of government spending, including federal initiatives to reform government processes and reduce expenditures contributed to variability in the timing of government awards and procurement activity, which affected our government business.

More recently, we have observed an improving federal funding environment for the mission areas our platform supports, including border security and public safety, which we believe is reflected in the growth and stage progression of our validated pipeline.

The timing and amount of government awards remain subject to factors outside our control, including appropriations, shifting agency priorities and procurement cycles, and we can provide no assurance regarding the conversion of any particular opportunity.

Strategic Initiatives

We are pursuing a deliberate expansion of our commercial business to complement our established federal law enforcement and homeland security customer base.

While a substantial majority of our revenue is currently derived from government customers, we believe our edge AI and data management platform is directly applicable to commercial organizations with large-scale sensor, security and data-management requirements, and we are investing to broaden our presence across commercial verticals.

The strategic initiatives described below are central to this expansion.

Agentic AI (Ask Airship)

We are developing Ask Airship, an agentic AI capability designed to allow users to query, analyze and act on structured data across our platform using natural language, which we intend to offer as a standalone product complementary to our Outpost AI, Acropolis, Airship Command and Fortress Server offerings.

We intend to make Ask Airship available on a software-as-a-service (subscription) basis as well as on a pay-per-use, consumption-based basis.

For deployments in federal and other security-sensitive environments, we expect on-premises inference to rely on Western open-weight models to satisfy applicable procurement and model-origin requirements.

We are extending our edge AI and data management platform to ingest, structure and act on data from autonomous and robotic sensor platforms, with a particular focus on commercial customers as well as government customers, consistent with our broader commercial expansion.

We are evaluating commercial models for these capabilities, including subscription and as-a-service arrangements.

We can give no assurance regarding the timing, cost, market acceptance or financial contribution of this initiative, which is subject to development, integration, supply-chain and regulatory risks.

We are an AI-driven data management platform that solves complex data challenges for large institutions operating in dynamic and mission-critical environments characterized by rapidly increasing volumes of data ingested from a rapidly growing number of data sources.

We address these challenges by structuring “dark” or unstructured data at the edge, the location at which the data is generated and collected using purpose-built AI models, enabling real-time decision-making rather than transmitting raw data to a central location for processing.

We specialize in ingesting metadata from edge-based sensors used by government and law enforcement agencies worldwide, including video, audio, telemetry, acoustic, seismic and autonomous devices, as well as by large commercial organizations with similar requirements.

Our trained AI models detect and extract identifying characteristics of objects within a video frame (for example, a vehicle’s license plate characters and its make, model and color), a process we refer to as “structuring” the data, and allow customers to act on that data both in real time and through historical search.

Our primary offerings include Outpost AI (edge structuring and analysis), Acropolis (enterprise management software backbone, deployable on-premises or in cloud/multi-cloud architectures), Airship Command (visualization across workstation, web and mobile) and Fortress Server (our on-premises data center server and storage platform).

These product offerings allow customers to manage their data across the full data lifecycle through a secure, permission-based, single-pane-of-glass architecture.

Our typical customer engagement is a multi-year agreement that includes our core offerings together with professional services, technical support and software maintenance, which we expect to result in predictable, long-term recurring revenue.

From inception until the Merger in December 2023, we operated as a 100% employee-owned, bootstrapped company with no outside investment.

As a U.S.-based company, we operate at the intersection of public safety and AI, in which we address a combined market we estimate at more than $70 billion in 2026 and growing, spanning edge AI hardware and software (approximately $30 billion, according to Grand View Research, 2026, service and professional robotics, including robotics-as-a-service (approximately $31 billion according to Fortune Business Insights, 2026), and agentic AI (approximately $10 billion according to multiple industry analysts, 2026).

Fair Value Transactions in Connection with Merger

4 unchanged sentences

Liability as of

March 31, 2026

June 30, 2026

December 31, 2025

3 unchanged sentences

Total liabilities measured at fair value

Other income related to instruments recorded at fair value during the three months ended March 31, 2026 and 2025

Other income related to instruments recorded at fair value during the three months ended June 30, 2026 and 2025

$ (1,026,133 )

$ (21,795,769 )

Other income related to instruments recorded at fair value during the six months ended June 30, 2026 and 2025

Private Placement and Public Warrants in Connection with Merger

3 unchanged sentences

The purpose of this reduced exercise price was to potentially raise proceeds received from the exercise of such warrants, if any, for working capital and general corporate purposes.

As of March 31, 2026, there were 515,000 private placement warrants and 16,145,006 public warrants outstanding.

As of June 30, 2026, there were 515,000 private placement warrants and 16,145,006 public warrants outstanding.

Segment Reporting

6 unchanged sentences

Results of Operations

The following table sets forth key components of our results of operations during the three months ended March 31, 2026 and 2025.

The following table sets forth key components of our results of operations during the three months ended June 30, 2026 and 2025.

(dollars in thousands)

6 unchanged sentences

Other income (expense):

(Loss) from change in fair value of earnout liability

(Loss) in fair value of warrant liability

Interest income, net

Total other expense, net

(Loss) before provision for income taxes

Provision for income taxes

Net Revenues — Net revenues for the three months ended June 30, 2026 increased $1,977,000 to $4,124,000 as compared to $2,147,000 for the three months ended June 30, 2025.

The increase was due to increased commercial orders, which more than offset variability in the timing of federal awards during the period.

Consistent with the concentrated, enterprise nature of our customer base, two customers represented approximately 84% of revenue for the three months ended June 30, 2026.

Backlog as of June 30, 2026 was approximately $6.9 million, representing firm fixed price contracts awarded in the first and second quarters of 2026 that are expected to be shipped and primarily invoiced in the third quarter of 2026.

Cost of Net Revenues — Cost of net revenues primarily consists of product costs and post customer support.

For the three months ended June 30, 2026, cost of sales increased $412,000 to $1,026,000 as compared to $614,000 for the three months ended June 30, 2025.

The increase was due to increased sales and reflects product mix with increased higher margin commercial sales during the three months ended June 30, 2026, offset by raw material cost increases.

Research and Development Expenses — Research and development expenses for the three months ended June 30, 2026 increased $113,000 to $854,000 as compared to $741,000 for the three months ended June 30, 2025.

The increase was due to increased expenses for product development in the United States and Taiwan.

Selling, General and Administrative Expenses — Selling, general and administrative expenses for the three months ended June 30, 2026 increased $921,000 to $3,735,000 as compared to $2,814,000 for the three months ended June 30, 2025.

The increase is primarily due to an increase in stock-based compensation expense of $579,000 and other personnel costs.

Other (Expense) — Other expense for the three months ended June 30, 2026 was $916,000 as compared to other expense for the three months ended June 30, 2025 was $21,735,000.

Other expense for the three months ended June 30, 2026 consisted of (i) loss from change in fair value of earnout liability of $193,000;

(ii) loss from change in fair value of warrant liability of $833,000;

and offset by (iii) interest income of $110,000.

The loss from change in fair value of earnout liability resulted from an increase in the our share price.

The expense from change in fair value of warrant liability was primarily the result of an increase in our stock price.

Other expense for the three months ended June 30, 2025 was $21,735,000 as compared to other income of $17,486,000 for the three months ended June 30, 2024.

Other expense for the three months ended June 30, 2025 consisted of (i) loss from change in fair value of earnout liability of $7,302,000;

(ii) loss from change in fair value of warrant liability of $14,494,000;

and (iii) other income of $61,000.

The loss from change in fair value of various financial instruments was primarily the result of an increase in our stock price.

Net (Loss) — Net loss for the three months ended June 30, 2026 was $2,407,000 as compared to net (loss) of $23,757,000 for the three months ended June 30, 2025.

The net loss primarily related to increases in selling, general and administrative and research and development expenses.

Net loss for the three months ended June 30, 2025 was $23,757,000 as compared to net income of $18,462,000 for the three months ended June 30, 2024.

The net loss primarily related to noncash expenses of $22,264,000.

Noncash items included (i) loss from change in warrant liability of $14,494,000;

(ii) loss from change in earnout liability of $7,301,000;

(iii) stock based compensation of $372,000;

and (iv) net amortization of operating lease right of use asset of $97,000.

The following table sets forth key components of our results of operations during the six months ended June 30, 2026 and 2025.

(dollars in thousands)

Six Months Ended,

Cost of net revenues

Research and development expenses

Selling, general and administrative expenses

Total operating expenses

Operating loss

Other income (expense):

(Loss) gain from change in fair value of earnout liability

Gain change in fair value of warrant liability

Gain from change in fair value of warrant liability

Interest income, net

Total other income, net

(Loss) income before provision for income taxes

Total other (expense) income, net

(Loss) before provision for income taxes

Provision for income taxes

Net (loss) income

Net Revenues — Net revenues for the three months ended March 31, 2026 increased $850,000 to $6,353,000 as compared to $5,503,000 for the three months ended March 31, 2025.

The increase was due increased commercial orders.

On January 20, 2025, President Trump signed an executive order creating an advisory commission, the Department of Government Efficiency, to reform federal government processes and reduce expenditures.

Pressures on and uncertainty surrounding the U.S.

federal government’s budget, and potential changes in budgetary priorities and spending levels, could adversely affect staffing levels and the funding for government projects.

Disruptions in how the government agencies operate due to these policies is materially affecting our government business.

Net Revenues — Net revenues for the six months ended June 30, 2026 increased $2,827,000 to $10,477,000 as compared to $7,650,000 for the six months ended June 30, 2025.

The increase was due to increased commercial orders, which more than offset variability in the timing of federal awards during the period.

Consistent with the concentrated, enterprise nature of our customer base, four customers represented approximately 89% of revenue for the three months ended June 30, 2026.

Cost of Net Revenues — Cost of net revenues primarily consists of product costs and post customer support.

For the three months ended March 31, 2026, cost of sales decreased $81,000 to $3,187,000 as compared to $3,268,000 for the three months ended March 31, 2025.

The decrease was due product mix with increased higher margin commercial sales during the three months ended March 31, 2026, offset by raw material cost increases.

Research and Development Expenses — Research and development expenses for the three months ended March 31, 2026 increased $125,000 to $844,000 as compared to $719,000 for the three months ended March 31, 2025.

For the six months ended June 30, 2026, cost of sales increased $331,000 to $4,213,000 as compared to $3,882,000 for the six months ended June 30, 2025.

The increase was due to increased sales and reflects product mix with increased higher margin commercial sales during the six months ended June 30, 2026, offset by raw material cost increases.

Research and Development Expenses — Research and development expenses for the six months ended June 30, 2026 increased $238,000 to $1,698,000 as compared to $1,460,000 for the six months ended June 30, 2025.

The increase was due to increased expenses for product development in the United States and Taiwan.

Selling, General and Administrative Expenses — Selling, general and administrative expenses for the three months ended March 31, 2026 increased $674,000 to $3,904,000 as compared to $3,230,000 for the three months ended March 31, 2025.

Selling, General and Administrative Expenses — Selling, general and administrative expenses for the six months ended June 30, 2026 increased $1,594,000 to $7,638,000 as compared to $6,044,000 for the six months ended June 30, 2025.

The increase is primarily due to an increase in stock-based compensation expense of $816,000 and other personnel costs.

Other Income (Expense) — Other income for the three months ended March 31, 2026 was $861,000 as compared to other income for the three months ended March 31, 2025 was $25,422,000.

Other income for the three months ended March 31, 2026 consisted of (i) loss from change in fair value of earnout liability of $726,000;

(ii) gain from change in fair value of warrant liability of $1,499,000;

Other (Expense)Income — Other expense for the six months ended June 30, 2026 was $55,000 as compared to other income for the six months ended June 30, 2025 was $3,687,000.

Other expense for the six months ended June 30, 2026 consisted of (i) loss from change in fair value of earnout liability of $919,000;

offset by (ii) gain from change in fair value of warrant liability of $666,000;

and (iii) interest income of $198,000.

The loss from change in fair value of earnout liability resulted from the increase in the volatility factor to 78.4%, offset by a decrease in the our share price.

The income from change in fair value of warrant liability was primarily the result of a decrease in our stock price.

Other income for the three months ended March 31, 2025 consisted of (i) gain from change in fair value of earnout liability of $9,824,000;

The loss from change in fair value of earnout liability resulted from the increase in the volatility factor to 76.8%.

The reduction in gain from change in fair value of warrant liability was primarily the result of a decrease in our stock price as compared to the change in stock price during the six months ended June 30, 2025.

Other income for the six months ended June 30, 2025 was $3,687,000 as compared to other expense of $13,076,000 for the six months ended June 30, 2024.

Other income for the six months ended June 30, 2025 consisted of (i) gain from change in fair value of earnout liability of $2,522,000;

(ii) gain from change in fair value of warrant liability of $1,027,000;

(iii) other income of $77,000.

The gain from change in fair value of various financial instruments was primarily the result of a decrease in our stock price.

Net (Loss) Income — Net (loss) for the three months ended March 31, 2026 was $721,000 as compared to a net income of $23,708,000 for the three months ended March 31, 2025.

and (iii) other income of $138,000.

The gain from change in fair value of various financial instruments was primarily the result of an increase in our stock price.

Net (Loss) — Net loss for the six months ended June 30, 2026 was $3,127,000 as compared to net loss of $49,000 for the six months ended June 30, 2025.

The net loss primarily related to increases in selling, general and administrative and research and development expenses.

Net income for the three months ended March 31, 2025 primarily related to noncash items of $24,833,000.

Net loss for the six months ended June 30, 2025 was $49,000.

The net loss primarily related to an operating loss of $3,700,000 offset by noncash items of $2,569,000.

Noncash items included (i) gain from change in warrant liability of $1,027,000;

and (ii) gain from change in earnout liability of $9,823,000;

(ii) gain from change in earnout liability of 2,522,000;

and offset by (iii) stock based compensation of $800,000;

and (iv) net amortization of operating lease right of use assets of $83,000.

Liquidity and Capital Resources as of March 31, 2026 and 2025

Liquidity is our ability to generate funds to support its current and future operations, satisfy its obligations, and otherwise operate on an ongoing basis.

and (iv) net amortization of operating lease right of use asset of $180,000.

Liquidity and Capital Resources as of June 30, 2026 and 2025

Liquidity is our ability to generate funds to support our current and future operations, satisfy its obligations, and otherwise operate on an ongoing basis.

Significant factors in the management of liquidity are funds generated by operations, levels of accounts receivable and accounts payable and capital expenditures.

We have incurred losses from operations in the past few years and had an accumulated deficit of $46 million as of March 31, 2026.

We have incurred losses from operations in the past few years and had an accumulated deficit of $48.7 million as of June 30, 2026.

As of June 30, 2026, we had cash and cash equivalents of $12.4 million and no outstanding debt.

Based on our current available cash and operations, we have concluded there is no substantial doubt about our ability to continue as a going concern for at least twelve months from the issuance of these financial statements.

On October 8, 2025, we entered into warrant exercise inducement offer letter with the holder of existing common stock warrants exercisable for an aggregate of 2,162,162 shares of common stock to exercise such warrants at the existing exercise price of $4.50 per share, in exchange for our agreement to issue new common stock warrants to purchase 2,702,702 shares of common stock at an exercise price per share of $6.20.

The aggregate gross proceeds received from the exercise of the existing warrants were approximately $9,729,729, before deducting financial advisory fees.

The aggregate gross proceeds received from the exercise of the existing warrants were $9,729,729, before deducting financial advisory fees.

We intend to use the net proceeds from the exercise of the existing warrants for working capital and general corporate purposes.

Operating Activities

Net cash generated by operating activities for the three months ended March 31, 2026 was $814,000.

Net cash generated by operating activities for the six months ended June 30, 2026 was $579,000.

This amount was primarily related to (i) net loss of 3,127,000;

and (ii) noncash items of $5,000;

offset by (iii) operating assets and liabilities changes of $1,540,000 (including a $493,000 increase in deferred revenues).

Noncash items included (iv) gain from change in warrant liability of $1,499,000;

and offset by (v) loss from change in earnout liability of $726,000;

(vi) stock based compensation of $666,000;

and (vii) net amortization of operating lease right of use asset of $102,000.

Net cash used in operating activities for the three months ended March 31, 2025 was $2,098,000.

This amount was primarily related to (i) net income of $23,708,000;

and offset by (ii) operating assets and liabilities reductions of $973,000 (including a $713,000 reduction in deferred revenues);

and (iii) noncash items of $24,833,000.

offset by (ii) noncash items of $2,077,000;

and (iii) operating assets and liabilities changes of $1,629,000 (including a $314,000 increase in deferred revenues).

Noncash items included (iv) loss from change in earnout liability of $919,000;

(v) stock based compensation of $1,617,000;

(vi) net amortization of operating lease right of use asset of $207,000;

and offset by gain from change in warrant liability of $666,000.

Net cash used in operating activities for the six months ended June 30, 2025 was $3,919,000.

This amount was primarily related to (i) net loss of $49,000;

(ii) net working capital reductions of $1,301,000 (including a $606,000 reduction in deferred revenues);

and offset by (iii) noncash items of $2,569,000.

Noncash items included (iv) gain from change in warrant liability of $1,027,000;

and (v) gain from change in earnout liability of $9,823,000;

(v) gain from change in earnout liability of 2,522,000;

and offset by (vi) stock based compensation of $800,000;

and (vii) net amortization of operating lease right of use assets of $83,000.

and (vii) net amortization of operating lease right of use asset of $180,000.

Financing Activities

Net cash provided by financing activities for the three months ended March 31, 2026 was $11,000 and consisted of proceeds from stock option exercises.

Net cash used in financing activities for the three months ended March 31, 2025 was $497,000 and consisted of (i) repayment of advances by founders of $600,000;

Net cash provided by financing activities for the six months ended June 30, 2026 was $56,000 and consisted of net proceeds from stock option and warrant exercises.

Net cash used in financing activities for the six months ended June 30, 2025 was $1,182,000 and consisted of (i) repayment of advances by founders of $1,300,000;

and offset by (ii) net proceeds from exercise of warrants of $60,000;

7 unchanged sentences

There is a one three year option to extend the lease based on the fair market rate on October 31, 2027.

The option must be exercised by October 31, 2026.

We do not believe that is reasonably certain that the lease will be extended.

On December 6, 2024, we entered into two separate office leases in Mooresville, North Carolina, the terms of which commenced on February 1, 2025.

We lease an aggregate of 5,240 square feet and the net monthly payment is approximately $9,105.

We lease an aggregate of 5,240 square feet and the net monthly payment is $9,105.

The leases expire January 31, 2028 and the monthly payment increases 3% on February 1, 2026 and each year thereafter.

10 unchanged sentences

We believe that the significant accounting policies described in “ Note 2, Summary of Significant Accounting Policies ” to our audited consolidated financial statements are accurate and complete.

The critical accounting estimates and policies during the three months ended March 31, 2026 have not materially changed to those discussed in our Annual Report on Form 10-K for the year ended December 31, 2025.

The critical accounting estimates and policies during the three and six months ended June 30, 2026 have not materially changed to those discussed in our Annual Report on Form 10-K for the year ended December 31, 2025.

QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK.

1 unchanged sentence

Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-Q

Item 2. Management’s Discussion and Analysis