NASDAQ: BNAI

Since
then, we have enhanced these capabilities into scalable technology designed for enterprise deployment. In 2025, we advanced the general
availability of our platform, designed to support deployment of our AI solutions across enterprise environments and real-world operational
settings. Our architecture is built on a modular foundation spanning perception, understanding, and response, enabling adaptable and
context-aware interaction systems. We focus on providing configurable solutions that meet specific enterprise use cases, including customization,
workflow integration, and cross-channel deployment. Our ongoing development efforts are focused on expanding platform scalability, strengthening
enterprise integrations, and supporting real-world operational environments.

Our
initial commercialization efforts have focused on healthcare applications, with continued expansion into additional verticals, including
hospitality, insurance, and advertising and media. We are deploying our solutions to address resource constraints, improve operational
efficiency, and support more informed decision-making across these environments. We continue to expand across these verticals while refining
our capabilities to meet the demands of complex, real-world operational settings. Recognizing the broader applicability of intelligent
engagement technologies, we are expanding the range of enterprise use cases supported by our platform while enhancing performance, scalability,
and integration across industry-specific environments.

We
aim to ensure our AI solutions operate effectively across cloud, on-premises, and hybrid environments, supporting seamless integration
with our customers’ systems, including deployment of our multimodal AI Agents within native applications, kiosks, and software
development kit integrations. We believe that by focusing on the intersection of personalization, customization, and configuration, we
can deliver versatile AI solutions that enhance value for both businesses and their customers.

4

Commercial
Development

As
a pre-revenue company, revenue in 2022 through 2024 was minimal. Initial revenues in 2022 were generated from beta testing a mobile advertising
platform under an exploratory business model, which was subsequently discontinued. In November 2023, we acquired our first healthcare
customer through our entry-level community cloud AI Agent offering.

In
2024, we expanded our customer base with AI Agent pilots across additional healthcare organizations. These pilot initiatives primarily
focused on evaluating our AI Agents in real-world healthcare settings, including patient engagement, education, and operational support
use cases. During the same period, we established commercial partnerships with two healthcare technology companies and an audiovisual
media branding firm to extend global awareness, sales opportunities, and technological capabilities.

In
2025, we continued to expand geographically and across new verticals. In Mexico, we strengthened our presence through strategic partnerships
involving SKYE LATAM and related entities. In the United States, we deepened engagement with healthcare organizations while expanding
into the insurance sector, including through a strategic partnership with Swiss Life Global Solutions. We maintained momentum in South
Africa through ongoing collaborations with local technology partners, including Valio Technologies and hospitality-related partners.
Additionally, we entered the hospitality vertical, deploying AI solutions designed to enhance operational efficiency, customer engagement,
and data sovereignty across properties and services. These activities reflect the progression from initial pilot initiatives toward broader
deployment opportunities across multiple industry verticals.

We
provide configurable, enterprise-grade AI designed to connect human intent to enterprise systems, workflows, and execution, while delivering
secure, consistent, and compliant interactions across industry-specific environments. Our solutions are designed not only to engage in
conversation, but to execute tasks and trigger actions within enterprise systems. Our AI Agents can connect to clients’ real-time
data systems to access approved information, enabling personalized responses while maintaining compliance with applicable privacy and
data protection regulations. We also offer tools that support clients’ customers in managing their personal data and interactions.

Our
solutions emulate natural, human-like conversations to create meaningful interactions and improved user experiences. Our technology enables
rapid training and deployment across customer-defined environments and multiple engagement modes, including web (desktop, mobile, and
applications), phone (voice and text), and physical locations via kiosks. By supporting interactions on preferred devices and integrating
with clients’ backend systems—such as customer relationship management (CRM), enterprise resource planning (ERP), and IoT
platforms—our solutions can be widely adopted while delivering operational efficiencies, particularly in industries seeking to
address labor and cost constraints.

The
platform integrates multiple components into a seamless, configurable AI Agent, trained on a client’s internal data to provide
tailored customer service, education, and engagement solutions. Our AI Agents operate with existing LLMs, including models from
providers such as Anthropic and Meta (Llama), while leveraging small footprint models and additional data retrieval techniques to
optimize computational efficiency and safety. The system dynamically adjusts dialogue, personality, and appearance to suit
client-specific environments and user needs. Deployment is flexible across mobile apps, desktops, kiosks, and SDK integrations
within secure, ringfenced environments. These AI Agents are powered by our proprietary Engagement Language Model (ELM™), which
orchestrates multi-modal perception, understanding, and response to deliver adaptable, secure, and enterprise-ready
interactions.

Automotive
Commercial Development

We
believe that the automotive industry represents a significant opportunity for the adoption of conversational and agentic AI due to increasing
cost pressures, evolving consumer expectations for digitally enabled engagement, and the need to continuously improve efficiency across
dealership and service operations. Consumer behavior continues to shift toward online and mobile-first interactions, and we believe these
dynamics create a favorable environment for AI-driven automation and decision-support tools that can enhance customer experiences and
streamline internal workflows.

Our
initial automotive commercial development strategy in 2023 was focused on building and deploying a conversational and agentic AI solution
that could support the administration of vehicle service contracts and warranty claims, reduce fraud, improve cash flow and reduce overall
dealer costs. This initial strategy incorporated the vision of having conversational AI agents replace the traditional owner’s
manual for a specific year, make and model and allow vehicle operators to engage in natural conversations with an AI agent. The Company
created its first demonstration of this in July 2023.

5

In
August 2023, the Company entered into an exclusive global automotive reseller agreement with AFG Companies, Inc. The strategy was to
advance our vision and leverage the nearly 1,000 franchise dealerships within the AFG Companies, an extended warranty company that administers
vehicle service contracts and other related Finance & Insurance products to dealerships, agencies, and manufacturers. The shift in
our initial vision was at the direction of the exclusive reseller, AFG, in October 2023, and the new go-to-market strategy was to implement
AI agents within the dealership for sales, service and dealer principal interaction. The Company and AFG introduced the new go-to-market
strategy to attendees of the 2023 NADA (National Automotive Dealers Association) Show, hosted at the MGM Grand to select invitation-only
participants. Our current automotive product suite includes multiple AI implementations designed to support both consumer-facing engagement
and internal dealership operations, including: (i) Web AI Agent, which enhances online dealership experiences by understanding customer
intent, answering questions, and supporting lead capture; (ii) In-Vehicle Experience, designed to connect with vehicle data, mobile applications,
and contextual information to provide personalized engagement opportunities; (iii) Sales AI Agent, which supports in-dealership customer
interactions through interactive kiosk-based experiences; (iv) Service AI Agent, which assists customers with appointment scheduling,
maintenance inquiries, and service program education; and (v) Technician AI Agent, which provides real-time guidance and information
to technicians while supporting adherence to OEM requirements.

By
early October 2024, the Company completed a technology integration with Dealer.com, a Cox Automotive company, to enable retrieval of
live inventory data from a participating dealership. In January 2025, we terminated our relationship with AFG Companies, Inc. and subsequently
announced the termination publicly, along with the initiation of legal action. Following this termination, we shifted our automotive
commercialization strategy to focus on connecting to vehicle operators and delivering in-vehicle engagement capabilities, providing consumers
with the ability to search hands-free while driving, make reservations, and manage vehicle maintenance and repair through AI-driven voice
interaction. The Company has been in discussion with a global auto manufacturer (OEM) to implement this strategy and anticipates a business
decision by the end of Q2 2026. While we believe these initiatives may accelerate distribution and adoption, we cannot guarantee that
our strategy or their relationships will result in increased customer usage or increased revenue.

Differentiation
Through Configurable Safety and Security

A
core differentiator of our AI Agents is their ability to operate within well-defined boundaries, producing accurate, contextually appropriate
responses while minimizing the risk of fabricated or misleading outputs, commonly referred to as “hallucinations.” This is
achieved through a combination of architectural design choices, configurable safety layers, and ongoing validation practices.

Our
platform is built on retrieval-augmented generation (“RAG”), a technique in which the AI system retrieves relevant information
from an approved, client-specific knowledge base before generating a response. Rather than relying solely on patterns learned during
model training (which can produce plausible but inaccurate outputs), our AI Agents ground their responses in verified, current information
provided and maintained by the client. This reduces the likelihood of the model generating statements that go beyond what the approved
data supports.

A
key component of our RAG implementation is confidence-based response management. Each retrieval query produces a relevance score indicating
how well the retrieved content matches the user’s input. When that score falls below a defined threshold, signaling that the system
cannot locate sufficiently relevant information to formulate a reliable response, the platform routes the interaction to a pre-configured
fallback, such as prompting the user to rephrase their question. This prevents the model from generating speculative responses in the
absence of adequate source material, a common failure mode in AI systems that are otherwise designed to always produce an output.

Our
retrieval architecture incorporates several advanced techniques to improve the quality and relevance of retrieved content:

●
Semantic search using vector embeddings,
which identifies conceptually related information rather than relying on exact keyword matches;

●
Hybrid retrieval, which combines semantic
and keyword-based methods to improve recall across diverse query types;

●
Query decomposition and expansion, which
break down complex questions and broaden search coverage to capture relevant content that a narrower query might miss;

●
Re-ranking, which reorders retrieved results
by relevance before they reach the response generation layer; and

●
Context enrichment, which augments retrieved
content with supplementary information to improve response coherence and accuracy.

Our
platform also incorporates a configurable safety and data protection layer that sits between raw user inputs and the core AI processing
pipeline. This layer performs two primary functions. First, it handles entity identification and anonymization: when a user provides
personally identifiable or sensitive information (for example, a patient sharing their name and medical history in a healthcare context),
the system identifies those data entities and replaces them with anonymized identifiers before the data is processed or persisted. This
reduces the risk of exposing sensitive personal information to third-party model providers. Second, the layer includes a moderation function
that screens inputs for adversarial, inappropriate, or policy-violating content before it reaches either the language model or the information
retrieval system. This is designed to prevent prompt injection and other attempts to manipulate the AI’s behavior outside of its
intended parameters.

The
accuracy and reliability of our AI Agents are evaluated using RAGAS (Retrieval-Augmented Generation Assessment), an established open-source
framework for measuring the performance of RAG-based systems. Our validation process draws on both controlled test results and outcomes
observed in live customer deployments, providing a basis for ongoing quality monitoring and continuous improvement.

6

Customization,
Configuration, and Optimization

Our
AI Agents are designed to be extensively configurable, allowing clients to tailor the interaction experience to their specific user populations,
brand standards, and operational contexts.

On
the communication side, clients can adjust automatic speech recognition (ASR, the system’s ability to interpret spoken input),
text-to-speech (TTS, the system’s ability to generate spoken responses), and natural language processing (NLP, the system’s
ability to understand and generate human language) parameters to configure tone, cadence, personality, and emotional register. NLP configuration
also controls response depth: the same underlying knowledge base can produce detailed, technical responses for healthcare professionals
or concise, plain-language responses for consumer-facing interactions.

AI
Agents can additionally be configured with a visual persona, including customizable physical appearance and professional attire
appropriate to the deployment context (such as medical scrubs, business attire, or industry specific uniforms). This degree of
visual personalization is grounded in evidence from published research indicating that human-like, contextually appropriate AI
representations can improve user engagement and trust, factors that are particularly significant in high-stakes environments such as
healthcare.

Deployment

Our
modular architecture is designed to support rapid deployment. Source data can typically be ingested and made available for agent training
and response generation within a matter of hours through a standardized data interface, though actual timelines may vary depending on
the complexity of the use case and the scope of the solution being deployed.

Once
data has been ingested, our platform uses a combination of statistical and heuristic methods to accelerate agent training and dialogue
management configuration, reducing the time required before an agent is ready for live deployment.

Deployments
can be configured for cloud, on-premises, or hybrid environments, and optimized for the client’s existing hardware, operating systems,
and IT infrastructure. Our AI Agents support multiple engagement modes, including web (desktop, mobile, and in-app), phone (voice and
text), and physical installations via kiosks, enabling clients to meet their users across whichever channels are most relevant to their
operations.

Use
Cases

We
deploy our AI solutions across industry-specific and cross-industry use cases, focused on operational environments where engagement drives
measurable actions and outcomes. Our current use cases reflect learnings from active deployments and pilot initiatives including international
markets such as Mexico, where localized data, regulatory requirements, and in-market workflows inform solution design and performance.
These deployments have contributed to the refinement of our platform’s ability to integrate with third-party systems, support regulated
environments, and operate across both digital and physical interfaces.

7

Hospitality
and Service Operations

We
deploy AI-powered assistants across hospitality and service operations to support real-time engagement, service coordination, and operational
execution. These solutions are being advanced through pilot initiatives and early deployments in hospitality and high-traffic service
environments.

Guest
Experience Solution: Supports hospitality environments by managing guest requests, coordinating services, and delivering personalized
recommendations across voice, text, and on-site interfaces.

Operations
Coordination Solution: Connects customer interactions to internal workflows, enabling staff coordination, task execution, and
service fulfillment in real time.

Concierge
Solution: Provides context-aware recommendations and booking support for dining, entertainment, transportation, and local services,
integrating with third-party providers where applicable.

These
solutions are designed to operate across digital and physical environments, including kiosks, mobile devices, and embedded systems, enabling
seamless engagement throughout the customer journey.

Healthcare
and Life Sciences

We
deploy AI-driven solutions to support patient evaluation, patient engagement, care navigation, integration of quality initiatives, patient-centered focus, care variation analysis, and adherence within regulated
healthcare environments. These use cases have been informed by deployments and pilot programs in international markets, including
implementations involving healthcare leaders and partners in Latin America.

Patient
Engagement Solution: Provides education and support related to medications, treatment plans, and care protocols, with the goal
of improving adherence and patient outcomes.

Care
Navigation Solution: Assists patients with scheduling, accessing services, and understanding care pathways, reducing administrative
friction and improving access to care.

Insurance
and Benefits Solution: Supports education and decision-making related to healthcare coverage, including commercial and
Medicare Advantage and related programs.

A Comprehensive Continuum of
Care Solution: Facilitates the integrated management of acute, chronic, and complex multi-morbidity presentations— including endocrine, rheumatologic, and
behavioral health pathologies.

These
solutions are designed to operate within secure, governed environments and integrate with existing healthcare systems and workflows where
required.

Advertising
and Media

Interactive
Engagement Solution: Transforms traditional digital content into conversational, interactive experiences that enable brands to
engage directly with consumers and drive measurable actions and outcomes.

This
use case builds on our experience in brand engagement and digital media, where interactive formats are used to convert passive content
into active, two-way experiences.

8

Automotive

We
support targeted automotive use cases focused on dealership and service environments. These deployments have informed our approach to
integrating AI into operational workflows and customer-facing systems.

Retail
and Service Solution: Enhances customer interactions across online and in-person dealership experiences, supporting sales and
service workflows.

Technician
Support Solution: Provides real-time access to information and procedural guidance for service personnel, supporting consistency
and operational efficiency.

We
expect to continue expanding supported use cases across existing verticals and into additional industries, including hospitality, insurance,
and other service-based sectors, as we scale deployments, expand internationally, and further develop platform capabilities.

Recent
Developments

During
2025, we advanced the deployment and commercialization of our AI platform across multiple industries and geographies, with a focus on
healthcare, hospitality, insurance, media, and international expansion. These initiatives reflect our strategy to deploy AI in real-world
operational environments where engagement drives measurable actions and outcomes.

In
Latin America, we announced and initiated an exclusive licensing partnership with SKYE Inteligencia LATAM, S.A.P.I. de C.V. (“SKYE
LATAM”), designed to support government and commercial market opportunities across Latin America and Spain. We also announced the
formation of Skye Salud, together with KNOBLOCH Information Group and SKYE LATAM, to support healthcare modernization initiatives in
Mexico through secure, localized AI solutions designed for regulated healthcare environments.

In
Africa, we announced and initiated a strategic partnership with Valio Technologies (Pty) Ltd to establish an exclusive AI licensing framework
for government and commercial markets across the region. As part of this initiative, we also announced a memorandum of understanding
with Nelson Mandela University for an institution-approved pilot deployment focused on student wellbeing within a governed, closed-loop
environment.

In
hospitality, we announced and initiated our entry into guest-facing service environments through a collaboration with Seven Visions Resort
& Places, The Dvin, in Yerevan, Armenia. This initiative represents our expansion into hospitality-focused deployments that
support real-time guest engagement and service coordination in physical environments.

In
insurance, we announced and initiated a strategic partnership with Swiss Life Global Solutions to support the implementation of AI-driven
solutions intended to enhance customer value through digital health, mental health, and financial wellbeing services.

In
advertising and media, we announced and initiated reseller and deployment activity through Vybroo and Grupo Siete, including pilot initiatives
designed to support interactive, AI-driven consumer engagement across media platforms in Mexico and other international markets.

These
developments contributed to the continued refinement of our platform, including multilingual deployment capabilities, integration with
third-party systems, support for regulated and institution-approved environments, and the ability to operate across both digital and
physical interfaces.

9

The
AI Industry

We
operate within the generative AI industry, a rapidly advancing segment within the broader artificial intelligence market, positioned
at the intersection of machine learning, deep learning, and natural language processing. Our conversational AI solutions allow us to
target a total addressable market estimated to grow from approximately $10 billion to $47 billion¹ by 2030.

The
growing adoption of generative AI is being driven by the pursuit of cost reduction, value enhancement, differentiated customer engagements,
and operational efficiency benefits that we believe are not available to organizations through legacy solutions.

Agentic
AI. We believe the landscape of generative AI has evolved from knowledge-based tools such as chatbots and co-pilots to AI-enabled
agents capable of executing complex, multi-step workflows. Industry research indicates increasing enterprise focus on deploying agent-based
AI systems capable of execution-oriented tasks.²

Growing
Acceptance of AI. Industry research indicates that a majority of organizations have adopted some form of artificial intelligence
and are increasingly incorporating generative AI into business functions.³,⁴

Trust,
Security & Reliability. Industry research indicates that organizations are focused on addressing concerns related to bias,
hallucinations, inaccuracies, cybersecurity, privacy, and intellectual property.⁴

Ethical
and Regulatory Change. Governments and regulatory bodies are introducing frameworks to support responsible AI deployment and
data protection.⁵

Timely,
Personalized Experiences. Industry research indicates that organizations prioritizing personalization can improve commercial
outcomes and better meet evolving consumer expectations.⁶

Our
Core Strengths

Versatile
Applications and Configurable Design Across Industries.

We
believe our AI Agents are deployable across multiple industry verticals, regardless of whether a business leverages public or private
cloud services, localized or hybrid environments. Our solutions are designed to integrate with customers’ existing systems and
workflows across industries, enabling flexibility without requiring significant infrastructure changes. We believe this broad applicability
allows us to respond efficiently to evolving market demands and expand into new verticals without substantial delays or incremental costs.

Configurable
Solutions Delivering Personalized Experiences.

We
believe every engagement is unique. While our AI Agents are designed to support consistent, brand-aligned communication, our architecture
incorporates memory and secure identity protocols that enable individualized experiences over time. Our systems leverage client-approved
data to generate contextual, human-like responses, allowing each AI Agent to reflect the specific tone, knowledge, and requirements of
the customer’s organization.

10

Adaptive
Analytics Supporting Scalable Deployment.

We
believe our ability to train AI Agents on customer-specific data in an efficient and scalable manner supports rapid deployment across
enterprise environments. Our platform is designed to process large volumes of structured and unstructured data, enabling real-time insights
and operational support. We believe these capabilities allow our customers to improve decision-making, operational efficiency, and responsiveness.

Experienced
Management Team.

Our
management team brings experience across artificial intelligence, software, and enterprise systems. We believe this experience positions
us to execute on our strategy and navigate the evolving AI landscape.

Our
Growth Strategy

Customer
Acquisition Through Direct and Channel Partnerships.

We
aim to expand our customer base through a combination of direct sales efforts and strategic partnerships. We intend to continue forming
relationships with industry partners and regional collaborators to expand market access and support international growth initiatives,
including joint ventures and localized deployment strategies.

“Land
and Expand” Strategy.

We
seek to establish initial customer relationships through targeted deployments and expand these engagements over time by introducing additional
capabilities and use cases aligned with customer needs.

Product
and Vertical Expansion.

We
are developing a pipeline of enhancements and new capabilities designed to expand the range of use cases supported by our platform. As
we deepen our presence in existing verticals, we also intend to expand into adjacent industries.

Collaboration
with Academic and Research Institutions.

We
collaborate with universities and research institutions to support ongoing development of our technology and access to emerging talent
and innovation.

Collaboration
with Cataneo GmbH.

We
are continuing to collaborate with Cataneo GmbH on go-to-market efforts, particularly in international markets such as Mexico. These
efforts are focused on integrating capabilities and expanding distribution opportunities across media and enterprise environments.

Current
Target Verticals

Below
are summaries of key end-markets that we believe illustrate both immediate and long-term potential for our product offerings:

Healthcare

We
believe our platform can support healthcare organizations by reducing administrative burden, improving patient engagement, and enhancing
care coordination across fragmented systems. The healthcare industry includes more than 145,000 organizations across segments such as
outpatient care facilities, urgent care centers, physician groups, hospitals, and dental practices. These organizations often operate
across disparate systems, which can limit data interoperability and increase administrative complexity.

11

Healthcare
represents one of the largest sectors of the global economy, with U.S. healthcare spending exceeding $4 trillion annually⁷. Industry
research indicates that administrative inefficiencies account for a meaningful portion of healthcare spending, with some estimates suggesting
up to 25% of costs are associated with administrative complexity⁸.

We
believe our AI solutions can support patient education, care navigation, and adherence, while also assisting providers with administrative
workflows, intake processes, and communication.

Advertising
and Media

The
advertising industry continues to evolve toward more personalized and measurable engagement. The U.S. advertising market is projected
to reach approximately $569 billion by 2029⁹. Advertisers are increasingly focused on improving targeting, attribution, and consumer
engagement while addressing growing concerns around data privacy.

We
believe our AI solutions can enhance advertising effectiveness by enabling interactive, conversational experiences that move beyond passive
content toward measurable engagement.

Financial
Services

We
believe our AI solutions can support customer engagement, onboarding, and service delivery across financial services institutions. The
industry includes over 227,000 organizations spanning banking, credit intermediation, asset and wealth management, and insurance.

Global
financial services revenue exceeds $20 trillion annually¹⁰. Financial institutions operate in highly regulated environments
where trust, compliance, and data security are critical.

We
believe our platform can support secure customer interactions, onboarding workflows, and service delivery while enabling consistent and
compliant communication.

Government
and Data Sovereignty

We
believe there is growing demand for AI solutions that support data sovereignty, regulatory compliance, and secure deployment within government
and public sector environments.

Global
government IT spending is projected to exceed $600 billion annually¹¹.

We
believe our architecture positions us to support sovereign AI initiatives and public sector deployments.

Automotive

We
believe the automotive sector presents opportunities driven by increasing digitization of customer interactions and service operations.

Consumer
behavior continues to shift toward digital research and engagement prior to purchase, with industry research indicating that over 90%
of vehicle purchases begin with online research¹².

We
believe our AI solutions can support both customer-facing interactions and internal operational workflows across sales and service environments.

12

Illustrative
Offering Tiers

We
plan to offer our products across three primary deployment tiers, differentiated by level of integration, customization, scalability,
and data control, based on the needs of our enterprise customers.

Community
Cloud.

Designed for organizations requiring scalable infrastructure with standardized configurations. This tier leverages shared
cloud environments and supports efficient deployment for high-volume customer engagement use cases with defined customization options.

Private
Cloud.

Designed for organizations requiring enhanced control over infrastructure, data, and customization. This tier supports
more complex deployment environments, enabling greater flexibility, integration, and configuration while maintaining strong data governance.

On-Premises.

Designed for large enterprises with high concurrency requirements and strict data security and compliance needs. This tier provides
a fully isolated, ring-fenced deployment within the customer’s own infrastructure, enabling maximum control over data, systems,
and operations.

Commercial
Strategy, Customers, and Strategic Relationships

We
leverage a combination of direct sales efforts and strategic channel partnerships to drive customer acquisition and market expansion.
Our go-to-market approach is designed to support both direct enterprise adoption and localized deployment through commercial, licensing,
and strategic partner relationships. This approach enables us to expand into regulated and international markets while aligning our solutions
with region-specific customer needs, workflows, and compliance requirements.

During
2025, we announced and initiated commercial expansion activities across multiple regions and industry verticals. In Latin America, we
advanced our presence through partnerships involving SKYE LATAM and related initiatives, including Skye Salud, which is focused on healthcare
modernization opportunities in Mexico. These efforts support localized deployment, healthcare-focused use case development, and broader
market access in the region.

We
expanded our activities in Africa through collaborations with Valio Technologies and related regional initiatives, including institution-focused
deployment efforts. In hospitality, we entered guest-facing service environments through our collaboration with Seven Visions Resort
& Places, The Dvin, reflecting our broader strategy of deploying AI solutions in physical operating environments where engagement,
coordination, and service execution are critical.

In
the United States, we continued to deepen engagement with healthcare organizations while expanding into insurance through our strategic
partnership with Swiss Life Global Solutions. In advertising and media, we expanded reseller and deployment activity through Vybroo and
Grupo Siete, supporting interactive consumer engagement initiatives across Mexico and other international markets.

We
believe our customer base will primarily consist of enterprise and mid-market organizations, including healthcare providers, insurance
companies, financial institutions, hospitality operators, automotive service providers, and advertising and media platforms. We intend
to target partners and customers whose offerings can be enhanced through integration of our AI solutions.

Go-To-Market
Strategy

We
utilize a multi-channel go-to-market approach:

1. Partner
with industry-specific solution providers to access targeted verticals

2. Acquire
enterprise customers directly and through partners to establish market presence

3. Scale
through embedded deployments within partner platforms and service offerings

We
aim to expand our presence by leveraging partner distribution networks, existing customer relationships, and integrated solution offerings.
Our international growth strategy also includes working with regional collaborators and local operating partners to support deployment,
commercialization, and market-specific expansion.

13

Market
Opportunity and Demand Drivers

Demand
for enterprise artificial intelligence solutions continues to grow across industries as organizations seek to improve operational efficiency,
reduce costs, and enhance customer engagement. AI adoption is accelerating in sectors such as healthcare, financial services, and customer
experience, where organizations are increasingly deploying AI to support real-time interactions, automate workflows, and augment decision-making.

In
healthcare, rising patient demand, workforce shortages, and increasing administrative complexity are driving interest in AI-enabled engagement
and automation solutions¹⁶,¹⁷. In financial services and insurance, organizations are adopting AI to improve customer
experience, streamline operations, and support compliance and risk management functions¹⁸,¹⁹.

Across
industries, enterprises are increasingly prioritizing AI systems that can operate within secure, governed environments and integrate
directly with existing enterprise systems and workflows.

We
believe these trends support the expansion of our solutions across both digital and physical environments, including customer engagement,
service operations, and enterprise workflow automation.

Core
Strengths

Secure,
Enterprise-Grade Architecture

Our
platform is designed to operate within secure, closed-loop environments using organization-approved data, enabling deployment in regulated
and high-compliance industries such as healthcare, insurance, and financial services. We emphasize governance, auditability, and control,
supporting enterprise requirements for privacy, compliance, and operational integrity.

Configurable
and Customizable AI Systems

Our
AI solutions are highly configurable to meet the specific needs of enterprise customers. We support customization across interaction
design, workflows, integrations, and user experience, enabling organizations to tailor AI deployments to their operational environments,
customer populations, and business objectives.

Multimodal
Engagement Capabilities

Our
platform supports interaction across multiple modalities, including text, voice, and avatar-based interfaces. This enables deployment
across web, mobile, contact centers, kiosks, and embedded environments, supporting consistent engagement across digital and physical
touchpoints.

Integration
with Enterprise Systems and Workflows

Our
AI solutions are designed to integrate with enterprise systems, including customer relationship management (CRM), enterprise resource
planning (ERP), and other operational platforms. This enables our AI Agents to move beyond conversational interaction and support real-time
task execution, workflow automation, and decision support.

Data
Sovereignty and Controlled AI Environments

We
focus on enabling organizations to retain control over their data, AI behavior, and system outputs. Our architecture supports deployment
within controlled environments where data governance, residency, and regulatory compliance are critical, aligning with emerging enterprise
priorities around data sovereignty and secure AI deployment.

14

Competitive
Landscape

We
operate within a highly competitive and rapidly evolving artificial intelligence market. Our primary sources of competition include companies
developing conversational AI, language processing, and AI agent technologies, as well as industry-specific solution providers and large
technology platforms offering integrated AI capabilities.

The
AI ecosystem spans multiple layers, including applications, models, infrastructure, and supporting technologies. Competitors range from
specialized AI providers to large-scale technology companies incorporating AI into existing products and services.

Competitive
Factors

We
believe the principal competitive factors in our market include:

●
Accuracy and reliability of natural language processing and
understanding

●
Ability to support multimodal interactions across voice, text,
and visual interfaces

●
Flexibility of deployment across cloud, hybrid, and on-premises
environments

●
Speed and ease of implementation and integration

●
Degree of customization and adaptability to customer workflows

●
Ability to deliver personalized, context-aware interactions

●
Data security, privacy, and regulatory compliance

●
Strength of product development and innovation pipeline

●
Depth of industry-specific expertise

●
Scope and effectiveness of partner and distribution networks

●
Pricing structure and return on investment for customers

●
Strength of sales, marketing, and brand positioning

●
Existing customer relationships and adoption levels

●
Proven performance in complex, real-world environments

Additional
Development and Academic Collaborations

We
continue to invest in research and development initiatives to enhance our platform capabilities and expand into additional industry verticals.
We believe there are meaningful opportunities to extend our offerings into adjacent markets such as hospitality, enterprise services,
contact centers, and connected environments, supported by broader demand trends for enterprise artificial intelligence and automation
solutions¹³,¹⁴,¹⁵.

We
have engaged in academic collaboration efforts, including with Korea University, to support research and development initiatives and
advance certain technical capabilities of our platform. These collaborations are intended to supplement our internal development efforts
by providing access to research expertise, talent, and emerging technologies.

While
we maintain relationships with academic and research institutions, our development strategy has evolved to focus primarily on scalable,
enterprise-driven product development rather than reliance on any single research partnership.

Intellectual
Property

We
rely on a combination of patents, patent applications, registered and unregistered trademarks, copyrights, trade secrets, license agreements,
confidentiality procedures, non-disclosure agreements with third parties and other contractual measures, to protect our intellectual property
rights.

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As
of March 24, 2026, we have 23 issued patents, including 12 U.S. issued patents and 11 issued abroad. Our U.S. issued patents expire between
September 9, 2028, and April 1, 2044. We also have 24 pending patent applications, including 24 U.S. nonprovisional patent applications,
9 U.S. provisional patent applications, one Patent Cooperation Treaty patent application, and three patent applications in other jurisdictions.
The pending U.S. patent applications, if issued, would expire between 2041 and 2044. We continually review our development efforts to
assess the existence and patentability of new intellectual property.

We
control access to and use of our proprietary technology and other confidential information through the use of internal and external controls,
including contractual protections with employees, contractors, customers and partners. We also generally apply a policy requiring our
employees and independent contractors to sign agreements assigning to us any inventions, trade secrets, works of authorship, developments,
processes and other intellectual property generated by them on our behalf and under which they agree to protect our confidential information.
There are a number of risks associated with our patent rights and other intellectual property rights, including whether such rights
are valid, enforceable or sufficient to protect our business, products or services. See the section titled “Risk Factors-Risks
Related to Intellectual Property, Information Technology, Data Privacy and Security” for a more comprehensive description of
risks related to our intellectual property.

Regulation

We
operate under a complex and evolving landscape of data protection, privacy, cybersecurity, and artificial intelligence (“AI”)
governance regulations across multiple jurisdictions. While comprehensive AI-specific regulation remains in development, existing regulatory
frameworks applicable to our business continue to expand.

We
are subject to a variety of U.S. federal and state laws governing the privacy and security of personally identifiable information (“PII”),
including health information. In particular, the Health Insurance Portability and Accountability Act (“HIPAA”), as amended
by the Health Information Technology for Economic and Clinical Health Act (“HITECH”), establishes privacy and security standards
that limit the use and disclosure of protected health information (“PHI”) and requires the implementation of administrative,
physical, and technical safeguards.

In
addition to HIPAA, we may be subject to other federal and state privacy laws, including the California Consumer Privacy Act (“CCPA”),
as amended by the California Privacy Rights Act (“CPRA”), the Illinois Biometric Information Privacy Act (“BIPA”),
New York City Local Law 144, the Texas Data Privacy and Security Act (“TDPSA”), and the Virginia Consumer Data Protection
Act (“VCDPA”), among others.

Internationally,
we may be subject to additional data protection and privacy laws, including Mexico’s Federal Law on Protection of Personal Data
Held by Private Parties (“LFPDPPP”), South Africa’s Protection of Personal Information Act (“POPIA”), and
the General Data Protection Regulation (“GDPR”) in the European Union and European Economic Area.

We
maintain compliance with applicable healthcare and data protection regulations, including HIPAA, where required. We have also obtained
a Service Organization Control 2 (“SOC 2”) Type II report covering certain internal controls in the United States. While
SOC 2 Type II is not a legal requirement in all jurisdictions, it is widely recognized by enterprise customers as evidence of effective
security and operational controls.

In
certain jurisdictions, including Mexico and South Africa, we may also be subject to sector-specific regulatory oversight depending on
the nature of our deployments, including oversight by financial services and healthcare regulators.

We
also monitor and align with emerging governance frameworks, including standards published by the National Institute of Standards and
Technology (“NIST”) and international ISO standards, which address areas such as data processing, AI system governance, and
risk management.

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Employees

As
of December 31, 2025, we had approximately 29 full-time employees, including 2 executive officers. We also engage independent contractors
and consultants to support our operations. None of our employees are represented by a labor union, and we believe we maintain positive
employee relations.

Corporate
Information

Our
principal executive offices are located at 300 Delaware Avenue, Suite 210, Wilmington, Delaware 19801, and our telephone number is (307)
757-3650. Our website address is www.brandengagementnetwork.com. The information contained on, or that can be accessed through,
our website is not incorporated by reference into this Annual Report on Form 10-K and should not be considered part of this Annual Report
on Form 10-K.

Available
Information

We
file reports with the Securities and Exchange Commission (the “SEC”). The SEC maintains an Internet website at www.sec.gov
that contains reports, proxy and information statements, and other information regarding issuers that file electronically with the SEC.

Our
Annual Reports on Form 10-K, Quarterly Reports on Form 10-Q, Current Reports on Form 8-K, and any amendments to those reports filed or
furnished pursuant to Section 13(a) or 15(d) of the Securities Exchange Act of 1934 are available free of charge on our investor relations
website at https://investors.brandengagementnetwork.com as soon as reasonably practicable after we electronically file such material
with, or furnish it to, the SEC.

Legal
Proceedings

AFG
Litigation

On
January 16, 2025, the Company filed a lawsuit against AFG and its Chief Executive Officer, Ralph Wright Brewer III, in the Northern District
of Texas, Dallas Division alleging fraudulent misrepresentation, breach of contract, and the concealment of a ransomware attack on its
own network shortly before the Reseller Agreement was executed. Given that the litigation is not yet at issue, the Company is currently
unable to estimate the potential range of recoverable damages or the potential loss or range of loss, if any, resulting from a favorable
or unfavorable outcome.

On
March 26, 2025, the Company filed a First Amended Complaint against AFG in the Southern District of New York alleging breach of contract
against AFG with respect to the AFG Subscription Agreement. Specifically, the Company alleges that AFG failed to fund its required March
13, 2025 payment in the amount of $6,500,000. In the lawsuit, the Company seeks actual damages in the amount of the missed payment, pre-
and post-judgment of interest, consequential damages and attorneys’ fees and costs. It also seeks a declaration from the court
that AFG was and is obligated to purchase an aggregate of $6.5 million of additional shares of the Company’s Common Stock on each
of the first four anniversaries of the Initial Offering Closing Date and Business Combination Closing (as defined in the AFG Subscription
Agreement) pursuant to the AFG Subscription Agreement. On May 12, 2025, AFG filed an Answer and Counterclaims in which it denies the
allegations of the lawsuit and asserts counterclaims for an unspecified amount of damages against the Company. Given that the litigation
is not yet at issue, the Company is currently unable to estimate the potential range of recoverable damages or the potential loss or
range of loss, if any, resulting from a favorable or unfavorable outcome.

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Related
Party Investigation

The
Company’s management team assigned an advisor to the Board to conduct an internal investigation of potential related party transactions
with certain members of DHC Sponsor, LLC, prior to the merger with Brand Engagement Network, Inc. These matters are still under investigation.

From
time to time, we may become involved in legal proceedings or be subject to claims arising in the ordinary course of our business. Apart
from the foregoing, we are not presently a party to any other legal proceedings that we believe, if determined adversely to us, would
individually or taken together have a material adverse effect on our business, operating results, cash flows or financial condition.
Defending such proceedings is costly and can impose a significant burden on management and employees. The results of any current or future
litigation cannot be predicted with certainty, and regardless of the outcome, litigation can have an adverse impact on us because of
defense and settlement costs, diversion of management resources and other factors.

References
for Part 1.

1. https://www.statista.com/statistics/1552183/global-agentic-ai-market-value/

2. https://www2.deloitte.com/us/en/insights/industry/technology/technology-media-and-telecom-predictions/2025/autonomous-generative-ai-agents-still-under-development.html

3. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/

4. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-state-of-gen-ai-q4.pdf

5. https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-releases/state-of-generative-ai.html

6. https://www.gartner.com/en/executive-guidance/impact-of-personalization

7. https://www.cms.gov/data-research/statistics-trends-and-reports/national-health-expenditure-data

8. https://www2.deloitte.com/us/en/insights/industry/health-care/cost-of-health-care-in-the-united-states.html

9. https://www.statista.com/outlook/amo/advertising/united-states

10. https://www.statista.com/outlook/dmo/fintech/worldwide

11. https://www.gartner.com/en/newsroom/press-releases/2024-01-17-gartner-says-worldwide-government-it-spending-to-total-588-billion-in-2024

12. https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/the-future-of-car-sales

13. https://www.statista.com/outlook/tmo/artificial-intelligence/worldwide

14. https://www.idc.com/getdoc.jsp?containerId=prUS50528223

15. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

16. https://www.aha.org/workforce

17. https://www.mckinsey.com/industries/healthcare/our-insights

18. https://www2.deloitte.com/us/en/insights/focus/cognitive-technologies/ai-financial-services.html

19. https://www.mckinsey.com/industries/financial-services/our-insights

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