NASDAQ: MBLY

Company Overview

Mobileye is a leader in the development and deployment of advanced driver assistance systems (“ADAS”) and autonomous driving technologies and solutions. We pioneered ADAS technology more than 25 years ago and have continuously expanded the scope of our ADAS offerings, while leading the evolution to autonomous driving solutions. On February 3, 2026, we completed the acquisition of Mentee Robotics Ltd. (“Mentee Robotics”), a humanoid robotics company. This acquisition combines Mobileye’s advanced artificial intelligence (“AI”) technology and global production expertise with Mentee Robotics’ breakthrough humanoid platform and deep AI talent, creating a comprehensive provider of Physical AI technology across two transformative markets: autonomous driving and humanoid robotics.

Our portfolio of solutions is built upon a comprehensive suite of purpose-built software and hardware technologies designed to provide the capabilities needed to make the future of ADAS and autonomous driving a reality. These technologies can be harnessed to deliver mission-critical capabilities at the edge and in the cloud, advancing the safety of road users, and revolutionizing the driving experience and the movement of people and goods globally.

While today ADAS is central to the advancement of automotive safety, we believe that an evolutionary path toward fully autonomous vehicles is the future of mobility. While still nascent, full autonomy - where a human is not actively engaged in driving the vehicle for extended periods of time - requires the autonomous driving solution to be capable of navigating any environment in any condition at any time. The ability to drive autonomously not only requires a substantial amount of data, but also a robust technology platform that optimizes both precision (i.e., safety) and recall (i.e., availability) without compromise, and can withstand the validation and audit process of global regulatory bodies. Further, the autonomous driving solution needs to be produced at a cost that makes it affordable. We are building our technology platform to address these fundamental and significant challenges in order to enable a full spectrum of solutions, from ADAS to autonomous driving, with multiple products in between to best serve the needs of our customers.

We believe that our industry-leading technology platform, built upon over 25 years of research, development, data collection and validation, and purpose-built software and hardware design, gives us a differentiated ability to not only deliver excellent safety ratings and maintain a leadership position with our ADAS solutions, but also to make the mass deployment of autonomous driving solutions a reality. We also believe that the breadth of our solutions, combined with our global customer base, represents a significant market opportunity for us. Our platform is efficient and modular by design, enabling our customers to productize our most advanced solutions today and then leverage those investments to launch even more advanced systems in a modular and incremental manner. Our solutions are also highly customizable, which allows our customers to benefit from the core technology supporting our advanced solutions while also augmenting and differentiating their offerings.

We have experienced significant growth since our founding. For 2025, 2024 and 2023, our revenue was $1.9 billion, $1.7 billion and $2.1 billion, respectively, representing a year-over-year increase of 15% in 2025 compared to 2024. We currently derive substantially all of our revenue from our commercially deployed ADAS solutions. We recorded net losses of $392 million, $3,090 million and $27 million in 2025, 2024 and 2023, respectively, with the net loss in 2024 primarily being the result of recording a $2,695 million non-cash impairment of goodwill in the third quarter of 2024. Our Adjusted Net Income (Loss) for 2025, 2024 and 2023 was $286 million, $205 million and $659 million, respectively. Adjusted Net Income (Loss) is a non-GAAP financial measure; see “Item 7. Management’s Discussion and Analysis of Financial Condition and Results of Operations – Non-GAAP Financial Measures” for a reconciliation of Adjusted Net Income (Loss) to Net Income (Loss). The adjustments to reconcile Net Income (Loss) with Adjusted Net

Income (Loss) are related to amortization of intangible assets, stock-based compensation expenses, impairment of goodwill and related income tax effects where applicable.

As of December 27, 2025, our solutions have been installed in approximately 1,400 vehicle models (including local country, year, and other vehicle model variations), and our System-on-Chips (“SoCs”) have been deployed in more than 230 million vehicles. We are actively working with more than 50 Original Equipment Manufacturers (“OEMs”) worldwide on the implementation of our ADAS solutions. For the year ended December 27, 2025, we shipped approximately 35.7 million of our EyeQ™ SoC and SuperVision™ systems, of which the substantial majority were EyeQ™ SoCs. This represents an increase from approximately 29.0 million systems that we shipped in 2024.

We were founded in Israel in 1999. Our co-founder, Professor Amnon Shashua, is our President and Chief Executive Officer. In 2014, we completed an initial public offering as a foreign private issuer and traded under the symbol MBLY on the New York Stock Exchange. Intel Corporation (“Intel”) acquired Mobileye for $15.3 billion in 2017, after which we became a wholly-owned subsidiary of Intel. We completed the internal reorganization and design of our new public entity (the “Reorganization”) and the Mobileye IPO in October 2022.

Our Technology Platform is Built to Enable the Full-Stack of Autonomous Solutions

Our technology platform, which includes our software and hardware intellectual property, leverages our decades of experience as a technology leader for sensing and perception solutions for the automotive industry and our focused efforts to build highly scalable, compute-efficient and cost-efficient autonomous solutions. Our technologies are foundational to the development and deployment of our ADAS and AV capabilities. Our platform is built on five fundamental pillars:

●Computer Vision Processing. Mobileye’s history as a cutting-edge deployer of AI-based solutions in the real world starts with our expertise in computer vision processing. ADAS solutions are responsible for saving lives and must meet very high-performance metrics with extreme levels of efficiency, as well as pass increasing oversight from regulatory bodies. The precision requirements for advanced solutions in the Premium ADAS and AV segments are even more exacting. We are a technology leader for computer vision technology for ADAS, largely through front camera solutions, and we have continuously enhanced our leadership position through our ability to meet the extreme performance, accuracy, and cost metrics of our OEM customers. In recent years, we have expanded our capability to enable creation of a 360-degree worldview through the processing of multiple cameras placed around the vehicle to support our portfolio of advanced solutions. Our products primarily use monocular camera processing that works accurately alone, or together with radar and lidar for redundancy. The software supporting camera processing is diverse, including end-to-end neural network processing (both 2- and 3-dimensional) and model-based techniques, among other approaches, this compound AI system structure leads to internal redundancies within the camera-based perception system that enhances precision through design. We have been responsible for many “industry first” launches using monocular vision processing, and have enhanced our computer vision capabilities over time to include multiple cameras such as the trifocal camera configuration (three cameras with different fields of view placed side-by-side facing forward), which has been in series production since 2018, and the 11-camera configuration on our Mobileye SuperVision™ solution, which was launched in late 2021.

●Road Experience Management™. Our Road Experience Management™ (“REM™”) technology generates high-precision maps to support advanced ADAS and autonomous vehicle systems from crowd-sourced data that is uploaded and analyzed in the cloud from REM™-equipped production ADAS solutions deployed on vehicles on the road. REM™ is a cloud-based system that leverages the broad installed-base of REM™-equipped vehicles to build Mobileye Roadbook™, our crowd-sourced, high-precision definition maps of roads from around the world. Our REM™ mapping system harvests small packets of Road Segment Data from various vehicle models produced by our partner OEMs that are equipped with special processing software that extracts only the relevant information necessary to support increasing levels of ADAS and autonomous driving. In 2025 alone, we collected 34.5 billion miles of road data from, based on our estimates, over 8 million REM™-enabled vehicles worldwide. The Road Segment Data is uploaded to the cloud where our software automatically creates and updates a detailed and accurate model of the road. Our REM™ mapping system seamlessly creates high-precision maps from such Road Segment Data in the cloud at centimeter-level detail, which are then delivered to the edge and integrated with our computer vision engines to provide vehicles with real-time intelligence, including situational awareness, context, and foresight. Mobileye Roadbook™ was designed to provide the driving solution with a pre-aggregated representation of relevant static and slowly changing elements of the environment (road geometry, boundaries, and semantics) and temporary events such as construction zones and road debris, at a high refresh rate.

●Compound Artificial Intelligence Systems, including True Redundancy™. Our Compound AI structure supports precision, recall, and overall efficiency by design. While recent advancements in transformer-based architectures and Generative AI create efficiencies in learning-based systems, which Mobileye makes full use of, it also introduces shortfalls such as lack of abstraction, shortcut-learning problem, alignment issues (i.e., learning from common but incorrect data), and the long-tail problem (i.e., identifying and fixing edge cases one by one). This approach is inevitably intended to drive high recall at the expense of precision. This inherently introduces significant risk when it comes to the complexity of real-world driving scenarios. Our solution, which aligns with the latest developments in Generative AI even in non safety-critical applications includes insertion of abstractions and an architecture with multiple levels of redundancies that support a quadratic improvement in precision through design. Insertion of abstractions can successfully convert large sets of out-of-distribution edge cases to in-distribution without the need for iterative network re-training with more and more data. Additionally, our structure includes redundancies within the computer vision stack, the fusion of mapping with real-time perception, the fusion of decomposable and end-to-end architectures, and True Redundancy™ - the fusion of independent world-views produced by separate vision and radar/lidar-based subsystems. Finally, our newest innovations include simulation training of driving policy through artificial community intelligence. This innovation enables reinforcement learning based training of driving policy in a simulated environment that achieves extraordinary amount of training hours overnight and addresses the issue of nearly infinite sample complexity when training driving policy.

When it comes to safety, our multi-faceted high-level fusion structure is governed by a Primary / Guardian / Fallback methodology (“PGF”) which can handle “majority-rule” as well as non-binary discrepancies. This technology approach supports a quadratic improvement in precision through a framework in which the system only fails if two subsystems fail concurrently. It is a critical enabler of our goal of building a fully autonomous driving-system that can be validated as safer than human-driven vehicles, devoid of unreasonable risks, and deployed in a cost-efficient manner. This approach separates our system from competitors that utilize a monolithic approach.

●Next Generation Imaging Radars. A solution targeted to complement the camera-based system with a sensor that has almost fully independent failure modes, supports high precision and to reduce the need for multiple expensive lidar sensors, supports cost-efficiency, a major component of recall. The in-house development of imaging radar is a key enabler of our goal of building a cost-effective fully autonomous driving-system. Our radar is expected to deliver rich point-cloud models like those customary of lidar, with far higher resolution and significantly more dynamic range than traditional radar. During 2024, these goals were validated through widespread testing of our B-sample hardware by a number of OEMs. These radars differ from legacy radar and other imaging radar development as they are backed by advanced processing algorithms and can enable an independent “sensing state” with independent failure modes unlike the camera-based system which supports a quadratic improvement in mean-time-between failure. Our choice to focus on the evolution of the radar modality is also related to its cost structure which is significantly below lidar sensors. We believe our custom designed imaging radars address not only the performance, but also the cost limitations of lidar-centric solutions for mass AV deployment. We have selected multiple manufacturers for this solution which is approaching start of production.

During 2025, a leading global automaker chose Mobileye Imaging Radar™ as a key component of its upcoming eyes-off, hands-off automated driving system in personal vehicles, following an extensive, years-long evaluation of Mobileye’s technology and competing systems. Starting in 2028, this new customer for Mobileye plans to use the imaging radar to deliver SAE Level 3 automated driving at highway speeds, designed to provide exceptional detection of vehicles, people and objects in conditions such as fog or rain, and at long distances, that challenge existing sensors.

●Our Family of Purpose-Built EyeQ™ SOCs. Fundamental to our leadership position in ADAS and our ambitions to develop the most cost-efficient, high-performing AV solutions, our EyeQ™ SoCs incorporate a set of proprietary compute-acceleration models to enhance the accuracy, quality, and functional safety of our perception solutions, while minimizing the power consumption to address the requirements of the automotive market. The EyeQ™ family design also enables a scalable Electronic Control Unit (“ECU”) architecture, thereby supporting a variety of ADAS and autonomous vehicle solution architectures that meet the functional safety requirements of our customers. These solutions range from base, windshield mounted ECUs to multi-SoC central compute ECUs

supported currently by EyeQ™5 High and in the near future EyeQ™6 High, which can be deployed in a scalable way to support a full suite of Premium ADAS and AV solutions.

The efficiency of our inference silicon design is a core enabler of the overall efficiency of our system, and is critical in applications such as automotive application which highly value packaging size and power consumption. Designing an efficient silicon architecture requires optimizing the competing factors of efficiency and flexibility. We accomplish this through the development a variety of accelerators, each of which are designed to perform specific tasks that either most favor efficiency, flexibility, or a combination of both. Successful design has led to a 10-times improvement in frames-per-second processing for EyeQ™6 High, as compared to EyeQ™5 High, despite only double the headline processing power (i.e., TOPS) and 25% higher power consumption. Based on competitive benchmarking, the EyeQ™6 High is significantly more efficient than more general purpose SoC’s that are much higher headline processing power, in terms of frames-per-second, latency, and cost. We continue to believe that, as AV solutions continue to develop, efficiency of inference silicon will be one of the most significant purchasing criteria and Mobileye has inherent advantages in this area.

Our EyeQ™5 SoCs and subsequent generations are increasingly customizable by our OEM customers, supported by our Driving Experience Platform (“DXP”). DXP is a software platform that enables automakers to develop and customize the driving experience (i.e., the OEM-unique aspect of a vehicle’s automated driving features) while utilizing Mobileye’s proven core technology perception and driving policy software (i.e., the objective, universal aspects of a vehicle’s automated driving features). This new application programming interface supports our customers’ desire to create unique products from our technology while also accelerating time-to-market and reducing overall execution risk. Importantly, this collaborative addition to our platform offers a mutually beneficial middle ground between open and closed systems which we believe is the optimal path forward.

These five pillars form the core of our highly versatile and customizable platform, which we intend to deploy with progressively increasing functionality to continue to enhance our market-leading ADAS solutions and lead the evolution to autonomous driving solutions.

The Autonomous Vehicle Revolution

Autonomous driving is one of the most difficult technological challenges facing the world today, but as a technological concept has remained at the forefront of human imagination for decades. Since the early 2000s, a number of automotive and technology companies have invested heavily to try to make this a reality. Mobileye’s vision for the last number of years is to chart a clear path from ADAS to scalable autonomous driving.

Vehicle autonomy can be viewed as a spectrum that uses the same technology building blocks to power the full span of driver assist functions, ranging from those available in hundreds of car models today, through full autonomy powering robotaxis and, eventually, personal autonomous vehicles. The automotive industry breaks down this spectrum into what are known as SAE Levels 1, 2, 3, 4 and 5. We have developed our own, more user-friendly taxonomy. Each level of our taxonomy is further defined and supported by the particular operational design domain (“ODD”) for which it was designed.

First, we refer to basic driver assist features, such as automatic emergency braking or lane keeping assist, together with longitudinal control such as adaptive cruise control as “eyes-on/hands-on”. The driver is still responsible for the overall task of driving, while the system supports the human driver.

Second, “eyes-on/hands-off”. This refers to premium driver assist functions adding additional safety and comfort functionality. This functionality allows the driver to experience hands-free driving while requiring the driver’s full attention and eyes on the road.

Third, “eyes-off/hands-off”. The system controls the driving function within a specified ODD, such as highway driving, without the need for the human driver to monitor driving. If the ODD is exceeded and the driver does not reassume control, the system is capable of performing a Minimum Risk Maneuver (“MRM”) and safely stop at the roadside.

Fourth, “no driver”. When no human driver is present, e.g., a robotaxi, the system will perform a MRM when needed, including coming to a full stop, and can also contact a teleoperator for decision support, such as re-routing and rules decisions.

We see a parallel path developing with significant growth in the adoption of cost-efficient eyes-on/hands-off systems on specified road types across a variety of price segments. On the other side of the spectrum, with the advent of commercial driverless services in 2024 and 2025 in the United States, we believe that the future state and growth of fully autonomous vehicles deployed in cities by fleet operators is no longer a question of technology, but rather of business model and scalability.

We believe that growth in eyes-on/hands-off systems and commercial driverless services will enhance public trust and familiarity with the technology to grow and eventually lead to more sophisticated self-driving systems for privately-owned vehicles. Our ADAS solutions, which have been deployed in over 230 million vehicles, are important building blocks for these more advanced autonomous systems. We believe the key factors in the growth of autonomous driving will be increased safety, consumer demand, and other economic and social benefits, such as increased mobility for older adults and persons with disabilities, less traffic congestion, and the reduction of land use for parking.

Our Solutions

We have utilized the technology pillars detailed above to build a robust portfolio of end-to-end ADAS and autonomous driving solutions that provide the capabilities needed for the future of autonomous driving, leveraging a comprehensive suite of purpose-built software and hardware technologies. We pioneered “base” ADAS features to meet global regulatory requirements and safety ratings with our Base ADAS solution and we have since created new categories of ADAS with our Cloud-Enhanced ADAS™, Mobileye Surround ADAS™, and SuperVision™ offerings. Additionally, we have designed a full set of eyes-off/hands-off solutions at a wide variety of price points and a spectrum of functionalities and ODDs.

We believe that our industry-leading technology platform, built upon multiple years of research, development, data collection and validation, gives us the unique ability to not only deliver excellent safety ratings with our ADAS solutions, but also to make the mass deployment of autonomous driving solutions a reality. We believe that the breadth of our solutions, combined with our global customer base, represents a significant market opportunity for us.

The chart above represents commercially deployed solutions (Base ADAS, Cloud-Enhanced ADAS™ and Mobileye SuperVision™) and solutions that we expect to be commercially deployed in the future (Mobileye Surround ADAS™, Mobileye Chauffeur™, and Mobileye Drive™).

Our End-to-End ADAS and AV Solutions

Mobileye Base ADAS

Mobileye’s Base ADAS, powered by our purpose built, on-windshield EyeQ™ SoC devices and our expertise in computer vision, brings our core ADAS solutions to millions of vehicles on the road today and is foundational to our spectrum of ADAS and autonomous vehicle solutions. Our EyeQ™ SoC provides drivers with basic safety features covered by front-facing sensing, such as collision warning, lane departure warnings, pedestrian and cyclist collision warning, headway monitoring and warning, speed limit indicator, blind spot detection, and many more. Our software algorithms and purpose-built hardware are designed to provide the driver with accurate and reliable driver assist solutions, promoting road safety.

Cloud-Enhanced ADAS™

Mobileye’s Cloud-Enhanced ADAS™ leverages crowdsourced data from millions of REM™-equipped vehicles around the globe every day, providing high-level accuracy localization via continuously updated information about the driving scene. Enhancing the existing single-camera system with crowd-sourced data offers comprehensive in-path assist functionality that enables better performance and compliance even in complex or challenging circumstances. Relying on data from prior human driving activity to anticipate and adapt, our Cloud-Enhanced ADAS™ solution provides a safer, smoother, and more natural driving experience – marking a software defined leap in ADAS performance with no need for additional hardware.

Mobileye Surround ADAS™

Building on our ADAS expertise and the core of our single-camera Cloud-Enhanced ADAS™ system, we offer through our Mobileye Surround ADAS™ system the ability to meet expanded late-decade active safety requirements through the utilization, analysis, and processing of additional surround perception sensors. Mobileye Surround ADAS™ utilizes the SuperVision™ software stack, including our RSS (defined below) policy model, and is powered by an ECU with one EyeQ™6 High SoC, which processes data from the customer’s third-party sensor suite featuring up to six cameras and up to five radars. Such cameras generally consist of two long-range cameras in the front and rear, while leveraging data from four short-range surround vision cameras that are already equipped on many production vehicles today for parking visualization purposes. Additionally, Mobileye Surround ADAS™ offers eyes-on/hands-off functionality for highway ODDs by adding features like automatic lane change, front and rear collision avoidance, traffic jam assist, and a Highway Pilot function up to 130 kilometers per hour with the fidelity of a multi-camera and multi-radar sensor suite. This system also includes DXP support, which enables customers to customize the driving experience while benefiting from our industry-leading technology platform.

Mobileye SuperVision™

Mobileye SuperVision™, our eyes-on/hands-off Premium Driver Assist offering, is our most advanced driver assist system on the market and is the bridge to consumer autonomous vehicles. It is designed to handle standard driving functions across various road types, offering “hands-off” navigation capabilities under certain ODDs, while still requiring the driver to pay full attention and keep eyes on the road. Derived from our autonomous vehicle research and development, Mobileye SuperVision™ leverages cloud-based enhancements such as REM™, a number of algorithmic and architectural redundancies, and our RSS policy model. The system utilizes 360-degree surround sensing with 11 third-party cameras powered (plus optional radar) processes by a turnkey ECU with two EyeQ™5 or, starting with expected launches in 2027, two EyeQ™6 SoCs. Furthermore, in addition to supervised point-to-point assisted driving, Mobileye SuperVision™ is capable of changing lanes, managing priorities, and turning in intersections as well as engaging in automated parking, preventative (i.e., evasive) steering and braking, and other Driver Assist features. This solution is further supported by OTA updates. The 11 third-party cameras (seven long range cameras and four short-range surround vision cameras) provide full surround coverage and consist of 120-degree and 28-degree cameras in the front, four 100-degree corner cameras (two front-facing and two rear-facing), a 60-degree rear camera and four wide-view 195-degree short-range cameras mounted on the side mirrors and front and rear bumpers. The mapping is powered by REM™, and integrated with computer vision perception, to create a 360-degree environmental model (subject to the availability of map data) and RSS constrains the driving decisions to be compliant with an underlying formally proven model for safe driving decisions. This offering also includes DXP, which will enable customers to control the driving experience while benefiting from our industry-leading technology platform.

Importantly, our SuperVision™ technology also serves as a bridge, or foundational technology, for Mobileye and its customers to develop a spectrum of eyes-off/hands-off solutions with expanding ODDs. In other words, an OEM that adopts and validates SuperVision™ is taking a significant step towards consumer AV as SuperVision™ serves as a validated baseline, including a common primary ECU board, which can be leveraged to add eyes-off functionality under an increasing set of operating conditions in a modular way.

The first series production launch of this offering occurred in 2021 as Geely Group launched Mobileye SuperVision™ in its ZEEKR premium electric vehicle brand. Through the end of 2025, over 350,000 SuperVision™ systems were delivered to ZEEKR, Polestar and other brands.

Mobileye Chauffeur™ and Mobileye Drive™

Mobileye Chauffeur™ is our geographically scalable eyes-off/hands-off solution for consumer vehicles in a gradually expanding ODD, combining computer vision technology with surround imaging radars and front lidar. The first generation solution will be based on three EyeQ™6 High SoCs, deployed with a primary board including two EyeQ™6 High SoCs supporting full surround computer vision perception and mapping and a secondary board with an additional EyeQ™6 High SoC supporting radar / lidar perception and our Compound AI fusion architecture. The primary board is common to our SuperVision™ solution which reduces the OEM’s validation burden and the dual-board setup provides functional safety redundancy. The system will provide 360-degrees of coverage through two independent and redundant sensing subsystems, along with REM™ maps, RSS, and our PGF architecture, to support optimized scalability and safety. Mobileye Chauffeur™ is expected to be capable of eyes-off/hands-off driving with a human driver still in the driver’s seat, in a gradually expanding ODD that can range from a limited ODD (e.g., highway only, up to 130kph), an ODD that we believe covers the majority of most consumers’ driving, to the more advanced ODDs that we are pursuing through this solution in subsequent generations. By using Mobileye SuperVision™ eyes-on/hands-off system as a basis for Mobileye Chauffeur™, we allow for an incremental and modular eyes-off transition from one ODD to the next. This can be done by adding more active sensors for redundancy and more compute power to the already validated and road-tested Mobileye SuperVision™. This approach gives our customers a viable, modular, and incremental path toward useful and safe consumer AV solutions.

Mobileye Drive™ is our fleet-focused end-to-end self-driving system that enables automakers, public transportation companies, and transportation network operators to offer a no-driver solution for robotaxis, ride-pooling, public transport, and goods delivery. This eyes-off/hands-off/no driver solution will build upon our core autonomous driving technologies found in Mobileye Chauffeur™ and will deliver driving functions without the need for any in-vehicle human intervention by adding teleoperability and by minimizing cases where human input would be required. Our overall turnkey self-driving solution offers an advanced ODD that can turn various vehicle configurations and solutions autonomous. Mobileye Drive™ is already being integrated, and is in the development, testing and validation stages in autonomous public transit, autonomous goods delivery and autonomous mobility-as-a-service (“AMaaS”) across industries and around the globe.

We believe that both Mobileye Chauffeur™ and Mobileye Drive™ have sustainable competitive advantages as a result of the cost efficiency, scalability, and regulatory validation of our technology platform:

●Cost Efficiency - cost-efficient, low-energy, purpose-built central compute processors; imaging radars targeted to reduce the need for multiple lidar units;

●Geographic Scalability - REM™-based maps that eliminate the need for dedicated high-definition mapping efforts; RSS-based driving policy designed for global deployment by not relying on driving culture or local rules; sensing technologies built on a foundation of a massive data training set from over 40 countries; and

●Regulatory Validation - True Redundancy™, with multiple independent, separate perception subsystems feeding our Compound AI architecture that increases robustness and ease of validation, and RSS used by international bodies that are currently developing standards with respect to the safety of AV.

●Self-Driving System & Vehicles. We expect to deploy our Mobileye Drive™ eyes-off/hands-off self-driving system inside purpose-built vehicle platforms that are engineered to integrate our technology stack. Announced supply-side vehicle development partners are Volkswagen Commercial Vehicles and MOIA, Schaeffler, Verne and Holon. We and our vehicle development partners will then market these vehicles and systems through business-to-business channels into a range of transportation network operators, with announced demand-side customers including Deutsche Bahn, Beep, Holo / Ruter, Lyft and others.

Overall, we believe our proprietary set of software and hardware technology solutions results in significant competitive advantages and a wider range of potential offerings compared to other approaches by industry participants attempting to commercialize network-deployed autonomous vehicles.

Models for AV Adoption

We believe that the availability of autonomous vehicles will cause a significant transformation in mobility, including vehicle ownership and utilization. We expect that autonomous vehicle technology will eventually be accessed by consumers through shared-vehicle AMaaS networks, as well as in consumer-owned and operated autonomous vehicles. It is our view that, to reach the full potential of autonomous driving over the long-term, the technology solutions that enable these separate markets should converge over time, and that is reflected in our strategy.

Autonomous driving has the potential to dramatically increase the proliferation of shared mobility, creating greater utilization of what is currently a significantly underutilized asset, the car. We believe that this model will ultimately manifest itself in the form of networks operated by a variety of different automotive and technology companies, where the consumer will be able to hail on-demand transportation at the click of a button, instead of owning a vehicle.

In addition, we believe consumer-owned and operated AVs will fundamentally change how individuals utilize their vehicles. Automation will allow the individual to be significantly more productive during their commute or other time spent in the car, given that the vehicle could operate eyes-off/hands-off in an increasingly wide ODD. Providing consumers with access to affordable autonomous vehicles can create significant value by decreasing time spent focused on the driving function and increasing safety.

As autonomous driving technology advances, a number of new transportation use cases are expected to emerge around the type of vehicle ownership, what is transported, and where and when the vehicle can operate. We believe that the most important factors in operating AMaaS networks will be the technology that powers the vehicles, as well as the scale of the network which will influence the availability of vehicles. As fleet operators increase network scale and availability of vehicles, the value of the platform to the user base will rise. We believe that mobility supply is developing in two main segments - automated public transport operators and automated transportation network companies - with very few companies able to operate within both over the long-term. It is our view that a flexible solution that supports both consumer AVs and AMaaS will be necessary to reach the full potential of autonomous driving over the long-term.

Challenges to Making Autonomous Vehicles Ubiquitous

To make autonomous vehicles at scale a reality, we believe that there are three core challenges that must be addressed beyond optimization of safety and performance:

●Regulatory Endorsement - Autonomous driving solutions must be architected, by design, to be verifiably safe, in a manner that fosters broad societal and regulatory endorsement. Regulation is an often-overlooked factor. While laws and regulations are specific to human drivers, there are challenges to balance safety and practicality of an AV in a manner that is acceptable to society. We believe it will be easier to develop laws and regulations governing a fleet of robotaxis than privately owned vehicles. A fleet operator would receive a limited license per use case, per geographic region and will be subject to extensive reporting and back-office remote operations. In contrast, licensing AVs to consumers would require a complete overhaul of the complex laws and regulations that currently govern drivers. Autonomy must wait until regulation and technology reach an equilibrium, which we believe will first be achieved through AMaaS deployments. Self-driving regulation is inherently complicated, and driving policy depends on “what would happen next” reasoning, which is not factual. Two humans might provide two different answers when asked whether an AV should yield to a car at an intersection or take the right of way. As a result, there is no clear definition of “error,” but rather, it is open to interpretation or depends on after-the-fact judgment. All motor vehicle drivers owe a duty of care to other road users, and autonomous vehicles will need to be held to the same standard. Statistically, autonomous vehicles should be safer than human drivers. For driving policy, however, being “safer” does not always mean being better. As a society, we balance safety and practicality by determining what the “reasonable risk” we are willing to take is, and this is the type of question regulators will be required to address when licensing autonomous vehicles to navigate our roads.

●Geographic Scale - Geographic scale refers to the challenge of creating high-definition maps with great detail and accuracy through our REM™ technology, and keeping those maps continuously updated, which is crucial for series production AVs. AMaaS vehicles can be confined to geofenced areas, which allows AVs to reach prominence through the robotaxi industry before expanding the ODD to outside of those areas. While robotaxi operators may be successful providing their services in limited geofenced areas, broad-based consumer AV adoption requires the ability to drive safely anywhere, and in diverse environments, rather than only in geofenced areas. In 2025 alone, we collected 34.5 billion miles of road data from, based on our estimates, over 8 million REM™-enabled vehicles worldwide, and analyzed up to 94.5 million miles of road data per day, with the size of the REM™-enabled fleet increasing daily. Since we deployed REM™ in 2018, we have harvested a total of 91.5 billion miles of road data. As of December 27, 2025, we estimate that the data we have accumulated covers over 95% of the approximately 0.8 million miles of motorway, trunk, and primary road types in each of the United States and Europe, respectively, as well as a large majority of other road types. This data enables us to create robust high-definition maps to support solutions across the product spectrum from Cloud-Enhanced ADAS™ to Mobileye Surround ADAS™ and Mobileye SuperVision™ to Mobileye Chauffeur™ and Mobileye Drive™.

●Cost - The cost of a self-driving system commonly employed by robotaxis, with its cameras, radars, specialized lidars, and high-performance computing is currently in the tens of thousands of dollars. This cost level is acceptable for the monetization model of a driverless ride-hailing service, but is far too expensive for series-production passenger cars. In order for autonomous driving consumer vehicles to scale in volume, we believe the cost of self-driving systems needs to be reduced significantly, such as to several thousands of dollars, an order of magnitude lower than the cost of market solutions to date. The ability to scale at low-cost, both from the on-board technology perspective and the cost of mapping, is critical to the mass adoption of AVs. AVs need to be safe, yet affordable, to achieve adoption among individuals and not just fleet operators.

Our Competitive Strengths

We believe that our leadership in ADAS and autonomous driving is based primarily on our: (1) first-mover advantage; (2) technology, including differentiated technological cores and solution architectures; (3) comprehensive portfolio of solutions; (4) delivery, including agility, response times, and time-to-market; and (5) inherent cost-driven advantages. These significant advantages form the basis for our competitive strengths described below:

●Coupling of software and hardware delivers optimized performance and efficiency - We design our own purpose-built SoCs and develop a software stack to optimally match the architecture of the SoCs. This results in an optimized cost/performance paradigm, allowing for a range of products that can be produced at high volume. We continue to innovate in this area; for example, our latest SoC, the EyeQ™6 High, achieves a ten-fold increase in frames-per-second processing as compared to our EyeQ™5 High SoC, with only a two-times increase in overall processing power and 25% increase in power consumption. Our coupled software and hardware architecture is highly differentiated from general purpose SoCs and software stacks that are not optimized for a specific use case. Our

approach results in low power consumption and lean compute, and yet, is able to support a very powerful range of solutions for the ADAS and AV markets. The principle of efficiency permeates the overall solution design, including our Compound AI system architecture, which includes our True Redundancy™ approach, with multiple separate subsystems to increase robustness and simplify validation efforts, and RSS, which separates the perception system’s validation from the driving policy system, and allows for a compute-efficient driving policy. Each of these are critical contributors to achieving efficient solutions.

●Scalable EyeQ™ SoC design addresses the entire spectrum of ADAS and autonomous driving - Our proprietary accelerator cores are optimized for a wide variety of computer vision, signal processing, and machine learning tasks, including deep neural networks. Our EyeQ™ architecture is highly scalable, powers our solutions, ranging from our base ADAS to highly advanced autonomous driving solutions, and is designed to support the increasingly computationally intensive demands of ADAS and autonomous driving solutions on the same architecture.

●Industry leading computer vision capabilities - ADAS solutions are responsible for saving lives and must meet very high-performance metrics with extreme levels of efficiency, and pass increasing regulatory oversight. We are a technology leader for computer vision solutions for ADAS, and we have continuously enhanced our leadership position through our ability to meet the extreme performance, accuracy, and cost metrics of our OEM customers. Our products primarily use monocular camera processing that works accurately alone, or together with radar and lidar for redundancy. We have been responsible for many “industry first” launches using monocular vision processing. These include forward collision warning, automatic emergency braking, pedestrian detection, hands-free driving, and numerous other advanced functions based solely on computer vision. We have pioneered many computer vision features such as deep networks for the discovery of “free space” or the space available to the vehicle to drive in, so that a vehicle can determine a driving path. We have enhanced our computer vision capabilities over time to include multiple cameras such as the trifocal camera configuration (three cameras with different fields of view placed side-by-side facing forward), which has been in series production since 2018, and the 11-camera configuration on our Mobileye SuperVision™ solution, which was launched in late 2021.

●We offer solutions for developing and deploying differentiated features on top of EyeQ™ SoC - Our platform is modular by design, enabling our customers to productize our most advanced solutions today and then leverage those investments to launch even more advanced systems in a modular and incremental manner. Our systems are also highly customizable, which allows our customers to benefit from our cutting-edge, verified, and validated core technologies such as computer vision, radar, and lidar processing, Compound AI system architecture (including True Redundancy™), REM™ mapping, and driving policy, while enabling our customers to augment and differentiate their offerings. Customization on top of these core technologies comes primarily through Mobileye DXP, which is a software platform that enables automakers to build from Mobileye’s proven autonomous technology framework to create differentiated products and customized automated driving experiences while supporting faster time-to-market and reducing overall execution risk. Mobileye DXP was designed by separating the universal aspects of driving policy, such as integration with perception, providing safe decision-making actions, and predicting intentions of other road users, from the unique aspects of the driving experience, or “how” the vehicle executes specific scenarios. This approach enables a middle ground between traditional black box (i.e., “closed”) and software development kit (SDK) (i.e., “open”) strategies, satisfying automakers’ desire to control and differentiate the overall driving experience—including how the vehicle responds to traffic signals, other vehicles on the road, take-way or give-way choices, and more. Additionally, automakers can also set specific response parameters for factors like geography, regulations, road type or weather conditions. DXP supports efficient, successive software updates based on automaker roadmaps, as the safety critical elements, like sensing, environmental perception, and driving policy, remain static.

●“Scale by design” approach - Our technology platform is built to deliver autonomous driving solutions at scale by leveraging our REM™ mapping technology, which allows our solutions to be driven without the limitations of geofencing; our True Redundancy™ approach, which allows for cost-efficient validation; our RSS and driving policy, which provides a framework for regulatory certainty and lean compute that is critical for mass-deployment; and, our active sensor architecture based on our imaging radars, which we expect will help support cost-efficient consumer AV production at scale in the future.

●Autonomous driving-ADAS synergies - The autonomous driving-ADAS interplay, which is borne out of our Compound AI architecture (including True Redundancy™), is bi-directional: advanced technologies transfer from autonomous driving to ADAS and significantly enhance our market proposition, and in turn, these advanced autonomous driving technologies are validated in commercial, mass market ADAS deployments and contribute to the process of verifying and validating the various elements of our autonomous driving solution stack. Moreover, our scalable architecture provides our OEM partners with operational efficiencies as modular technology platform architecture minimizes the OEMs’ integration and validation burden as our solutions can be seamlessly deployed across multiple vehicle segments.

●Road Experience Management™ creates a powerful network effect and long-term competitive advantage - Our REM™ system is a crucial ingredient that we believe allows for: (1) defining a new category of cloud-enhanced ADAS that we call Cloud-Enhanced ADAS™, where information in Mobileye Roadbook™ enhances existing ADAS functions such as lane keeping assist and lane-centering and allows for new functions such as the analysis of behavior patterns in intersections and near traffic signs and lights; (2) evolving ADAS to an eyes-on/hands-off point-to-point assisted driving navigation system; and (3) the scale deployment of AV. REM™ is complex, requiring advanced processing at the edge (for creating processed data to be sent to the cloud and for localizing the vehicle at centimeter-level accuracy in Mobileye Roadbook™), and computationally intensive processing in the cloud to build Mobileye Roadbook™ from billions of data packets sent from millions of vehicles - all automatically. REM™ benefits from a powerful network effect, where more vehicles with REM™ enabled technology from which we are able to collect and process data, not only improves our own solutions, but also delivers benefits to our customers and to consumers through greater safety and expanded functionality. We believe this network effect creates a powerful competitive advantage, particularly given our leadership position in ADAS, as we are able to efficiently collect large amounts of data from our consumer solutions already deployed on roads globally through their regular use. Our REM™ maps are a critical component that supports our SuperVision™ product’s ability to operate across a wide ODD and, therefore, the modular process of expanding this technology to eyes-off/hands-off Chauffeur™ products for a defined ODD. Further, our REM™ maps support our ability to deploy our AMaaS technology in new cities and geographies quickly.

●Data and technology advantage - Developing effective ADAS technology is technologically complex and requires the development of large validation datasets in order to train the required software algorithms effectively, a long-term commitment to validation and qualification with an OEM before series production can even begin, and significant financial resources. We have assembled a substantial dataset of real-world driving experience, encompassing hundreds of petabytes of data, which includes tens of millions of clips collected over decades of driving on urban, highway, and arterial roads all over the world that enable us to develop and continuously improve advanced computer vision algorithms to fit road scenarios and use cases that our system encounters. We have developed sophisticated 2D and 3D automatic-labeling methodologies that, together with a team of thousands of external specialized annotators, allow for fast development cycles for our computer vision engines based on the dataset we have. In addition, our advanced data labeling infrastructure and data mining tools can unlock significant data-driven insights. In parallel, we have created a rich dataset of roads driven from over 8 million REM™-enabled vehicles worldwide that we estimate covers over 95% of the approximately 0.8 million miles of motorway, trunk, and primary road types in each of the United States and Europe, respectively, as well as a large majority of all other road types. We apply a series of on-cloud algorithms to build this crowd-sourced data into a high-definition, rapidly updating map that contains a rich variety of information, including road geometry, drivable paths, common speeds, right-of-way, and traffic light-to-lane associations. Our REM™-enabled solutions continuously harvest high-precision data that is analyzed in the cloud, creating a large repository of real-world data from the analysis of tens of millions of miles of road data per day, varying by road types and geography. This data enables us to create robust high-definition maps to support solutions across the product spectrum from Cloud-Enhanced ADAS™ and Mobileye Surround ADAS™ to Mobileye SuperVision™ to Mobileye Chauffeur™ and Mobileye Drive™. These two datasets create powerful network effects as we seek to continually improve our solutions as more vehicles are deployed with our technology.

●RSS: Our Technology Safety Concept for Deploying AV at Scale - Responsibility Sensitive Safety (“RSS”), published in 2017, is a key component of our safety model, intended to specifically address the regulatory and public debate regarding, and enable the acceptance of, eyes-off/hands-off autonomous solutions. It is a formal, explicit, machine interpretable model governing the safety of our autonomous driving solutions’ driving policy. RSS articulates a set of plausible-worst-case assumptions regarding the behavior of other road-users, thereby enabling assertive, human-like driving while rigorously respecting the boundary between safe driving decisions and dangerous, risk-inducing ones. By doing so, it provides a deterministic model for safe driving decisions. As such, RSS further gives regulators and industry participants a framework for standardizing autonomous driving decision-making safety. RSS is also the key enabler of our lean compute driving policy design, as we distinctly separate comfort driving strategies and tactics from safety-related inhibitions and adjustments. RSS has inspired a global standardization effort of AV safety including IEEE 2846, an industry working group that we lead. We first published our RSS model in 2017, setting another example of our industry leadership in addressing one of the key issues to enable regulatory and public acceptance of eyes-off/hands-off autonomous solutions at scale.

●RSS is the key enabler of our lean compute driving policy design, where we distinctly separate driving comfort features from safety-related inhibitions and adjustments. Our framework monitors and establishes driving policy by identifying intentions in order to only predict the plausible actions of road users, significantly reducing possible options and computational demands. Our RSS-based driving policy is designed for global deployment, as it does not need to be tailored to specific driving cultures.

●Purpose-built imaging-radar unlocks consumer AV at scale - We have developed software-defined imaging-radar with cutting-edge dynamic range and resolution. Our differentiated True Redundancy™ architecture, which is adaptable to different lidar architectures, will leverage our imaging-radar, which we believe will give us the ability to significantly reduce the cost of the overall sensor suite by replacing multiple, expensive lidars around the vehicle, with only a single front-facing lidar sensor, which we believe will support consumer AV production at scale.

●Deep, collaborative ecosystem relationships - Our deep global relationships with key partners across the value chain, from component suppliers, through Tier 1 customers and up to OEMs, offer us a broad and diverse set of collaboration opportunities for high-performance computing, networking, and advanced packaging technologies, among others, from the vehicle to the cloud. Together with our partners, we believe that we can accelerate the pace of autonomous innovation and market adoption.

Our Growth Strategies

Key levers of our growth strategy are:

●Benefit from regulatory and safety rating changes promoting base ADAS - We intend to continue to lead and deliver upon global regulatory and safety requirements for base ADAS features by maintaining and enhancing our vision only solution. We expect a strong increase in base ADAS fitment rates due to global regulatory and safety requirements, as OEMs move to adopt standard ADAS technology for the vast majority of new model launches. We plan to continue to leverage our technology leadership and strong customer relationships to position us for additional design wins with high production volumes. We believe that our comprehensive stack of solutions and proven success at scale will enable us to further solidify our industry leadership.

●Capitalize on Cloud-Enhanced ADAS™ features - We have pioneered a cloud-enhanced ADAS solution, which offers customers using advanced EyeQ™ versions (EyeQ™4 and above) a significant value through our REM™ technology. Our Cloud-Enhanced ADAS™ solution is capable of utilizing our EyeQ™ SoCs and entry level camera technologies to deliver feature enhancements over time. Our premium Cloud-Enhanced ADAS™ features range in complexity from all road-type lane keeping assist and lane centering, to Cross-Junction Assist, to Traffic Jam Assist. We will continue to grow the depth and breadth of our REM™ maps in order to deliver leading ADAS capabilities. In the future, we plan to create revenue streams from our OTA capabilities and REM™ maps through solution upgrades.

●Further enhance and drive adoption of our Premium Driver Assist solutions - Our Mobileye Surround ADAS™ and SuperVision™ solutions represent the next steps toward next-generation comprehensive eyes-on/hands-off ADAS solutions where incremental safety and the convenience of hands-off driving combine in a compelling package for drivers. Our initial generation of SuperVision™ was based on the EyeQ™5 High system on chip and initially launched with the Geely Group’s premium electric vehicle brand, ZEEKR. After the initial launch, we successfully executed a series of software updates and also achieved a series of production program awards with Volkswagen Group that substantially increased the number of vehicle models in our future launch pipeline. During 2025, we made significant progress in the execution of the second generation of SuperVision™, based on EyeQ™6 High, targeting a number of upcoming vehicle launches with VW Group brands Porsche and Audi. Our validated SuperVision™ technology can serve as the foundation to enable eyes-off/hands-off capabilities in a modular way. We believe that Mobileye SuperVision™ has the potential to transform ADAS at its core, potentially leading to adoption driven by regulatory requirements and safety ratings of a Mobileye SuperVision™-like solution in its own category, similar to how safety-ratings and regulation have driven the adoption of base ADAS beginning in 2014.

Additionally, we added a new innovative Premium ADAS solution, Mobileye Surround ADAS™, which utilizes the SuperVision™ software stack with a down-scaled sensor suite and an ECU that includes one EyeQ™6 High SoC. The solution will enable eyes-on/hands-off driving on highway road types (as compared to SuperVision™ which is expected to operate on various ODDs). Mobileye Surround ADAS™ will provide OEMs with higher levels of autonomy than Cloud-Enhanced Driver Assist™, which we believe will expand the application and adoption of our products. In addition to the safety features and eyes-on/hands-off capability, this product can also result in the consolidation of several functions, including automated parking and driver / occupant monitoring, onto a single ECU that results in a lower-cost solution for OEMs as compared to first-generation Level 2+ systems currently on the market. As a result, we are seeing increasing traction to equip this type of system as standard-fit across wide-ranging vehicle price and model segments.

Our Premium Driver Assist offerings are expected to be available with DXP, which will enable OEM customers to deploy their own internally-developed software on our EyeQ™ SoCs while benefiting from our industry-leading technology platform.

●Innovate and commercialize our next-generation autonomous driving solutions - Propelled by our next generation EyeQ™ SoC, our surround computer vision Mobileye SuperVision™ solution, productization of software-defined imaging radars and our Compound AI system architecture including True Redundancy™, we believe that we will be positioned to deliver an autonomous driving solution that can enable the mass adoption of AV. We plan to continue to develop innovative and cost-optimized solutions to deliver comprehensive capabilities for mass market adoption to our customers. We believe the introduction of our Premium ADAS capabilities with our launched Mobileye SuperVision™ solution, which can be scaled to a variety of Mobileye Chauffeur™ consumer AV solutions, and our eyes-off/hands-off/no driver capabilities with Mobileye Drive™ will help us continue to provide our customers with innovative solutions and enable further growth for us. The favorable view of Chauffeur™ eyes-off technology by automakers is based on two key factors: 1) Chauffeur™ adds “buying your time back” as an additional value proposition on top of the safety and convenience benefits of SuperVision™; and 2) the sharing of tech building blocks between SuperVision™ and Chauffeur™ creates a scalable bridge from one to the other, significantly lowering the investment needs and raising the probability of success for a consumer AV product. We plan to continue to build and enhance our full-stack technology platform in order to offer an affordable, time-saving and much safer driving experience, which we believe will propel the mass-market adoption of autonomous driving solutions.

●Utilize our flexible platform to expand our collaboration with our OEM customers - We have designed our EyeQ™5 SoCs and subsequent generations to be increasingly customizable by our OEM customers, supported by DXP. DXP enables automakers to develop and customize the driving experience while utilizing Mobileye’s proven core technology perception and driving software - allowing our customers to create unique products from our technology while accelerating time-to-market and reducing overall execution risk. We plan to continue to develop our platform to offer our customers the ability to seamlessly address the additional capabilities and features that they demand by customizing their offerings on top of our solutions. This collaborative addition to our platform offers a mutually beneficial middle ground between open and closed systems, which will allow OEMs to innovate on top of our platform, augmenting and differentiating their offerings, while benefiting from our cutting-edge, verified and validated core technologies such as computer vision, true redundancy perception, REM™ mapping and driving policy.

●Capitalize on our active sensor technology - We intend to continue to develop and commercialize next-generation active sensors such as software-defined imaging radars, which leverage our AI capabilities. Our software-defined imaging radars are designed to form a standalone “sensing state” layer which can be utilized as a sensing layer on its own, enabling 360-degree coverage, replacing multiple lidar sensors and requiring only a single front-facing lidar. We believe enhancing our sensing and perception technology leadership will further strengthen our competitive position and allow us to offer additional differentiated and cost-effective solutions to our customers.

●Accelerate our roadmap of next generation proprietary EyeQ™ SoCs - We believe that we have created the standard for processors focused on Compound AI systems that control perception, including computer vision. Our EyeQ™ SoCs are purpose-built for sensing and perception technologies and optimized for high throughput and power efficiency. We intend to continue to accelerate our technology leadership with a focus on silicon, packaging, and systems level needs to deliver cost-efficient processing at the edge. EyeQ™6 High will be built to address the needs of eyes-on/hands-off and eyes-off/hands-off solutions in a scalable way. Our architecture is highly scalable and is designed to support the increasing and computationally intensive demands of future autonomous driving applications.

●Utilize our substantial and growing dataset to continuously improve the intelligence and robustness of our solutions - We will continue to grow the depth and breadth of our substantial dataset. We believe that our ability to use this data to create, maintain, and improve our Compound AI systems and high-precision REM™ maps through our REM™ mapping system will enable us to further improve our ADAS offerings and position us well for autonomous driving.

●Establish our Eyes-Off/Hands-Off autonomous and AMaaS solutions - We believe that Mobileye Chauffeur™ and Mobileye Drive™ will unlock new use cases and end-consumers for our OEM and fleet-owner customers, which will be applicable for both the AMaaS and consumer AV markets. We expect, in collaboration with our customers, to add additional cities to our AMaaS offerings to showcase our industry-leading technology and to help accelerate the pace of AV adoption. We also expect to continue to invest in our ecosystem partnerships with OEMs and transportation network companies in order to foster close collaboration and further commercialize our autonomous technologies.

●Benefit from opportunities in large emerging markets - We intend to continue to invest in customer relationships in emerging markets to accelerate ADAS and autonomous driving adoption, particularly in India. Mahindra & Mahindra, one of India’s largest automakers, has launched the first vehicle made locally to offer ADAS capabilities, which is powered by our EyeQ™ SoC. Its accessible price point compared to imported alternatives expands the ADAS reach to a broader range of consumers in one of the most populous countries in the world. We believe our long-term partnerships with emerging market OEMs position our solutions at the forefront of continued innovation and market growth.

Our Customers

Our customers include leading OEMs, which we primarily sell to through Tier 1 automotive suppliers that implement our product into automotive vehicles, as well as fleet owners and operators.

OEMs

Our market position has remained strong across a broad set of customer relationships for many years. We are actively working with more than 50 OEMs worldwide on the implementation of our ADAS solutions.

Tier 1 Automotive Suppliers

We supply certain OEMs with the EyeQ™ platform through our arrangements with automotive system integrators, known as Tier 1 automotive suppliers, which are direct suppliers to OEMs. Our Tier 1 customers include Aptiv, Magna, Valeo, ZF, Imotion, HL Klemov, Mobis and others.

Autonomous Mobility-as-a-Service

We, along with commercialization partners such as MOIA and Holon, expect to sell or deploy Mobileye Drive™-equipped self-driving vehicles to a range of transportation network companies, public transit operators, other mobility service companies and vehicle OEMs which intend to operate a variety of services (e.g., consumer-facing AMaaS, transportation on demand, delivery). These partners could produce vehicles themselves and integrate Mobileye Drive™ with our assistance.

Our Partnerships with STMicroelectronics and Intel

Our long-standing relationship with STMicroelectronics N.V. (“STMicroelectronics”) continues to strengthen with the complexity of our solutions. Our partnership includes close collaboration in product development, design, and manufacturing. For example, we have co-developed six EyeQ™ generations, including the EyeQ™6. We also benefit from STMicroelectronics’ advanced packaging and testing capabilities and automotive expertise. Together with STMicroelectronics, we are working on developing and productizing next-generation automotive-grade technology for high volume automotive applications, which we believe will accelerate the pace of autonomous innovation and market adoption.

Our close partnership with Intel exists on multiple fronts. As a result of our relationship with Intel, we have access to certain technologies that support design and development of our software-defined radar, including Intel’s mmWave technologies. Intel’s strength in government affairs and policy development around the world will continue to be of significant value to us as we collaborate with regulators who are preparing frameworks to enable commercial deployment of AVs.

Manufacturing

Our products are designed and manufactured specifically for automotive applications after extensive validation tests under stringent automotive environmental conditions.

We partner with STMicroelectronics, a leading supplier and innovator of semiconductor devices for automotive applications, in manufacturing, design and research and development. We have co-developed six generations of our automotive grade SoC, EyeQ™, with STMicroelectronics including EyeQ™5 and EyeQ™6. We design the front-end and STMicroelectronics designs the back-end package. These design processes also include testing, quality assurance, customer care, failure analysis and ensuring compliance with manufacturing standards. All of our EyeQ™ integrated circuits are manufactured by or outsourced to a partner foundry by STMicroelectronics.

We have also established a relationship with Quanta Computer, Taiwan Semiconductor Manufacturing Company (“TSMC”) and other suppliers to develop and assemble our ECUs including our reference design for our Mobileye SuperVision™ solution, which includes our EyeQ™5 and EyeQ™6 SoCs from STMicroelectronics.

Regulation and Ratings

Automobile safety is driven by both regulations and the availability to consumers of independent assessments of the safety performance of different car models. These assessments have encouraged OEMs to produce cars that are safer than those required by law. In many countries, these NCAPs have created a “market for safety” as car manufacturers seek to demonstrate that their models satisfy the various NCAPs’ highest ratings.

National NCAPs will continue to add specific ADAS applications to their evaluation items over the next several years, led by the Euro NCAP. In the EU, pre-market approval is required for all vehicles sold, and many manufacturers choose to satisfy a set of technical criteria determined by the Euro NCAP. The Australian, Japanese, and Korean NCAPs’ have fully harmonized their policies with the Euro NCAP. In 2025, Euro NCAP approved and announced significant updates to its protocols that will take effect in 2026, reflecting evolving expectations for ADAS performance and human-machine interface considerations. We believe that this and such additional future evolution of standards will drive the need for additional sensors and compute which our Mobileye Surround ADAS™ solution is strategically positioned to support. In the United States, ADAS regulation continues to make large strides. For example, the INVEST in America Act, which was passed in late 2021, requires the U.S. Department of Transportation to issue requirements and standards regarding vehicle safety technologies. In addition, NHTSA has adopted a new FMVSS requiring automatic emergency braking systems on new light vehicles, and in early 2025 the U.S. Department of Transportation temporarily delayed the effective date of a related final rule as part of a regulatory review process. On the AV front, our RSS driving policy provides a cornerstone for global standardization efforts of the safety of assisted and automated driving, in particular IEEE 2846, a working group of approximately 30 organizations in the industry that we lead.

At the federal level in the United States, the safety of motor vehicles is regulated by the U.S. Department of Transportation through two federal Agencies - the National Highway Traffic Safety Administration (the “NHTSA”), which regulates all motor vehicles, and the Federal Motor Carrier Safety Administration (the “FMCSA”), which regulates commercial motor vehicles. NHTSA establishes the Federal Motor Vehicle Safety Standards (the “FMVSS”) for motor vehicles and motor vehicle equipment and oversees the actions that manufacturers of motor vehicles and motor vehicle equipment are required to take regarding the reporting of information related to defects or injuries related to their products and the recall and repair of vehicles and equipment that contain safety defects or fail to comply with the FMVSS. FMCSA regulates the safety of commercial motor carriers operating in interstate commerce, the qualifications and safety of commercial motor vehicle drivers, and the safe operation of commercial trucks.

While there are currently no mandatory federal U.S. regulations expressly pertaining to the safety of autonomous driving systems, the U.S. Department of Transportation has established recommended voluntary guidelines, and the NHTSA or the FMCSA, as applicable, have authority to take enforcement action should an automated driving system pose an unreasonable risk to safety or inhibit the safe operation of a motor vehicle. Certain U.S. states have legal restrictions on autonomous driving vehicles, and many other states are considering them. These variations increase the legal complexity of deploying our solutions. If discrepancies emerge in the legal restrictions adopted by different U.S. states, our plan is to develop our technology to comply with the strictest standards. We will continue to actively monitor regulatory developments in the U.S. and intend to adjust our products and solutions as needed.

In Europe, certain vehicle safety regulations apply to self-driving braking and steering systems, and certain treaties also restrict the legality of certain higher levels of autonomous driving vehicles. In jurisdictions that follow the regulations of the United Nations Economic Commission for Europe, some regulations restrict the design of advanced driver-assistance or self-driving features, which can compromise or prevent their use entirely. Other applicable laws, both current and proposed, may hinder the path and timeline to introducing self-driving vehicles for sale and use in the markets where they apply. Other markets, including China, continue to consider self-driving regulation. Any implemented regulations may differ materially from those in the United States and Europe, which may further increase the legal complexity of self-driving vehicles and limit or prevent certain features. Autonomous driving laws and regulations are expected to continue to evolve in numerous jurisdictions in the United States and foreign countries and may create restrictions on autonomous driving features that we develop.

Trade Restrictions and Export Control

In order for us to operate in international markets, we must comply with relevant legal regulations regarding autonomous vehicles as well as technology export control, data security, cybersecurity and other related regulations that apply to global technology companies. We have developed robust compliance processes and procedures related to these regulatory requirements and believe that we are in compliance with such requirements.

On October 7, 2022, the U.S. Department of Commerce’s Bureau of Industry and Security (“BIS”) announced restrictions on the export of advanced computing integrated circuits and related items to China and certain other jurisdictions. Based on our existing customer base and the export classifications for our existing chip products, we do not believe that these U.S. export controls will have a material impact on our sales of these products to our existing customers (including those in China), however this assessment remains subject to ongoing technical reassessment against evolving regulatory thresholds and may change for future generations of our chip products. In 2023, BIS added to these restrictions and the U.S. also worked with Japan and the Netherlands to align on additional restrictions on semiconductor manufacturing equipment. In January 2025, BIS announced additional controls on advanced computing chips and certain closed AI model weights. These controls were withdrawn before taking effect, however future AI oversight regulations could materially affect our business operations. On January 14, 2025, BIS announced the adoption of a final rule prohibiting certain transactions involving the sale or import of (i) connected vehicles integrating “Vehicle Connectivity System” hardware, and (ii) connected vehicles integrating “Automated Driving System” or “Vehicle Connectivity System” software, or those components sold separately, in each case with a sufficient nexus to the People’s Republic of China or Russia. The software provisions of the final rule and the prohibition on sales of connected vehicles will take effect for model 2027 and the hardware-related prohibitions will take effect in model year 2030, or January 1, 2029 for units without a model year. We have developed and implemented compliance processes for these new rules and expect to be compliant when these restrictions are effective. In addition, recent regulatory actions by the United States and the Netherlands have impacted Nexperia, a global manufacturer of essential semiconductor components, by restricting access to certain technologies and limiting cross-border transfers of semiconductor products. We have implemented supply chain redundancy strategies and diversified our Tier 2 semiconductor sourcing to address potential impacts to our business and operations and support long-term operational resilience. Import and Export control regulations adopted by the United States and other jurisdictions are subject to change and interpretation, and it is possible that future regulatory actions by BIS impacting U.S. imports and exports of integrated circuits as well as certain software and hardware components used in our systems and related items could have a material impact on our business operations.

Data Privacy

Privacy is fundamental to Mobileye. We collect, process, transmit, and store personal information in connection with the operation of our business and are subject to a variety of local, state, national and international laws, directives and regulations that apply to the collection, use, retention, protection, security, disclosure, transfer and other processing of personal data in the different jurisdictions in which we operate. Data collected by the camera and sensors of our solutions during the development cycle of a project may include personal information such as license plate numbers of other vehicles, facial features of pedestrians, appearance of individuals, GPS data, and geolocation data in order to train the data analytics and AI technology equipped in our solutions for the purpose of identifying different objects and predicting potential issues that may arise during the operation of a motor vehicle. As we work to integrate in‑cabin sensing technologies, including camera‑based driver monitoring and occupant monitoring systems, we may collect sensitive personal information, such as biometric identifiers, gaze patterns, facial features, behavioral attributes, and, in some configurations, audio or physiological indicators. This may increase the volume and sensitivity of data we process, and may subject us to heightened compliance obligations.

We anticipate that our collection of such personal information may increase with the growing introduction of our AMaaS and robotaxi solutions, and our integration of Moovit, which may provide us with access to personal information of users. Our data-collection processes implement strict methodologies to comply with data protection and privacy laws, including the EU General Data Protection Regulation (the “GDPR”, the UK General Data Protection Regulation, and U.S. federal and state laws, including the California Consumer Privacy Act of 2018 (the “CCPA”), as amended by the California Privacy Rights Act of 2020 (the “CPRA”). In addition, the EU Artificial Intelligence Act (“EU AI Act”) entered into force in 2024 and is being applied in a phased manner through 2025 and 2026. Certain AI systems used in the context of autonomous driving, mobility, and large-scale monitoring of public spaces may be classified as high-risk AI systems, triggering additional obligations related to data governance, transparency, human oversight, risk management, and post-market monitoring.

We leverage systems and applications that are spread over the countries in which we do business, requiring us to regularly move data across national borders. As a result, we are subject to a variety of laws and regulations in the United States, China, the European Union, Israel and other foreign jurisdictions as well as contractual obligations, regarding data privacy, protection, and security.

The scope and interpretation of the laws and regulations that are or may be applicable to us are often uncertain and may be conflicting, particularly with respect to foreign laws. We are subject to the GDPR, which became effective in May 2018. EU member states have enacted certain implementing legislation that adds to and/or further interprets the GDPR requirements. The GDPR together with national legislation, regulations and guidelines of the EU member states governing the processing of personal data, impose strict obligations and restrictions on the ability to collect, use, retain, protect, disclose, transfer, and otherwise process personal data with respect to EU data subjects. In particular, the GDPR includes obligations and restrictions concerning the consent and rights of individuals to whom the personal data relates, the transfer of personal data out of the EEA, security breach notifications and the security and confidentiality of personal data. We are also subject to the UK General Data Protection Regulation (i.e., a version of the GDPR as implemented into UK law), exposing us to two parallel regimes with potentially divergent interpretations and enforcement actions for certain violations. While the European Commission issued an adequacy decision in respect of the UK’s data protection framework, enabling data transfers from EU member states to the UK to continue without requiring organizations to put in place contractual or other measures in order to lawfully transfer personal data between the territories, that EC adequacy decision was originally subject to a sunset clause set to expire on June 27, 2025, but was subsequently extended for an additional six‑year term with a new sunset date of December 27, 2031. This adequacy decision may be revoked in the future by the European Commission if the UK data protection regime is reformed in ways that deviate substantially from the GDPR. Other countries have enacted or are considering enacting similar cross-border data transfer rules or data localization requirements.

Additionally, U.S. state governments continue to enact new data protection and privacy laws and regulations since 2018, including California, Colorado, Connecticut, Delaware, Iowa, Texas, Utah, Virginia and many others. These new state laws and regulations may impact our business practices, including limiting our ability to use clips for internal development and validation purposes. Several U.S. state laws impose heightened restrictions on the processing of sensitive personal data, including precise geolocation data and biometric identifiers, and provide consumers with opt-out rights from certain automated decision-making and profiling activities. Federal and state laws and regulations are changing rapidly and new federal data protection and privacy laws remain under discussion, to which we would become subject if any such laws were enacted. Compliance with these federal and state data protection and privacy laws and regulations, and other similar federal or state laws and regulations that may be enacted in the future, may require us to put in place additional mechanisms to comply with such laws and regulations which could cause us to incur substantial costs or require us to change our business practices, including our data processing practices, in a manner adverse to our business. Moreover, any failure to comply with such federal and state laws and regulations could result in, among other things, regulatory or government investigations, monetary penalties or fines, litigation (including civil claims, such as representative actions and other class action-type litigation), and orders to cease, modify or change our business practices, including our data processing practices.

In China, the Cyber Security Law (as amended in 2026) reaffirms the basic principles and requirements specified in other existing laws and regulations on personal information protection, such as the requirements on the collection, use, processing, storage, and disclosure of personal information. China has implemented additional comprehensive data protection and cybersecurity laws, including the PRC Data Security Law, the PRC Personal Information Protection Law (PIPL), the PRC Network Data Security Management Regulations (2025) and the Automotive Data Export Security Guidelines (2026), which significantly expand compliance obligations. Under these laws and related regulations, organizations may be subject to enhanced requirements regarding lawful processing, data localization in certain circumstances, government security assessments or other approvals for specific processing activities or cross-border data transfers, and restrictions on transfers of personal information and certain automotive data outside of China, with broad enforcement authority and potentially significant penalties for non-compliance.

In Israel, we are subject to the Israeli Privacy Protection Law, 5741-1981 (the “PPL”), and the regulations promulgated thereunder, including the Israeli Privacy Protection Regulations (Data Security), 5777-2017, which impose detailed requirements regarding the processing, transfer, and safeguarding of personal data, and additional regulations governing exercising of privacy rights, cross-border data transfers, import of personal data from the EU and so forth. Similar to the UK, the European Commission has issued an adequacy decision in respect of Israel’s privacy laws in 2011, enabling data transfers from EU member states to Israel without additional contractual burden, and currently, without expiry term.

The Israeli Privacy Protection Authority (the “PPA”), acting as the supervisory authority in respect of Israeli privacy laws, has from time to time issued guidance which serves as complementary compliance requirements on controllers and processors such as the Company. On August 14, 2025, the most significant amendment to the PPL (“Amendment 13”) took effect, which significantly increased

the enforcement and investigative powers of the PPA, and as a result, significantly increased the potential for imposing administrative sanctions for violations of the PPL and its regulations, and in some cases, monetary sanctions. In addition, Amendment 13 further increased civil liability as the statute of limitations was increased from two to seven years and new punitive damages without proof were added to protect privacy rights violations by controllers and processors. Significant amendments to the PPL or its regulations may require updates to our data protection and security practices. Failure to comply with the PPL and its regulatory framework could result in enforcement actions, litigation (including class actions), administrative orders, and monetary penalties.

Our Competition

The ADAS and autonomous driving industries are highly competitive. In the ADAS and consumer AV market, we face competition primarily from other external providers including Tier 1 automotive suppliers and silicon providers, as well as in-house solutions developed by the OEMs to a certain extent. Our Tier 1 customers may be developing or may in the future develop competing solutions. For example, certain of our competitors have announced that they are operating autonomous robotaxis. Tier 1 automotive supplier competitors include Bosch, Continental, and Denso. Our silicon provider competitors include Ambarella, Advanced Micro Devices, Arriver / Qualcomm, Black Sesame Technologies, Horizon Robotics, Huawei, NVIDIA, NXP, Renesas Electronics, and Texas Instruments. OEMs who have or are pursuing their own in-house solutions are also indirect competitors, with Tesla and Mercedes-Benz being examples of automakers taking that approach today, with others such as General Motors, NIO, Volvo Cars, Xpeng Motors, Huawei and Li Auto also pursuing in-house solutions for portions of the advanced ADAS software stack. In the future, our indirect competitors could become direct competitors.

In the autonomous driving market, including AMaaS and consumer AV, we face competition from technology companies, internal development teams from the automakers themselves, sometimes in combination with investments in early-stage autonomous vehicle technology companies, Tier 1 automotive companies, as well as robotaxi providers. AMaaS competitors include Cruise, Tesla, Motional, Waymo, NVIDIA, Yandex, and Zoox in the United States and Europe and Auto X, Baidu, Deeproute.ai, Didi Chuxing, Momenta, Pony.ai and WeRide in China. Consumer AV competitors include Sony and Tesla, who are developing self-driving vehicles for consumers. We also face competition from companies that offer “software-only” autonomous vehicle solutions, including StradVision, Autobrains, Wayve and Momenta.

Developing effective ADAS technology is technologically complex, requires the development of large validation datasets in order to train the required software algorithms effectively, requires a long-term commitment to validation and qualification with an OEM before series production can even begin, and requires significant financial resources. In addition, our tightly coupled software and hardware solutions, which are based on highly advanced, road-tested, sensing and perception technologies from decades of leadership in AI, including computer vision, and powered by our mission critical software and purpose-built EyeQ™ family of SoCs are extremely hard to replicate.

Competition in the humanoid and Physical AI robotics market is intense and rapidly evolving, with a growing number of well-capitalized companies developing general-purpose bipedal robots and related autonomy stacks for industrial and warehouse use. We face competition from other humanoid robotics developers such as Tesla, Figure AI, Sanctuary AI, PAL Robotics, Agility Robotics and Boston Dynamics, as well as additional emerging players (including a number of Chinese robotics companies) seeking to commercialize similar capabilities.

Moovit competes against urban mobility applications and mobility-as-a-service (“MaaS”) solutions which provide transportation services and navigation data to consumers. Moovit’s free and subscription-based application competition includes Alphabet, Apple, Citymapper, and Transit. Moovit’s application also competes with local urban and inter-city ticketing service providers that provide purchase and ticketing of public transit and mobility services on their own platform.

The principal competitive factors impacting the market for our solutions include:

●completeness of our technology platform including SoCs, sensing and perception technologies, sensor fusion architecture, high-precision mapping system, and supporting software and algorithms;

●ability to design and develop ADAS, autonomous driving and humanoid robotics solutions that meet our customers’ needs;

●automotive quality standards, compliance, and performance in all areas of ADAS and autonomous driving;

●ability to successfully integrate Mentee Robotics’s business and humanoid and Physical AI robotics technology with our existing platform;

●agile software validation and robust product release discipline;

●scalability, and cost efficiency of our solutions;

●engineering capabilities, the ability to innovate and continuously improve our technology;

●pricing;

●design and development support for our customers;

●manufacturing reliability and the ability to make on-time delivery of appropriate quantities of product at a consistent level of quality;

●ability to meet regulatory requirements;

●intellectual property protection;

●attraction and retention of key talent, including in artificial intelligence and robotics; and

●brand and reputation, including the ability to market new offerings.

We believe we compete favorably with respect to these factors. In addition, as the ADAS and autonomous driving markets progress and, in some use cases, converge, we believe we will be in a favorable position to achieve meaningful business wins given our differentiated capabilities.

Distribution and Marketing

Our products are sold directly to customers throughout the world, or through distribution channels for our remaining inventory of aftermarket products meant for vehicles that do not come pre-equipped with ADAS technology.

We actively promote our brand and technologies to increase awareness and generate demand through direct marketing as well as co-marketing programs. Our direct marketing to consumers and businesses primarily includes trade events, industry and consumer communications and press relations. We work closely with our existing customers in order to ensure that we are aware of their requirements and plans for future car models and can respond promptly and effectively.

We regularly present our technology to regulators and safety organizations to demonstrate its capabilities and reliability and to help ensure that they develop regulations and ratings that address the full range of benefits that we believe we can offer.

Research and Development

We believe our strong research and development is our principal competitive strength and has led to our position in the market. Our research and development activities are predominantly conducted in Israel. We have approximately 85% of our full time-equivalent employees engaged in research and development, many of whom have been with the company for significant tenures. Our research and development efforts focus on algorithms, including visual processing, camera control, vehicle control, camera/radar fusion, autonomous driving sensing technologies, REM™ technology, driving policy and related engineering tasks as well as application software, silicon design and hardware electronics design. We believe we have a unique approach by developing ADAS and autonomous solutions simultaneously, giving us a technical and scale advantage over our competition.

Our Employees

As of December 27, 2025, we had approximately 4,200 employees operating across seven countries, with approximately 85% of such employees involved in research and development and approximately 3,900 of such employees operating in Israel. As of February 3, 2026, following a workforce reduction and the acquisition of Mentee Robotics, we had approximately 4,130 employees. None of our employees is represented by a labor union with respect to his, her or their employment. In certain countries in which we operate, we are subject to, and comply with, local labor law requirements, which may automatically make our employees subject to industry-wide collective bargaining agreements. We have not experienced any work stoppages and we consider our relations with our employees to be good.

Intellectual Property

Our ability to compete effectively depends in part on our ability to develop and maintain the proprietary aspects of our technology. Our policy is to obtain appropriate proprietary rights protection for any potentially significant new technology acquired or developed by us. As of December 27, 2025, we held 439 U.S. patents, 98 European patents, 205 U.S. patent applications, 633 European and other non-U.S. patent applications, and provisional patent filings. We do not view any single patent or patent application to be material.

In addition to patent laws, we rely on copyright and trade secret laws to protect our proprietary rights. We attempt to protect our trade secrets and other proprietary information through agreements with OEMs, distributors, other customers and suppliers, proprietary information agreements with our employees and consultants, and other similar measures. Our primary trademarks are for our name and product names. We cannot be certain that we will be successful in protecting our proprietary rights. While we believe our patents, patent applications, software and other proprietary know-how have value, changing technology makes our future success dependent principally upon our ability to successfully achieve continuing innovation.

Litigation may be necessary in the future to enforce our proprietary rights, to determine the validity and scope of the proprietary rights of others, or to defend us against claims of infringement, misappropriation or other violation or invalidity by others. An adverse outcome in such litigation or similar proceedings could subject us to significant liabilities to third parties, require disputed rights to be licensed from others or require us to cease marketing or using certain products, any of which could have a material adverse effect on our business, financial condition, and results of operations. In addition, the cost of addressing any intellectual property litigation claim, both in legal fees and expenses, as well as from the diversion of management’s resources, regardless of whether the claim is valid, could be significant and could have a material adverse effect on our business, financial condition, and results of operations.

Relationship with Intel

Prior to the Mobileye IPO, Intel beneficially owned 100% of our outstanding shares of common stock and we operated as Intel’s wholly owned subsidiary. As of December 27, 2025, Intel beneficially owns 50,000,000 shares of our Class A common stock and all of the outstanding shares of our Class B common stock, representing approximately 79.5% of our outstanding common stock and 97.3% of the voting power of our common stock. Due to the issuance of shares of Class A common stock in connection with the acquisition of Mentee Robotics, Intel beneficially owns approximately 77.0% of our outstanding common stock and 96.9% of the voting power of our outstanding common stock as of February 3, 2026. As a result, Intel is able to control all matters submitted to our stockholders for approval, including the election of our directors and the approval of significant corporate transactions. Furthermore, in addition to any other vote required by law or by our amended and restated certificate of incorporation, until the first date on which Intel ceases to beneficially own 20% or more of our outstanding shares of common stock, the prior affirmative vote or written consent of Intel as the holder of our Class B common stock will be required in order for us to: adopt or implement any stockholder rights plan or similar takeover defense measure; consolidate or merge with or into any other entity; permit any of our subsidiaries to consolidate or merge with or into any other entity, with certain exceptions; acquire the stock or assets of another entity for consideration in excess of $250,000,000 other than transactions in which we and one or more of our wholly owned subsidiaries are the only parties; issue any stock or other equity securities except to our subsidiaries, pursuant to the Mobileye IPO, or pursuant to our employee benefit plans limited to a share reserve of 5% of the outstanding number of shares of our common stock on the immediately preceding December 31; make or commit to make any individual or series of related capital or other expenditures in excess of $250,000,000; create, incur, assume or permit to exist any indebtedness or guarantee any indebtedness in excess of $250,000,000; make any loan to or purchase any debt securities of any person in excess of $250,000,000; redeem, purchase or otherwise acquire or retire for value any equity securities of our company except repurchases from employees, officers, directors or other service providers upon termination of employment or through the exercise of any right of first refusal; take any actions to dissolve, liquidate, or wind-up our company; declare dividends on our stock; or amend, terminate or adopt any provision inconsistent with our amended and restated certificate of incorporation or amended and restated bylaws. See “