May 14, 2026

Company Kudan Inc. Name Representative CEO Daiu Ko (Securities code: 4425 TSE Growth) Inquiries Head of Administration Tatsuhiro Ishii (Tel. 03-6892-7333)

The video and transcript of the financial results presentation for the fiscal year ended March 31, 2026 are available online

Kudan Inc. (“Kudan”) announces that the video and transcript of Kudan’s financial results presentation for the fiscal year ended March 31, 2026 are now available online. As the video is available in Japanese only, an English translation of the transcript is attached to this release.

【FY2026 financial results presentation】

1. Date: Thursday, May 14, 2026 2. Speakers: Daiu Ko, CEO

▼▼Financial results presentation video can be viewed from below (Japanese only)▼▼ https://youtu.be/19q_fuwYSJo

Daiu Ko (“Ko”): Hello everyone, this is Ko, CEO of Kudan Inc. I will now explain the full-year financial results for the fiscal year ended March 2026.

In this presentation, in addition to explaining our financial results, I would also like to discuss:

• ・ How Kudan is positioning itself within the broader trend of “Physical AI”

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• ・ How we believe this will lead to improved profitability and mid- to long-term growth

Ko: First, I would like to start with the overall picture of where Kudan is currently aiming.

The AI market is now entering a major turning point.

Until now, AI has centered on “AI without physical embodiment,” handling text, images, code, and similar content.

For example, generative AI writing text, creating images, or improving operational efficiency.

On the other hand, what we believe will expand rapidly going forward is “Physical AI” with physical embodiment.

In other words, a world in which AI exists in the real world, understanding space, taking action, learning continuously, and performing tasks autonomously.

What becomes important here is “Spatial Perception,” which Kudan focuses on. We describe this as the “machine’s eye.”

For humans, without the ability to see, we cannot walk, carry objects, or understand our environment.

The same applies to Physical AI: to exist within real space, it first needs the ability to understand space.

With Spatial Perception at its core, Kudan provides technology with applications in digital twins and mobile robots. We are now in a phase of evolving from being merely a provider of component technologies into a Spatial Perception platform company for the Physical AI era.

Over the past several years, Kudan has accumulated technical achievements and expanded its technology domains from software (SW) to hardware (HW) and solutions. In the previous fiscal

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year (FY2026, ended March 2026), we achieved revenue growth against the backdrop of the emergence of the Physical AI market.

In the current fiscal year (FY2027, ending March 2027), we will reduce losses by optimizing our revenue mix and business structure, and from the next fiscal year onward, we aim to achieve business growth accompanied by high profitability.

Ko: Now I will explain the summary of our financial results.

First, a review of the previous fiscal year (FY2026, ended March 2026). Full-year results exceeded our forecasts, with revenue above forecast and operating loss narrower than expected.

Revenue reached JPY 1.2 billion, expanding approximately 2.3 times from JPY 520 million in the prior year. This was attributable to our previous efforts in expanding technology domains and developing markets beginning to bear fruit, in addition to the contribution from expanding projects associated with the emergence of the Physical AI market.

Operating loss improved by JPY 210 million year-on-year to a loss of JPY 590 million. In particular, the profit improvement from revenue growth was a major factor and served as the central driver of operating profit improvement.

Next, the outlook for the current fiscal year (FY2027, ending March 2027).

This fiscal year is positioned as a transitional period where we prioritize “quality” over “quantity.” Specifically, we will focus on the high-gross-margin software business and accelerate profitability improvements.

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As a result, revenue is expected to temporarily decrease slightly. We view this as a temporary fluctuation that occurs during the transition to a more profitable, software-centric business structure.

On the other hand, due to this “improvement in quality,” operating profit is expected to improve significantly, with the operating loss projected to narrow from JPY 590 million in the previous fiscal year to JPY 340 million in the current fiscal year. Of this, the improvement effect from focusing on software alone is expected to be approximately JPY 350 million.

To summarize the overall flow of business performance: until FY2025, we prioritized expanding technology domains and developing markets, focusing on revenue growth. As a result, in the previous fiscal year, we significantly grew revenue and were able to capture the emergence of the Physical AI market.

In the current fiscal year, rather than stopping at mere revenue expansion from that growth, we will transition into a phase of transforming the business into one with higher profitability. We will optimize our business portfolio toward a form that prioritizes not only revenue scale but also profit margins and sustainability.

We believe that this transition will enable us to achieve revenue growth with higher profitability and a return to profitability from the next fiscal year onward.

In other words, we position the current fiscal year as an important year to develop a sustainable and highly profitable growth foundation for the Physical AI era, rather than maximizing shortterm revenue.

Ko: Next, the details of the previous fiscal year’s (FY2026, ended March 2026) results.

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Overall, against the backdrop of expanding our technology and business domains as well as the full-scale launch of the Physical AI market, we made progress in revenue growth and loss reduction over the full year.

In particular, while advancing our business focus on the high-gross-margin software area, some related hardware revenue was recognized earlier than originally planned, resulting in performance that exceeded the upwardly revised forecast.

Specifically, revenue reached JPY 1,197 million, significantly expanding from JPY 517 million in the prior year. This far exceeded the initial forecast of JPY 700 million and was approximately 9% above the upwardly revised forecast of JPY 1.1 billion.

This was supported by the expansion of software and hardware projects for digital twins, contributions from large-scale projects including government projects, and the strategic early recognition of related hardware sales as we focused on the software business.

Next, the profit side.

Operating loss was JPY 586 million, but this represents a significant improvement from a loss of JPY 800 million in the prior year. The loss was further narrowed compared to the upwardly revised forecast of a loss of JPY 680 million.

There were two main factors behind this improvement.

First, increased profit from revenue growth. Revenue expansion contributed approximately JPY 280 million in profit improvement.

Second, optimization of fixed costs. While maintaining R&D and our business structure, we reviewed our cost structure and reduced fixed costs to a certain extent.

In addition, ordinary profit and net profit improved significantly due in part to the impact of foreign exchange gains.

The “adjusted operating profit” shown in the lower section is an indicator that reflects R&D subsidy income in Europe, representing business profitability in a form closer to actual conditions. This also improved from a loss of JPY 753 million in the prior year to a loss of JPY 528 million in the previous fiscal year.

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Ko: Next, I will explain the background to revenue growth in the previous fiscal year.

The major point is that we are evolving from a company that provides SLAM alone into a Spatial Perception platform required for the Physical AI era. To this end, we have strengthened complementary technologies on both the software and hardware sides, expanding our technology and business domains to broaden revenue opportunities.

First, the upper section: expansion of SW technology.

Our central technology has traditionally been Artificial Perception (AP), represented by SLAM. In recent years, we have also expanded into the AI domain, which corresponds to the “machine’s brain.” We are extending into technology domains that not only recognize space but also learn from that information, make judgments, and translate those into action.

As a result, as shown on the right, we are expanding our suite of Spatial Perception technologies in a form where each component interoperates.

In addition to the existing domain of Localization and Mapping (self-position estimation and map generation), we are evolving by adding new domains such as understanding the semantic meaning of space, planning movement paths for robots, and high-fidelity reconstruction of the real world.

This significantly broadens the value provided as a suite of technologies for Physical AI.

Next, the lower section: utilization of HW packages.

Although we are a software company, in business development we also actively utilize collaboration with external hardware.

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First, for embedded HW packages, we provide development-oriented products that integrate sensors and processors. While this was previously primarily for development purposes, we are now expanding to UI and package offerings for actual operational use.

Furthermore, for complementary HW packages, we are expanding our ecosystem by incorporating third-party hardware that is compatible with our software.

What is important here is not merely expanding HW sales themselves, but using HW as an entry point to drive adoption of high-margin software and continued usage. In other words, while using HW as the entry point, the structure is ultimately to develop into high-margin software and solutions.

To summarize, the previous fiscal year was not merely about an increase in projects but a strengthening of our business structure combining HW and SW with a multi-layered suite of Spatial Perception technologies for the Physical AI era—this served as the background for revenue growth and business expansion.

Ko: Next, as the second background to revenue growth, I will explain changes in the market environment.

The key point here is that, amid a shift to next-generation technology demand, our direction is beginning to align with market needs.

Currently, major changes are occurring in the “digital twin” and “mobile robot” domains.

In digital twins, photorealistic technology and AI utilization are advancing, expanding beyond mere 3D display to applications that understand and analyze real space with high precision. In addition, sensors and scanners are becoming more affordable, accelerating practical implementation.

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In the mobile robot domain, with the development of Physical AI, we are entering an era where robots act autonomously in the real world. In particular, along with the evolution of legged and humanoid robots, the importance of advanced spatial recognition and navigation technologies supporting them is increasing.

In such a market environment, our technological advancement and differentiated position are strengths in capturing demand.

Regarding our technological advancement, we have been engaged in next-generation domains such as photorealistic technology, AI utilization, and advanced robotics from an early stage.

As for our differentiated position, we can provide SW, HW, and solutions in an integrated manner, and furthermore, we have technical interaction with high value that can deploy technology across both digital twins and robots.

In other words, our strength is the ability to handle the integrated flow of understanding space, digitizing it, and operating robots.

The revenue growth in the previous fiscal year stemmed from this alignment between changes in market structure and our technological positioning.

Ko: I will now explain the details of revenue growth in the previous fiscal year against this background.

In the previous fiscal year, revenue grew on multiple fronts across both digital twins and robots.

We advanced HW package utilization and SW technology expansion, connecting these to business growth in digital twins and mobile robots.

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In digital twins, in addition to HW packages such as scanner equipment, the provision of Kudan PRISM, a facility management solution, progressed. In this domain, while securing short-term revenue, multi-layered growth combining SW, HW, and solutions is progressing.

On the other hand, in mobile robots, we advanced robot development through government projects and initiatives with major construction firms. These initiatives contribute not only to short-term revenue but also to strengthening mid- to long-term competitiveness and our development structure.

Looking at the breakdown of revenue growth, growth in the digital twin domain contributed significantly, with growth in the mobile robot domain added on top of this. While there were also negative impacts from the freezing or suspension of past projects, we achieved growth exceeding those.

To summarize, the previous fiscal year’s revenue growth was not merely a one-time factor but the result of simultaneously securing short-term revenue in digital twins and strengthening mid- to long-term competitiveness in mobile robots. We will connect this growth to a high-margin, software-centric business structure from the current fiscal year onward.

Ko: In addition, the previous fiscal year was one in which not only was revenue growth achieved, but profitability also improved significantly through improvements in our cost structure.

In FY2025, we significantly strengthened our development structure in order to expand into new technology domains for Physical AI. As a result, fixed costs temporarily increased, expanding from approximately JPY 970 million to JPY 1.17 billion on an annualized basis.

However, this was strategic investment for future growth, centered primarily on strengthening capabilities to respond to new technologies.

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Then, in the previous fiscal year, after that expansion phase, we executed cost optimization over the full year.

Specifically, through organizational optimization to reduce fixed costs and the freezing or outsourcing of non-core technology domains to optimize development costs, we reduced fixed costs to approximately JPY 950 million on an annualized basis.

What is important in the flow from FY2025 to FY2026 is that this is not simply about cost-cutting fluctuations but represents a strategic structural transformation aimed at growth.

In other words, in the previous fiscal year, while maintaining investment in core technologies directly tied to future competitiveness, we organized lower-priority areas and transitioned to a more efficient development structure.

Therefore, from the current fiscal year onward, having completed the transitional structural reform phase, we will transition to maintaining and strengthening a sustainable development structure while balancing profitability and growth.

Ko: Now I will explain our growth strategy for the current fiscal year (FY2027, ending March 2027).

While continuing and developing our previous policies, we will promote three strategies, newly adding “focus on high-gross-margin SW” and “providing data technology for Physical AI.”

First, strategy A: focus on high-gross-margin SW.

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Until now, we have been developing markets while utilizing HW packages. Going forward, while continuing to use HW sales as an entry point to drive adoption of high-margin software, we will focus on more profitable software sales.

In other words, while providing HW as the entry point, our policy is to ultimately maximize SW revenue with higher continuity and gross margins.

Next, strategy B: expansion of SW technology and solutions. This is a continuation from the previous fiscal year. In both the robot and digital twin domains, we will continue to advance technology development and business expansion.

In particular, we will broaden the scope of solutions offered while utilizing our suite of core technologies such as Spatial Perception, navigation, and photorealistic technology.

Then, strategy C, our new initiative for the current fiscal year, is “providing data technology for Physical AI.”

In Physical AI, large amounts of spatial behavior data are required for robots to learn and act in the real world. Leveraging our strength of having both robot and digital twin domains, we will provide data construction technology at their intersection.

This is not simply data sales but is positioned as a foundational technology for the Physical AI era—acquiring real-world data from robots, augmenting and validating it on digital twins, and utilizing it for AI training.

Ko: I will now explain our forecast for the current fiscal year (FY2027, ending March 2027).

The key point this fiscal year is that the transition from low-gross-margin hardware revenue to high-gross-margin software revenue is fully underway.

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As a result, while revenue is expected to temporarily decrease year-on-year, profitability will improve significantly, and the loss reduction will, in fact, accelerate.

Specifically, revenue is expected to be JPY 1,030 million. While this is a decrease from JPY 1,197 million in the previous fiscal year, this is primarily due to a decline in hardware revenue.

On the other hand, software revenue is expected to continue growing, with an anticipated yearon-year increase of approximately JPY 360 million. In other words, the revenue mix itself is shifting toward a more profitable form.

On the profit side, the effects of this structural transition will be significant.

Operating loss is expected to improve from a loss of JPY 586 million in the previous fiscal year to a loss of JPY 340 million in the current fiscal year. This represents a loss reduction of approximately JPY 250 million.

In particular, the profit improvement effect from focusing on SW alone is expected to be approximately JPY 350 million. Meanwhile, we will continue and expand R&D investment for future growth, and as a result, fixed costs are expected to increase by approximately JPY 80 million.

In other words, the current fiscal year is not simply about profit improvement through cost reduction, but a phase to make the business structure itself more profitable while continuing investment for the future.

The current fiscal year is a transitional period prioritizing profitability improvement over revenue scale. By shifting from HW-centric to SW-centric, we will connect to revenue growth with higher profitability and a return to profitability from the next fiscal year onward.

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Ko: I will explain each of the strategies for this fiscal year one by one.

The first is “focus on high-gross-margin SW.”

We develop our business by combining hardware and software, but in the mid- to long-term, we aim to maximize revenue based on the widespread adoption of our core software technology.

Therefore, rather than pursuing profit from hardware alone, we are taking a strategy of utilizing it as an entry point for market development and adoption promotion, then connecting to highmargin software revenue beyond that.

In the past business phases, we first proved the effectiveness of our software through market track record, and then advanced market development utilizing HW packages. As a result, in FY2026 (ended March 2026), the HW revenue ratio increased, and the SW ratio in gross profit declined to 56%.

However, this is a movement during a strategic transitional period.

From the current fiscal year (FY2027, ending March 2027), we will transition into a phase where we convert the previously expanded HW projects into more sustainable and profitable SW revenue.

As a result, the SW ratio in gross profit is expected to improve significantly to 89% this fiscal year.

Furthermore, from the next fiscal year onward, we plan to maintain a level of 90% or higher while transitioning to a sustainable revenue model centered on software.

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In other words, the current fiscal year is positioned as an important time to transition the business structure itself into a high-profitability model, rather than merely expanding revenue.

Ko: I will explain in a little more detail the impact of these strategic policies on the current fiscal year’s revenue outlook.

The key point is that some HW package sales originally expected this fiscal year were recognized earlier in the previous fiscal year due to the execution of our SW focus strategy.

Specifically, we had planned to transition to profit improvement through SW focus from this fiscal year, and under that premise, we had assumed revenue this fiscal year would be a slight increase of approximately JPY 1.13 billion.

However, in actual progress, due to the early execution of the SW focus strategy at the end of the previous fiscal year, some related HW sales were recognized earlier in FY2026 (ended March 2026), with an impact of approximately JPY 97 million.

As a result, while revenue in the previous fiscal year grew beyond plan, revenue in the current fiscal year is affected by the resulting pull-forward impact, resulting in a plan of JPY 1,030 million.

Therefore, this is not a deterioration of business but a transient impact due to fluctuations in revenue recognition timing. What is important is that the improvement in revenue structure through SW focus is already progressing ahead of schedule. This fiscal year, we will further advance that structural transition, and from the next fiscal year onward, we aim to connect to revenue growth with higher profitability and a return to profitability.

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Ko: Next, of the second strategic policy—expansion of SW technology and solutions—I will first explain the digital twin domain.

Centered on our digital twin solution “Kudan PRISM,” we are advancing the continuous expansion of our customer base and revenue.

PRISM is a solution aimed at improving the productivity of facility management, with the feature that it can solve issues that had been challenges in the past, such as data accuracy and operational practicality.

In particular, as shown in the image at the bottom left, the ability to digitize real space in 3D with high precision and execute various intelligent tasks within the space in place of humans is our strength in the Physical AI era.

As for results in the previous fiscal year, the number of customers increased by approximately 200% year-on-year. The number of countries where we operate also expanded to 3, with adoption progressing across diverse industries including manufacturing, logistics, construction, infrastructure, energy, and facility management.

Furthermore, an increasing number of projects are progressing from the PoC and proof-of-concept stage to the practical operation phase. As a result, a sustainable revenue model based on the SW platform has been established, with a 100% retention rate going into FY2027 (ending March 2027).

In addition, we are implementing advanced features that respond to the latest market needs and strengthening our comprehensive technology provision system combining SW, HW, and solutions.

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For the current fiscal year plan, we plan to further expand the number of customers by approximately 150% and to expand our footprint to about 10 countries. We will also expand into new industries such as real estate, telecommunications, and the public sector.

What is even more important is that we are aiming not only at expanding adoption but also at expanding sustainable revenue through actual operation.

In addition, we will collaborate with the third strategic policy promoted from this fiscal year— “providing data technology for Physical AI”—and, in the future, strengthen our expansion into the robot domain.

In other words, PRISM is not merely a digital twin product but plays an important role connecting to a data platform for Physical AI in the future.

Ko: I will now introduce the features of Kudan PRISM.

As background for PRISM, the areas of facility management, infrastructure inspection, and disaster prevention have high social demand, but traditional technologies had practical operational challenges.

Previously, 3D point cloud data was central, but utilization in the field was limited due to limitations in AI accuracy, large data volumes, and difficulties in system integration.

In contrast, Kudan PRISM combines spatial representation equivalent to human perception, reality-understanding AI such as semantic 3D recognition, and efficient data integration, converting real space into a form that is easy for AI to understand and utilize.

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Currently, we are deploying it across a wide range of industrial DX, including facility and equipment management, infrastructure inspection and maintenance, smart cities, and disaster response.

In particular, the strength is the ability to realize automation, efficiency improvement, and remote operation for field tasks that had been difficult to digitalize.

In addition, labor shortages, aging infrastructure, and expanding disaster prevention needs serve as tailwinds, and we expect further demand expansion going forward.

Ko: Next, I will explain the mobile robot domain.

Since the previous fiscal year, we have been strengthening foundational technology for autonomous movement for robots, and in the current fiscal year as well, we are continuing to expand revenue and project scale.

By way of background, while autonomous mobility for robots has traditionally centered on mathematical methods, approaches based on Physical AI utilizing AI models are now developing rapidly.

We are advancing the introduction of this Physical AI model ahead of others, and in the future, we plan to evolve into a hybrid type that combines and balances the stability of mathematical methods with the versatility of AI models.

As results in the previous fiscal year, on the technology side, we expanded from core SW to a suite of technologies and began providing foundational technology for autonomous movement for robots.

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On the project side, we are leading the development of autonomous movement SW platforms, primarily through government projects. Business collaboration toward the practical use of mobile robots is also progressing, including in industries such as construction.

In addition, by optimally integrating our proprietary algorithms—which have high accuracy, speed, and stability—with complementary technologies, we are also strengthening our competitive advantage.

In our plan for the current fiscal year, we will fully commence provision of perception-data-driven foundational technology, that is, the Physical AI model. In the mobile robot domain, we believe this will be a significantly leading initiative globally.

In addition, we expect revenue scale to increase by approximately 100% year-on-year, with the continuation and expansion of large-scale projects such as government projects.

Furthermore, by collaborating with the third strategic policy—“providing data technology for Physical AI”—we will strengthen our unique advantage including the utilization of digital twins.

In other words, we are in the stage of evolving from providing SLAM to becoming a robot intelligence platform for the Physical AI era.

Ko: Let me explain the background of the mobile robot market in a little more detail.

The key point is that the mobile robot market itself is enormous and continued significant growth is expected. On the other hand, many technological challenges remain for practical implementation, and demand for solutions to these is increasing.

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As shown in the upper left, the area where practical implementation has been possible with traditional technologies has been limited to approximately 3 to 5% of the total. This is because the focus has been on technologies premised on relatively simple environments.

However, in the actual market, as shown in the lower right, the ability to handle more complex environments is required.

For example, warehouses and factories where the environment changes frequently, spaces where indoor and outdoor are mixed, complex three-dimensional structures like construction sites, environments with many people and moving objects, long corridors with few features, and vast open spaces.

In such environments, stable operation is difficult with traditional robot technology alone, and next-generation environmental recognition and Physical AI technology are required.

Therefore, much of the mobile robot market, which is expected to grow to approximately JPY 300 trillion by 2040, is considered to be in this area requiring such advanced technologies.

Within this, we have a track record of commercializing Spatial Perception technologies, including SLAM, globally, and we believe we can maintain a competitive advantage in mobile robots for complex environments.

In other words, our distinctive feature is that we target the next-generation robot market used in “truly difficult sites,” not robots for simple environments.

Ko: I will explain the existing government project in the mobile robot domain.

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This project is a robot-oriented SW development project promoted by the Ministry of Economy, Trade and Industry and major construction industry players, and we are participating as the development lead.

Against the background of serious labor shortages in Japan, the government and industry are strengthening Physical AI and robot policies. In particular, in high-difficulty environments such as construction sites, the advancement of autonomous movement technology is indispensable.

This project is promoted across industries, centered on the “Construction RX Consortium” with construction sites as the starting point. Based on our track record of technical achievements, we are leading the development of the software platform that forms the core of robot autonomous movement, as a core technology leader.

This technology is expected to be deployed not only in the construction sector but also in a wider range of industries such as logistics, manufacturing, and infrastructure management in the future.

We consider this to be more than a mere individual project—it is a position to advance the social implementation of mobile robot and Physical AI foundational technology in Japan. Going forward, through continued collaboration with the government, this may also link with large-scale policies and industrial infrastructure development.

In other words, we are in the stage of strengthening our position not as a mere robot vendor but as a core technology player supporting Japan’s Physical AI and robot industry infrastructure.

Ko: Next, as the third strategic policy for this fiscal year, I will explain our new initiative, “providing data technology for Physical AI.”

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Traditional AI has been centered on “thinking intelligence” that handles data in digital space such as text, images, and code.

In contrast, Physical AI is AI that acts in real space, like robots. For this, large amounts of data on the real world—such as space and location, and the movements of people and objects—are required.

In other words, in Physical AI, “how much real-space data can be built” directly determines competitiveness.

What we provide here is data technology utilizing Spatial Perception.

Specifically:

• ・ Automated data acquisition through robot autonomous movement

• ・ Data quality validation fusing digital twins and robots

• ・ Data augmentation through utilization of digital twins

Through these, we will build a data foundation for Physical AI.

What is important here is that we have both “robots” and “digital twins.”

By acquiring real-world data from robots and reproducing, validating, and augmenting it on digital twins, we can generate higher-quality and larger-scale training data.

In other words, data technology is positioned as a new business domain at the intersection of robot technology and digital twin technology.

In addition, we believe this data market for Physical AI has the potential to grow to approximately JPY 20 trillion by 2035.

By providing integrated technology offerings in this area, we will strengthen our competitive advantage and long-term profitability in the Physical AI era.

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Ko: I will introduce some examples of currently ongoing projects.

A distinctive feature is that we are deploying technology across multiple markets and globally in both digital twins and robots.

In addition, the number of projects premised on actual operation—centered on digital twins—is increasing, and the number of projects progressing to full-scale deployment phases (services), such as commercial service provision and integration with core systems, rather than mere PoCs, is also increasing.

We believe that the insights and data gained from a wide range of projects mutually contribute to strengthening our technology, leading to the accumulation of competitive advantage for the Physical AI era.

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Ko: Lastly, I will explain our mid- to long-term growth outlook.

Until now, we have built up technical achievements and a customer base, centered on providing core technology, mainly SLAM.

As a result, from FY2021 (ended March 2021) to FY2026 (ended March 2026), revenue grew at an annual average of approximately 57%.

Currently, based on that core technology, we are expanding our business domains to SW solutions and HW packages. In particular, in the short term, while expanding the digital twin business and increasing the scale of robot projects, we emphasize multi-faceted revenue growth and profitability improvement.

As part of this, this fiscal year we are advancing our focus on high-gross-margin SW. Although revenue is temporarily decreasing, we plan to accelerate loss reduction through gross margin improvement.

And in the mid- to long-term, in line with the full-scale expansion of the Physical AI market itself, we aim for high-profitability growth through the proliferation of commercial technology and the expansion of SW sales.

In particular, going forward, we believe markets with a high software ratio—such as robot intelligence, autonomous movement, digital twins, and spatial data utilization—will expand.

Within this, with Spatial Perception at our core, we leverage our strength of being able to develop across robots, digital twins, and data technology, and aim to grow as a foundational technology company for the Physical AI era.

This concludes our financial results presentation.

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Thank you very much.

■Company Details Name: Kudan Inc. Securities Code: 4425 (TSE Growth) Representative: CEO Daiu Ko

■For more details, please contact us from here

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