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spk00: Good day ladies and gentlemen. Thank you for standing by and we warmly welcome you all to the Shao Ai first full year 2023 earnings conference call. Currently all participants are in listen only mode. Later we will conduct a question and answer session and instructions will follow at that time. As a reminder we are recording today's call. If you have any objections you may disconnect at this time. Now I will turn the call over to Berisha, IR Director of Shao Ai. Please proceed.
spk01: Thank you, Operator, and greetings to all participants. Welcome to Cell Ice 2023 Earnings Conference Call. Present with us today are Mr. Max Yuan, Chief Executive Officer, and Mrs. Callie Wong, Chief Financial Officer. We announced our 2023 unaudited financial results earlier today. The press release is available on the company's IR website, as well as from Newswire Services. A replay of this call will also be available in a few hours on our IR website. During this call, we will discuss our business outlook and make forward-looking statements. Please note that these comments are made under the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Also, the forward-looking statements are based on our predictions and expectations as of today. Actual events or results could differ materially due to some risks and uncertainties, including those mentioned in our filings with the SEC. The company does not assume any obligation to update any forward-looking statement except as required under applicable law. Also, please note that unless otherwise stated, all figures mentioned during the conference call are in U.S. dollars. With that, let me now turn the call over to your CEO, Max Yuan. Please go ahead, Max.
spk04: Thanks, Valerie. Good day, everyone, and thank you for joining us today. The year 2023 marked a turning point for the generative AI sector. with tremendous growth on the horizon. I think it is undeniable that this technology has the potential to revolutionize the entire technology sector and become an integral part of nearly every business sphere. As a game changer, AI holds immense value up for grabs. In terms of financial performance, 2023 was a year of stable growth for our company. Our total revenue reached an impressive 59.2 million, reflecting a remarkable year-on-year increase of 22.8%. This growth was primarily driven by our strategic focus on AI model services, particularly our Huazhang LLM, which spearheaded the growth of our mass business by 48.5%, reaching $19.2 million. Simultaneously, our non-mass business also experienced healthy growth, with revenues increasing by 13.4% to reach $40 million. I am delighted to announce that 2023 has been a pivotal year for us, marked by groundbreaking initiatives If you were present at our 2023 Interim Results Call, you may recall the exciting news I shared that in July 2023, we launched our own JGPT, Huazhang Universal Large Language Model. In simple terms, it encompasses a wide range of capabilities and addresses the key challenges faced by global AI models. It is designed to be controllable, customizable, and deliverable. Another highly promising initiative I want to highlight is our Huazhang ecosystem, which was built upon the strong foundation of our Huazhang LAM and was introduced in October 2023. This ecosystem represents a revolutionary development with significant implications for the industry. Also, it not only streamlined our processes but also empowered us to provide tailor-made solutions to our customers, enabling them to create unique and branded conversational AI experiences. In just a few months since its launch, we have successfully implemented the Huazhang ecosystem, facilitating the commercialization efforts of our partners in various industries. The system is now collaborating with thousands of ecosystem partners across more than 50 industry fields, including finance, healthcare, automobile, and manufacturing. This success validates the commercialization path of the Huazhang ecosystem. With such robust support, I eagerly anticipate unlocking significant commercial potential and generating substantial returns for the company in the near future. Next, I want to emphasize the critical importance of strong research and development capability for our ongoing success and our ability to create innovative solutions in the rapidly evolving field of AI technology. We are dedicated to meeting the needs of our customers by listening to their feedback and requests and responding with new solutions and enhanced features. As of March Our research and development team consists of 158 talented individuals, making up 56.2% of our overall workforce. Among them, we have 104 bachelor's degree holders, 17 master's degree holders, and 7 individuals with many of our senior engineers have accumulated more than a decade of experience in the computer, Internet and AI industries. Additionally, we collaborate with a number of AI experts from renowned universities and research institutes. I am pleased to share with you that as of December 31, 2023, we had a total of 258 patent applications, including pending expelled and transferred cases, excluding granted patents. We also abated 318 patent grants and registered 137 software copyrights. In 2023 alone, we filed 36 new patent applications, received 39 patent grants, and registered 7 software copyrights. Among these, there were 6 patent applications specifically related to large models, all filed in 2003. and three registered software copyrights in the same category. Additionally, there were two patent applications related to OOTD Fusion, our upcoming new network architecture for realistic and controllable virtual try-on. It is worth noting the high popularity of OOTD on GitHub and the discussions on PlatformX. indicating significant attention from potential consumers and promising prospects for product commercialization. To further strengthen our capabilities, we have established joint laboratories with SME institutions such as the Institute of Software of the Chinese Academy of Science, is China Normal University and Hong Kong University of Science and Technology. Furthermore, we have fostered close partnerships with Tsinghua University, Fudan University, Shanghai Jiao Tong University, Beijing University of Posts and Telecommunications and Peking University. Together, through our own Weavering commitment to research and development, we are poised to conquer new horizons and shape the future of AI technology. Moving on to another key strategic focus, globalization. Our efforts towards global expansion gained momentum with the establishment of two overseas subsidiaries in the US and the United Arab Emirates. These strategic initiatives are integral to our vision of becoming a global leader in AI technology, enabling us to better serve our customers and seize opportunities in new markets. In conclusion, 2023 was a year of unprecedented growth, innovation and strategic expansion for HIAI. As we embark on the journey ahead, fueled by the successes of the past year, we are confident that we are well positioned to continue our trajectory of growth and leadership in the AI industry. Looking ahead into In 2024, we expect that the Huazhang LIM is set to further strengthen its commercialization efforts. Delving deeper into understanding and meeting customer needs, we expect our B2B operations to continue to exhibit a robust and consistent growth strategy with around 20% of growth rate on a yearly basis. At the same time, the advent of AI has significantly expanded the potential for AI in consumer applications. We believe the integration of AI models and consumer applications has become more seamless and impactful driven innovation and meeting consumer demand more effectively. Hence, we further expand our business into the B2C market. On the front of R&D, we will continue to make endeavors and investments to strengthen our product capabilities. Collaborative efforts with our partners and customers to integrate our large language model will be a central part of our approach. As you may have noticed, we have recently announced very exciting progress regarding several new products, including OOT diffusion, as I mentioned earlier, is a new network architecture for realistic and controllable virtual trials, and this daily investor-focused platform that utilizes advanced AI technology to provide capital market answers and insights on par with professional investors, supporting investment decision-making, our commitment to pushing boundaries and revolutionizing Industries will propel us towards a future where AI has a profound impact on people's lives. Together with our partners and customers, we will continue to embrace new challenges and seize opportunities to shape the world through cutting-edge AI solutions. Now, let me turn the call over to our CFO Kelly to go over our financials.
spk11: Thank you, Max, and welcome to everyone on the call. Before I go into numbers, please know that all numbers presented are in U.S. dollars, and all comprehensions are on a year-over-year basis unless otherwise stated. For a more comprehensive breakdown, please refer to our earnings press release. Driven by strong digital transformation needs in enterprises, we've hit a record top line for the year. we are taking about a 22.8% growth from the previous year. Not just that, the robust performance also translated into a 270 base point expansion, bringing our growth margin to an expansive 66.6%. And here's the cherry on top. As pioneers at the frontier of cognitive AI, We've unveiled our large language model. This innovative model has propelled our R&D investments to unprecedented hits, underscoring our unvarying dedication to harness and spearhead the transformative power of core AI technology. With that, we expect to capitalize on vast opportunities in the AI realm. Bringing it down further, the increase in the net revenue was primarily due to the increase sales of cloud platform products. These numbers help offset the declines in other areas led by a continued shift towards subscription-based cloud platform products from one-time software purchases. Keep in mind that some of our revenue channels like tech development services and software purchases typically shown in the last quarter of the year. I'd also like to bring to your attention that the rise in the cloud platform products is actually driven by the development of our mass business. As by nature, our mass business is mostly delivered through cloud platform products. In 2023, our mass business grew by 48.5%, reaching $19.2 million, with the primary contributions attributed to our huazhang large-language model. At the same time, the mass business accounted for over 30% of the total revenue for the first time. On the profits front, we hit $39.4 million in gross profit, making a 28% increase from $30.8 million a year early. Moreover, our growth margin expansion unfolded as planned, standing at 66.6% up from 63.9% in the previous year. The increase was primarily attributed to the significant increase in the proportion of revenues from sales of cloud platform products with a higher profit margin of 74.8%. Once again, I need to point it out that it was mainly driven by the strong growth of mass business. Embodied the core concept of providing AI models as a service to users rather than directly selling the models themselves. Our mass business model effectively reduced the barriers to using AI technology in building a broader range of business and developers to conveniently assess the leverage AI models. Now, moving to our operating expenses. Our total operating expenses were $61.3 million, up 18.7% from $33.9 million in the same period last year. Still, the majority of our operating expense increase was driven by a 118.3% surge in R&D expenses, which reached $52.4 million. This reflects our focused investment in the advanced large-language model. We accept our latest release, Huazhong, will play a priority role in our long-term growth as our co-creating model matrix, owning the subject to the foregoing as well as the pipeline of announced products under development, and all other continuing infrastructure growth. We currently accept our R&D investment to mainly at around 50% of our total revenue. As a result, our operating loss for 2023 was $21.9 million compared with an operating loss of $3.1 million a year early. Net loss was $27 million compared to a net loss of 6 million in 2022. Looking ahead, we remain committed to managing costs and enhancing efficiency as we focus on allocating resources strategically, particularly in the priority area of AI technology R&D. We believe this approach will position us well for continued growth and success. Thank you for your attention. We will now open the floor for questions. Operator, please go ahead.
spk00: Thank you. To ask a question, you will need to press star 1 and 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 and 1 again. Please stand by while we compile the Q&A roster. Thank you. We will now take our first question. This is from the line of Brian Lantier from Zach's Small Cap Research. Please go ahead.
spk18: Good evening and good morning to those joining from the East Coast. I just wanted to touch base on the OOT diffusion project, get a little bit more color maybe around when you see that becoming a commercial product. and what you think the eventual pricing model will look like. Will it be principally a cloud service, or do you think that could be a new model that you'd be looking at?
spk01: Thank you for your question, Brian. I'll need to translate a little bit here for our management team for better communication efficiency. Mr. Yuan, I will translate it for you first. Brian from Zax Capital has a question about our OOTD diffusion model. First of all, he asked us when this product will be put into operation and what our business model will be like. For example, what kind of level will it be at? As for this product, Will it introduce a new business model? Or will it follow the old business model? That's probably the question. First of all, thank you very much for this question.
spk04: First of all, our online time should be in May. This is the first point. The second point is that such a product, its payment model, first of all, it is a consumer product.
spk01: I'll translate the answer from Max. So first, as for the product for OOTD, it is actually a very new product. So we're going to introduce a new business model. First of all, the product is going to be launched in May very soon. And as for a new product, it's targeting a consumer audience. So the business model will be similar to that of the GPTs, will be conducted based on the subscription. And as for the first edition will be coming from the subscription, but later there will be ones of generative business model as well, based on the picture they generated, the service they get, they get additional payment as well. So that is the information for understanding. We hope we answered your question. Thank you, Brian.
spk18: Great. Thank you. And if I could just follow up with one other question regarding the, I think you called it the DIP, the daily investor focus. I haven't seen too much information on that. Will that be a consumer product for everyday investors, or would that be a product you would be marketing to some of your banking clients?
spk01: All right, thank you. Thank you.
spk04: First of all, DIV is a platform based on the big model and RPA. It's a platform that combines the two. In the future, this platform will extend a lot of applications for different scenarios, including for relevant source reports, paper writing, and some other things. for a large number of data, including text, knowledge, and processing. It may be applied to different distribution markets. Next month, we will also launch the first product on the DIF platform. We will soon announce that this product will basically have a better data analysis or corresponding reference for individual investors in the United States. Thank you, Mr. Yuan. Brian, so for your question as regarding to this daily invest focus,
spk01: This product is actually a new platform dedicated to deliver as an agent or co-pilot for our potential customers. The first application scenario will be located in the financial industries. But of course, as a platform, it will be further expanded into different scenarios. For example, not only for the finance industry, like analysis and investment analysis, but rather than will be further expanded into, you know, the research report writing, the asset writing, or even the market and the market analysis reports, etc. All of the vertical industry applications, the scenarios that might rely on the report writing scenarios we cannot further penetrate into. So as for this first scenario of the financial industry, we will be introducing the very first product based on this platform in May. So this product is more like a daily report first, because you can see the product name itself is called Daily Best Focus. So this first product will be firmly rely on the target audience or the potential consumers from the retail investor side. We help them to collect market information, sentiment, market sentiment, or even sometimes the per incident alert from the capital market side. to give our retail investors a fully data support on their investment. May they're more confident, may they're resourceful upon the data side, as well as the information side. So, this platform is developed based on our large model together with the multi-agent workflow, the agentic workflow and also the multi-agent system. One of these agents is using the RPAs and also the others are utilizing the data analysis, data mining, and the different agents being in the queue to handling the process based on our consumer's request. So it's going to be a very new business model as well as a platform that we're going to introduce to our investors. Sorry, our investors. And then we were hoping the AI is really making their life much better, making their investment much easier to give them more rights and access to the information in the market. So that would be an answer to a question.
spk13: Thank you.
spk17: Great. Thank you so much for that.
spk00: Thank you. We will now take our next question. Please stand by. This is from the line of Wilson Liu from 4Asian Network, sorry, 4Asian Investment. Please go ahead.
spk06: Yes, this is Wilson, and it sounds very attractive and interesting. So I have a question for you. I would like to ask, how do you view the future development trend of the big data model industry? Thank you.
spk13: All right, thank you, Wilson.
spk01: I'll translate for Max as well.
spk12: Wilson's first question is, how do we view the future trend of the big model industry?
spk04: Our understanding of the big model is that before the big model, the most important thing for the AI industry This obstacle is that AI technology cannot provide such a chance for all industries to transform. Maybe we can only choose some specific industries. But with the outbreak of the big model in the past two years, we will see that the big model has the ability to push all industries to explode at the same time. Of course, today, the big model has different development trends and views around the world. The first view may be that the big model has a relationship with AGI. There are companies that talk about the future of AGI. But from our point of view, we don't think that AGI can be decided by the big model. Because in the past 60 years, the underlying framework of AI has not been broken. We don't think that the big model can achieve AGI. But on the other hand, the biggest value of the big model is what I just mentioned. The big model is already capable of can provide a huge opportunity to reduce the cost. So today, for the big model, the development of the big model, because how to commercialize the transformation, this will be the most important question. And how to reduce the cost of the big model more effectively. So last year, when we released our own large model, we talked about the first one to be controllable, how to control the illusion of the big model, This is the first point. The second point is to be customizable. Because all large models can eventually enter every scene, every industry, it must be able to, and it must be required to be satisfied with such a specific demand in the industry. The third is to be affordable. Because today it is not every company that can spend $2 billion to buy a few hundred thousand GPUs to deal with this matter. And the global open source community is also trying to use small models to achieve this cost on a large scale. This is a trend. So, in summary, in the future of the large model, the entire artificial intelligence industry, because of the outbreak of the large model, we have entered a high-speed growth, and all industries need to be AI-supported at this stage. This is already an undeniable fact. On the other hand, the large model does not mean that if you invest a lot and continue to invest, there will be AGI. So today's commercial transformation may require us to use a more controllable, customizable, and affordable way. With lower cost and higher efficiency, we can use big models, small models, data, and application scenarios to combine these comprehensive advantages, so that we can accelerate the transformation of the C-end and B-end. This may be a very important point for the development of the entire big model in the future. Otherwise, the big model will be just a development technology in the past, and if it cannot be transformed, it will be meaningless for the entire future development trend.
spk01: Yes, I will do the translation right now. So here's the conclusion first, Wilson, is that it is the time point for the commercialization of large junction model and AI technologies. The general thinking in the industry is that we need to create AGI, one must stack up scale and computational power, and with the notion that the larger the model, that the better its performance, which is a scaling law, the bigger the better. The idea is that the bigger the model, the better it works. But to be honest, we are not totally sold on the idea. There's a catch, although, but it's expensive. The bigger the model, the more it costs to train it. So you need a lot of computing power and data, and there's no easy way around it. So it's like trying to turn lead into gold. It takes a lot of trial and error. And that means a lot of computing power. So because of this, we are considering the most important thing to do right now is to deliver based on the architecture, the technology framework we have, the large model, and we delivered the model that can be customized, can be delivered with cost effective, and also can be commercialized. So what we do right now is we were considering, like, for example, for business-to-business scenarios, the enterprise-level large-language models, we do not require such high performance. You don't need a Canon to show this barrel. So as the current capability of large-language models is already sufficient to significantly enhance the corporate operation efficiency. So what matters more is whether it makes economic sense and if the experience is good. So the key to large language model is always to tie them into business needs and process in a way that makes sense. And for the consumer side, with the development of large language model, the applicable scenarios of the AI products are rapidly increasing. We're seeing more and more uses of AI. So it's like a blue ocean. So this year, we might just see more really popular apps and that develop based on the large model. For example, like the previous product we've been introduced, the data invest focus, and also the OOT diffusion. All of these are the seaside that the company is trying to explore on. So we hope we answered your question. Thank you.
spk00: Awesome. Thank you. We'll now take our next question. This is from Anthony Chang from BE Investment. Please go ahead.
spk05: Hi. Dear management, thank you for the answers. I would like to follow up your previous answer that there are indeed many different application scenarios for your business model. I can hear that you have clients in financial institutions, telecom and pharmaceutical manufacturing, local government, but which client base are you going to focus more and what are your strategies for those client base? Thank you.
spk01: Yeah, thank you. I'll translate here. Anthony just asked a question.
spk12: Currently, our company has a wide range of customers.
spk01: The business situation we design, including the scene, including the pharmacy, or the three-digit telecommunications business, the bank, we have a lot of customers.
spk12: Including the local government, we have a lot of customers. The question is, which part will our future customers focus on? Our main strategy is to focus on the clients in which scenarios. This is probably a question for Anthony. First of all, in the future, the entire product will be divided into 2B and 2C.
spk04: We will focus more on the division of the 2B industry. In the 2B industry, despite being a large model, it is capable of promoting all the industries. But we also agree with the previous question. In terms of the industry, we still have some focus. In terms of the focus industry, we will mainly focus on the call center, smart finance, and other industries with high value. which are relatively good in terms of infrastructure and high in terms of digitalization. We have a very good collection in the past. We have more than 1,000 large-scale customers. They may come from the call center industry. In addition, there are many banks, securities, and insurance that come from the financial industry. Whether it is in the domestic market or in the overseas market, it is a globalized industry, and it is a very huge industry that continues to grow and AI can replenish. In these industries, we will continue to dig deeper and further develop the technology of large models. We will be able to embrace AI technology in these industries. At the same time, we will be able to quickly refresh and change large models to further release the great value of the industry itself. In addition, we will focus on the new consumer market. In the past, in the development of artificial intelligence technology, the consumer market did not have a particularly large display. But today, in the new technology of large-scale, we will see that, in fact, including the examples we just mentioned, such as DIF, DIAF, Daily Invest, Investor Focus, including OOTD, which can be very direct in the field of consumers, and can quickly generate transformational value. It also includes some hardware. In the next two months, we may also have some hardware, including ESG, that will be transferred directly to the hands of consumers. Therefore, in the 2B industry, we will focus on very important and strong foundations, including the huge industry that can continue to grow. At the same time, we will consider that the original AIS technology cannot cover the C-end part, including the out-of-sea part. We will further invest and expand.
spk01: So Anthony, thank you for your question. Here's a conclusion first. Your question is actually a very good one, because it's a very important question which customer we're going to focus on. So first, we wanted to answer that there's two dimensions. First one is actually business to business. And second one is actually business to consumers. So like you've been previously talked about, we have a very large customer base, we covered the industry from manufacturing to finance and also to the couriers, maybe all of these clients are within our customer base. So for these customer bases, we're going to dig deeper into their customer needs, and we will rely on their business development process, their strategies, to see whether or not they are strong enough to carry more AI technology applications. And we will focus on their pain point to deliver customized large-function models, combined and integrated AI solutions. So for the business-to-business scenario, we will further rely on 1,000 delivery cases, which we acquired within this 20 years, more than 20 years journey in a commercialization experience. and we will be further dig on to deliver better application and solutions to them. However, based on the new technology development process, we believe the large-range model would be a great turning point for the application in the business-to-consumers scenarios. So we will further focus on the 2C side. For example, like the previous product we've been mentioning about, the OOT Diffusion, it's actually the technology name, it's not the product name itself. The OOT Diffusion is the algorithm we're going to introduce to our consumers. We'll deliver a product based on their algorithm. And also the DIFF, we've been privileged to talk about it, the daily invest focus, we're going to deliver to the market very soon in May as well. Other than that, we also have the hardware that's focusing on the ESG side. You know, our company's vision is always to improve everyone's lives with AI technologies. So we wanted to deliver the hardware products that really solve the pain point as well as the issues in the disabled or the under-deserved markets demand. So we're going to introduce this product very soon, as well as in May, where we're going to press out release for this ESG product. And we're going to constantly introduce new products in the 2C side to explore the application and the market on that part. So here's a nutshell that for B-side, we'll dig deeper into our customer base and to give them better customized, better experienced products based on large-range model and the other related AI technologies. And for the 2C side, we're going to further explore into the consumer's scenarios and focus on the different underdeserved business segment or the mass consumption business segment, we'll make sure that all of our products are entering into the right commercialization process. So here's the answer to your question.
spk13: Thank you.
spk00: Thank you. We'll now take the next question. This is from Isaac Chan from Han Grand Holding Group Limited. Please go ahead.
spk08: Thank you for picking my question.
spk07: We have noticed that the company has disclosed its plans to initiate overseas expansion and expand into the consumer market. Could you provide information regarding the company's B2C strategy and overseas expansion strategy for this year? Thank you.
spk01: Thank you, Isaac. Mr. Yuan, his question is, we also released the B2C strategy this year. What is our specific strategy in this regard, or what is the specific strategy to expand the market? It's probably such a question.
spk15: President Yuan, can you hear me?
spk04: Okay. Sorry, I was out of tune. First of all, we believe that a very important business strategy this year is all about the transformation of the business model. Based on this transformation, we believe that in addition to the traditional B2B market, we will continue to grow and maintain a steady growth. In addition, there are two very key strategies. One is the overseas market, the international market. The other is the B2C market, which is aimed at consumers, and provides a large number of sustainable products. As for the overseas market, from last year, after the market was launched, we conducted a basic survey of the global market, including the Middle East market, Southeast Asia market, and the European and American markets. we will find a very interesting phenomenon. In fact, the more developed countries and regions in the world, from the point of view of AI and technology applications, I don't know how everyone feels. In fact, since China started moving the Internet, applications have been leading the world. So today, in all the developed countries and regions around the world, we will see that there is a very strong demand in the market. But in fact, from the point of view of applications, is far from being satisfied. Therefore, for us, in the past 20 years, there have been very successful and mature applications in the entire China region. We are very confident that we can quickly push these cases and applications to the global market. Regarding the layout of the global market, in fact, we have completed the structural changes and layout of the company in the Middle East and the United States. So, we will continue to promote mature products, including innovative products, to the international market. So, this is the first international strategy. The structure of the company has been completed. The whole globalization or the strategic layout of the key countries and regions. The rest will be in the second half of the year. You will see a lot of QC and QB products directly facing the overseas market. These products will be presented one after another. This is the first one. The second one, As for the consumer product, as we mentioned before, the consumer product is a very important part of the ability of the big model today. It is also a very important direction of how AI can really explode. So, including what we talked about, based on OOTD technology, we will soon launch new applications for consumers, such as our past big model, including RPA, including a technology platform based on in-depth learning, such as DIV. We will directly focus on these investors. There will be some very profound market analysis and market insights to give them reference. Of course, in the second half of this year, we will have a very clear and complete pipeline. We hope that in a very short time, there will be new products that can continually enter the market. For XiaoAi, we are not an application company. We are a company that has a complete core of large-scale basic capabilities. For large-scale, the most important thing is to be able to complete an application ecosystem. At the beginning of the construction of this application ecosystem, there will be some innovative products that will continue to invest on this platform. So I believe that we ourselves, including our eco-cooperative partners, will have a lot of products in the second half of the year. This is why we say that internationalization and the C-end market are two very important strategic strategies for AI large-scale transformation this year.
spk01: Thank you, Yanzong. Thank you, Isaac, for your question. So first of all, we wanted to answer your question one by one. First of all, I said regarding to the overseas business expansion strategy, First of all, our topic today is always centered with the commercialization. Based on the B2B market, we will still dig deeper to make sure that we have a robust and steady growth upon our original customer base, but for the overseas one, is that we've already adjusted our strategies. We've been conducting a lot of market analysis and research upon the global AI application scenarios, including the MENA area, Southeast Asia, as well as the United States and Europe. There's a very interesting phenomenon that the one that are more developed in R&D standard, R&D level or R&D performance, that the AI application is, however, not so satisfying. So there is a blank area between the technology and the actual application. So we think our company is actually quite good to deliver. We are quite experienced. So we're going to bring more mature and better experienced products to the overseas market. So our corporate structure has adjusted accordingly for our overseas expansion. So at the end of this, at the second half of this year, we're going to see more and more product we're going to bring to the overseas market. to further enhance and expand our product matrix and product lines. So the second point is about the consumer side. This year, we're thinking the AI capabilities is now at a specific time point that can enable these consumer side products to be more satisfying and better experienced. So based on the more applications, based on the LLM technology framework, as well as RPAs and also deep learning, all of these technologies, we're going to utilize those and to deliver better product to our consumers. So regarding to the product we've been introduced previously, it's like DEEP and OOTDs, that'll be the first two application we introduced to the market, and then there will be more. So, in a nutshell, the B2C and international expansion that we are, we've been firmly believe that we will leverage on the robust capabilities of AI technologies and we will witness a significant expansion in B2C market as well as the consumer market. Especially, we wanted to further, you know, highlight on the end goal of the company that is really delivered a product of the AI for good. So, our mission is to ensure the AI technology is not only transformative but also inclusive. to real creating the solutions, not just technologically advanced, but also empathetic and accessible. So by doing so, we aim to make a real difference in people's lives, bringing AI technologies to those who need it the most and improving their quality of life. across the board globally from B2B to B2C. So yeah, that is our strategies and answers to your questions.
spk13: Thank you.
spk00: Thank you. We will now take our next question. This is from Zheng Yang from BE Investment. Please go ahead.
spk10: Hi, first, thanks for your presentation. And I have some question regarding IMD investment. So as we know, the IMD is very important for the high tech company like Xiao'ai. Well, I'm just curious about how much is your IMD investment? And after the investment, when are you expect to turn the profit? Well, in the meantime, Would there have the liquid gap? Thanks. Thank you, Teresa.
spk01: This question goes back to Kelly. Okay.
spk11: Okay, thank you for the question. First of all, in terms of R&D investment, in 2024, we expect R&D investment to remain at a level of 50% of revenue, because we still need to maintain the advantage of such a basic sustainability. And then the main direction of R&D investment in the company is still this mass product and large-scale model. But of course, we will also use commercialization as the premise, and we will consider the consideration of this cost ratio and ROI in this regard. For the profit, first of all, it is divided into several directions to consider. First of all, in terms of income, most of our income in 2023 comes from QB and China. In 2024, we expect to have a 20% online growth in this area. At the same time, we are also actively developing overseas business. In 2024, we also expect to bring some increased business. In terms of operating expenses, in 2023, our sales and management expenses have decreased by 15%. As our revenue scale improves, we expect that the operating efficiency in 2024 will improve. Based on the above factors, we expect that in 2024, there may be a chance to achieve a large-scale reduction in losses and even a chance to achieve profit. Then we will continue to use this long-term collection of technical strength to combine this market demand to realize the commercial transformation of technology. At the same time, by continuously launching new products, expanding the product line, and improving the quality of the products, we will also create a sustainable business growth curve. We will also strive to improve efficiency, operating efficiency, and strengthen our operating capacity. In this way, we look forward to using better operating results to reward our shareholders. Thank you.
spk01: Teresa, here's the answer to your question. First of all, we will be utilizing on our large customer base, then we will anticipate a continued growth estimation upon the TB side. However, our revenue from this segment has been robust and we expected to sustain a solid growth again on next year's basis, around 20%. So this projection will be reflected on our confidence in the strength of our current business operation and the potential of the Chinese market. And also, that is not only for the 2B side. Like the 2C side we've been previously talked about, there will be more product introduced to the market. We're utilizing this wolf pack strategy, you know, to introduce one application, then another. There will be a lot of application going to be introduced to the market. There will be anticipated a revenue, incremental revenue will be generated from the 2C side as well. So in terms of the R&D investment that you previously asked about, currently speaking there's around 50% estimation, 50% of our revenue will go into the investment of our R&D. It's going to remain at a significant level, but going to be lesser in terms of the ratio of the R&D fees compared to last year. So our primary focus on R&D investment will be still in two areas. One, MUST, the model as a service product, and the development of Huazhang LLM. So these initiatives are the forefront of our technology offerings and are crucial for maintaining our competitive edge in the AI industry. As well as for the projection and estimation for the profitabilities, First of all, the revenue scale, like we've been previously talking about, there's going to be a 20% of revenue growth from B2B side and also domestic market side. But there will be actual additional upside from ROTC side as well as the overseas market. As for the operation expenses, in 2023, our SG&A expense rate was already being reduced to 15%. So with the expansion of our revenue scale, we expect the operational efficiency will be further continued, and there might be a further improvement in 2024 as well. And for the R&D investment, we still talk about there will be around 50% of the revenue goes into research and development to maintain technological edge. So based on that, we anticipate the company could significantly reduce losses in 2024 and may even turn a profit. So in terms of cash flow, with the increased revenue and optimized cost, we expect operating cash flow to become positive. So we will continue to leverage on our long-term technological accumulation aligned with the market demand to commercialize our technology by continuously Continuously launching new products, expanding our product lines, and perfecting our product matrix, we aim to create a sustainable growth curve for our business. In a nutshell, our financial forecast and strategic plans reflect our commitment to a balanced approach, sustaining our core business while pursuing new business opportunities, and investing in innovation with a keen focus on our commercial viabilities. So we believe that this strategy will enable us to continue our growth journey, to deliver value to our stakeholders, and to make a positive impact in the field of AI technologies. Thank you for your question.
spk00: Thank you. Seeing no more questions in the queue, let me turn the call back to Mr. Yuan for closing remarks.
spk03: Thank you, operator, and thank you all for participating on today's call and for your support.
spk00: Thank you all again. This concludes the call. You may now disconnect. you Thank you. Thank you. you Amen. Thank you. you Good day ladies and gentlemen. Thank you for standing by and we warmly welcome you all to the Shao Ai first full year 2023 earnings conference call. Currently all participants are in listen only mode. Later we will conduct a question and answer session and instructions will follow at that time. As a reminder we are recording today's call. If you have any objections you may disconnect at this time. Now I will turn the call over to Berisha, IR Director of Shao Ai. Please proceed.
spk01: Thank you, Operator, and greetings to all participants. Welcome to Cell Ice 2023 Earnings Conference Call. Present with us today are Mr. Max Yuan, Chief Executive Officer, and Mrs. Kelly Wong, Chief Financial Officer. We announced our 2023 unaudited financial results earlier today. The press release is available on the company's IR website, as well as from Newswire Services. A replay of this call will also be available in a few hours on our IR website. During this call, we will discuss our business outlook and make forward-looking statements. Please note that these comments are made under the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Also, the forward-looking statements are based on our predictions and expectations as of today. Actual events or results could differ materially due to some risks and uncertainties, including those mentioned in our filings with the SEC. The company does not assume any obligation to update any forward-looking statement except as required under applicable law. Also, please note that unless otherwise stated, all figures mentioned during the conference call are in U.S. dollars. With that, let me now turn the call over to your CEO, Max Yuan. Please go ahead, Max.
spk04: Thanks, Valerie. Good day, everyone, and thank you for joining us today. The year 2023 marked a turning point for the generative AI sector. with tremendous growth on the horizon. I think it is undeniable that this technology has the potential to revolutionize the entire technology sector and become an integral part of nearly every business sphere. As a game changer, AI holds immense value up for grabs. In terms of financial performance, 2023 was a year of stable growth for our company. Our total revenue reached an impressive 59.2 million, reflecting a remarkable year-on-year increase of 22.8%. This growth was primarily driven by our strategic focus on AI model services, particularly our Huazhang LLM, which spearheaded the growth of our mass business by 48.5%, reaching $19.2 million. Simultaneously, our non-mass business also experienced healthy growth, with revenues increasing by 13.4% to reach $40 million. I am delighted to announce that 2023 has been a pivotal year for us, marked by groundbreaking initiatives If you were present at our 2023 Interim Results Call, you may recall the exciting news I shared that in July 2023, we launched our own JGPT, Huazhang Universal Large Language Model. In simple terms, it encompasses a wide range of capabilities and addresses the key challenges faced by global AI models. It is designed to be controllable, customizable, and deliverable. Another highly promising initiative I want to highlight is our Huazhang ecosystem, which was built upon the strong foundation of our Huazhang LAM and was introduced in October 2023. This ecosystem represents a revolutionary development with significant implications for the industry. Also, it not only streamlined our processes but also empowered us to provide tailor-made solutions to our customers, enabling them to create unique and branded conversational AI experiences. In just a few months since its launch, we have successfully implemented the Huazhang ecosystem, facilitating the commercialization efforts of our partners in various industries. The system is now collaborating with thousands of ecosystem partners across more than 50 industry fields, including finance, healthcare, automobile, and manufacturing. This success validates the commercialization path of the Huazhang ecosystem. With such robust support, I eagerly anticipate unlocking significant commercial potential and generating substantial returns for the company in the near future. Next, I want to emphasize the critical importance of strong research and development capability for our ongoing success and our ability to create innovative solutions in the rapidly evolving field of AI technology. We are dedicated to meeting the needs of our customers by listening to their feedback and requests and responding with new solutions and enhanced features. As of March, Our research and development team consists of 158 talented individuals, making up 56.2% of our overall workforce. Among them, we have 104 bachelor's degree holders, 17 master's degree holders, and 7 individuals with many of our senior engineers have accumulated more than a decade of experience in the computer, Internet and AI industries. Additionally, we collaborate with a number of AI experts from renowned universities and research institutes. I am pleased to share with you that as of December 31, 2023, we had a total of 258 patent applications, including pending expelled and transferred cases, excluding granted patents. We also abated 318 patent grants and registered 137 software copyrights. In 2023 alone, we filed 36 new patent applications, received 39 patent grants, and registered 7 software copyrights. Among these, there were 6 patent applications specifically related to large models, all filed in 2003. and three registered software copyrights in the same category. Additionally, there were two patent applications related to OOTD Fusion, our upcoming new network architecture for realistic and controllable virtual try-on. It is worth noting the high popularity of OOTD on GitHub and the discussions on PlatformX. indicating significant attention from potential consumers and promising prospects for product commercialization. To further strengthen our capabilities, we have established joint laboratories with SME institutions such as the Institute of Software of the Chinese Academy of Science, China Normal University and Hong Kong University of Science and Technology. Furthermore, we have fostered close partnerships with Tsinghua University, Fudan University, Shanghai Jiao Tong University, Beijing University of Posts and Telecommunications, and Peking University. Together, through our own Weavering commitment to research and development, we are poised to conquer new horizons and shape the future of AI technology. Moving on to another key strategic focus, globalization. Our efforts towards global expansion gained momentum with the establishment of two overseas subsidiaries in the US and the United Arab Emirates. These strategic initiatives are integral to our vision of becoming a global leader in AI technology, enabling us to better serve our customers and seize opportunities in new markets. In conclusion, 2023 was a year of unprecedented growth, innovation and strategic expansion for HIAI. As we embark on the journey ahead, fueled by the successes of the past year, we are confident that we are well positioned to continue our trajectory of growth and leadership in the AI industry. Looking ahead into In 2024, we expect that the Huazhang LIM is set to further strengthen its commercialization efforts. Delving deeper into understanding and meeting customer needs, we expect our B2B operations to continue to exhibit a robust and consistent growth strategy with around 20% of growth rate on a yearly basis. At the same time, the advent of AI has significantly expanded the potential for AI in consumer applications. We believe the integration of AI models and consumer applications has become more seamless and impactful driven innovation and meeting consumer demand more effectively. Hence, we further expand our business into the B2C market. On the front of R&D, we will continue to make endeavors and investments to strengthen our product capabilities. Collaborative efforts with our partners and customers to integrate our large language model will be a central part of our approach. As you may have noticed, we have recently announced very exciting progress regarding several new products, including OOT diffusion, as I mentioned earlier, is a new network architecture for realistic and controllable virtual trials. And this daily investor-focused platform that utilizes advanced AI technology to provide capital market analysis and insights on par with professional investors, supporting investment decision-making, our commitment to pushing boundaries and revolutionizing Industries will propel us towards a future where AI has a profound impact on people's lives. Together with our partners and customers, we will continue to embrace new challenges and seize opportunities to shape the world through cutting-edge AI solutions. Now, let me turn the call over to our CFO Kelly to go over our financials.
spk11: Thank you, Max, and welcome to everyone on the call. Before I go into numbers, please know that all numbers presented are in U.S. dollars, and all comprehensions are on a year-over-year basis unless otherwise stated. For a more comprehensive breakdown, please refer to our earnings press release. Driven by strong digital transformation needs in enterprises, we've hit a record top line for the year. we are taking about a 22.8% growth from the previous year. Not just that, the robust performance also translated into a 270 base point expansion, bringing our growth margin to an expansive 66.6%. And here's the cherry on top. As pioneers at the frontier of cognitive AI, We've unveiled our large language model. This innovative model has propelled our R&D investments to unprecedented hits, underscoring our unvarying dedication to harness and spearhead the transformative power of core AI technology. With that, we expect to capitalize on vast opportunities in the AI realm. Bringing it down further, the increase in the net revenue was primarily due to the increase sales of cloud platform products. These numbers help offset the declines in other areas led by a continued shift towards subscription-based cloud platform products from one-time software purchases. Keep in mind that some of our revenue channels like tech development services and software purchases typically shown in the last quarter of the year. I'd also like to bring to your attention that the rise in the cloud platform products is actually driven by the development of our mass business. As by nature, our mass business is mostly delivered through cloud platform products. In 2023, our mass business grew by 48.5%, reaching 19.2 million US dollars, with the primary contributions attributed to our huazhang large language model. At the same time, the mass business accounted for over 30% of the total revenue for the first time. On the profits front, we hit 39.4 million in gross profit making a 28% increase from $30.8 million a year early. Moreover, our growth margin expansion unfolded as planned, standing at 66.6% up from 63.9% in the previous year. The increase was primarily attributed to the significant increase in the proportion of revenues from sales of cloud platform products with a higher profit margin of 74.8%. Once again, I need to point it out that it was mainly driven by the strong growth of mass business. Embodied, the core concept of providing AI models as a service to users rather than directly selling the models themselves. Our mass business model effectively reduced the barriers to using AI technology in building a broader range of business and developers to conveniently assess the leverage AI models. Now, moving to our operating expenses. Our total operating expenses were $61.3 million, up 18.7% from $33.9 million in the same period last year. Still, the majority of our operating expense increase was driven by a 118.3% surge in R&D expenses, which reached $52.4 million. This reflects our focused investment in the advanced large-language model. We accept our latest release, Huazhong, will play a priority role in our long-term growth as our co-creating model matrix, owning the subject to the foregoing as well as the pipeline of announced products under development, and all other continuing infrastructure growth. We currently accept our R&D investment to mainly at around 50% of our total revenue. As a result, our operating loss for 2023 was $21.9 million compared with an operating loss of $3.1 million a year early. Net loss was $27 million compared to a net loss of 6 million in 2022. Looking ahead, we remain committed to managing costs and enhancing efficiency as we focus on allocating resources strategically, particularly in the priority area of AI technology R&D. We believe this approach will position us well for continued growth and success. Thank you for your attention. We will now open the floor for questions. Operator, please go ahead.
spk00: Thank you. To ask a question, you will need to press star 1 and 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 and 1 again. Please stand by while we compile the Q&A roster. Thank you. We will now take our first question. This is from the line of Brian Lantier from Zach's Small Cap Research. Please go ahead.
spk18: Good evening and good morning to those joining from the East Coast. I just wanted to touch base on the OOT diffusion project, get a little bit more color maybe around when you see that becoming a commercial product. and what you think the eventual pricing model will look like. Will it be principally a cloud service, or do you think that could be a new model that you'd be looking at?
spk13: Thank you for your question, Brian.
spk01: I'll need to translate a little bit here for our management team for better communication efficiency. Mr. Yuan, I will translate it for you first. Brian from Zax Capital has a question about our OOTD diffusion model. First of all, he asked us when this product will be put into operation and what our business model will be like. For example, what kind of level will it be at? As for this product, Will it introduce a new business model? Or will it follow the old business model? That's probably the question. First of all, thank you very much for this question.
spk04: First of all, our online time should be in May. This is the first point. The second point is that such a product, its payment model, first of all, it is a consumer product.
spk01: I'll translate the answer from Max. So first, as for the product for OOTD, it is actually a very new product. So we're going to introduce a new business model. First of all, the product is going to be launched in May very soon. And as for a new product, it's targeting a consumer audience. So the business model will be similar to that of the GPTs, will be conducted based on the subscription. And as for the first edition will be coming from the subscription, but later there will be ones of generative business model as well, based on the picture they generated, the service they get, they get additional payment as well. So that is the information for understanding. We hope we answered your question. Thank you, Brian.
spk18: Great. Thank you. And if I could just follow up with one other question regarding the, I think you called it the DIP, the daily investor focus. I haven't seen too much information on that. Will that be a consumer product for everyday investors, or would that be a product you would be marketing to some of your banking clients?
spk01: All right, thank you. Thank you.
spk04: First of all, DIV is a platform based on the big model and RPA. It's a platform that combines the two. In the future, this platform will extend a lot of applications for different scenarios, including for relevant source reports, paper writing, and some other things. 对大量数据包括文本知识进行处理 它可能会在不同的细分市场上面 都会体现这个应用 那我们在下个月也会上线 DEEF这个平台之上的第一款产品 这个产品的话 我们很快就会预告 它基本上会针对美国的个人投资者 会有一个比较好的这样一个数据分析 或者是相应的这样一个参考 Thank you, Mr. Yuan. Brian, so for your question as regarding to this daily invest focus,
spk01: This product is actually a new platform dedicated to deliver as an agent or co-pilot for our potential customers. The first application scenario will be located in the financial industries. But of course, as a platform, it will be further expanded into different scenarios. For example, not only for the finance industry, like the analysis and also investment analysis, but rather than will be further expanded into, you know, the research report writing, the asset writing, or even the market analysis reports, etc. All of the vertical industry applications, the scenarios that might rely on the report writing scenarios we cannot further penetrate into. So as for this first scenario of the financial industry, we will be introducing the very first product based on this platform in May. So this product is more like a daily report first, because you can see the product name itself is called Daily Best Focus. So this first product will be firmly rely on the target audience or the potential consumers from the retail investor side. We help them to collect market information, sentiment, market sentiment, or even sometimes the per incident alert from the capital market side. to give our retail investors a fully data support on their investment. May they're more confident, may they're resourceful upon the data side, as well as the information side. So this platform is developed based on our large-range model together with the multi-agent workflow, the agentic workflow and also the multi-agent system. One of these agents is using the RPAs and also the others are utilizing the data analysis, data mining, and the different agents being in the queue to handling the process based on our consumer's request. So it's going to be a very new business model as well as a platform that we're going to introduce to our investors. Sorry, our investors. And then we were hoping the AI is really making their life much better, making their investment much easier to give them more rights and access to the information in the market. So that would be an answer to a question. Thank you.
spk17: Great. Thank you so much for that.
spk00: Thank you. We will now take our next question. Please stand by. This is from the line of Wilson Liu from 4Asian Network, sorry, 4Asian Investment. Please go ahead.
spk06: Yes, this is Wilson, and it sounds very attractive and interesting. So I have a question for you. I would like to ask, how do you view the future development trend of the big data model industry? Thank you.
spk13: All right, thank you, Wilson.
spk01: I'll translate for Max as well.
spk12: Wilson's first question is, how do we view the future trend of the big model industry?
spk04: Our understanding of the big model is that before the big model, the most important thing for the AI industry is that AI technology is not enough to provide a chance for all industries to transform. Maybe we can only choose some specific industries. But with the outbreak of the big model in the past two years, we will see that the big model has the ability to push all industries to explode at the same time. Of course, today, the big model has different trends and views around the world. The first view may be that the big model has a relationship with AGI. There are companies that talk about the future of AGI. But from our point of view, we don't think that AGI can be decided by the big model. Because in the past 60 years, the underlying framework of AI has not been broken. We don't think that the big model can achieve AGI. But on the other hand, the biggest value of the big model is what I just mentioned. The big model is already capable of can provide a huge opportunity to reduce the cost. So today, for the big model, the development of the big model, because how to commercialize the transformation, this will be the most important issue. And how to reduce the cost of the big model more effectively. So last year, when we released our own large model, we talked about the first one to be controllable, how to control the illusion of the big model, This is the first point. The second point is to be customizable. Because all large models can eventually enter every scene, every industry, it must be able to, and it must be required to meet the specific requirements of such an industry. The third is to be affordable. Because today, not every company can spend $2 billion to buy a few hundred thousand GPUs to deal with this matter. And the global open source community is trying to use small models to achieve this cost on a large scale. This is a trend. So, in summary, in the future of the large model, the entire artificial intelligence industry, because of the outbreak of the large model, we have entered a high-speed growth, and all industries need to be AI-supported at this stage. This is already an undeniable fact. On the other hand, the large model does not mean that if you invest hugely and continue to invest, you will definitely have AGI. So today's commercial transformation may require us to use a more controllable, customizable, and affordable way. with lower cost and higher efficiency, and use big models, small models, data, and application scenarios to combine these comprehensive advantages, so that we can accelerate the transformation of the C-end and B-end. This may be a very important point for the development of the entire big model in the future. Otherwise, if the big model will not transform with the past technology, which is just a development technology, it will be meaningless for the entire future development trend.
spk01: Yes, I will do the translation right now. So here's the conclusion first, Wilson, is that it is the time point for the commercialization of large junction model and AI technologies. The general thinking in the industry is that we need to create AGI, one less stack-up scale and computational power, and with the notion that the larger the model, that the better its performance, which is a scaling law, the bigger the better. The idea is that the bigger the model, the better it works. But to be honest, we are not totally sold on the idea. There's a catch, although, but it's expensive. The bigger the model, the more it costs to train it. So you need a lot of computing power and data, and there's no easy way around it. So it's like trying to turn lead into gold. It takes a lot of trial and error, and that means a lot of computing power. So because of this, we are considering the most important thing to do right now is to deliver, based on the architecture, the technology framework we have, the large-range model, and we delivered the model that can be customized, can be delivered with cost-effective, and also can be commercialized. So what we do right now is we were considering, for example, for business-to-business scenarios, the enterprise-level large-language models, we do not require such high performance. You don't need a Canon to shot a spiral. So as the current capability of large-language models is already sufficient to significantly enhance the corporate operation efficiency. So what matters more is whether it makes economic sense and if the experience is good. So the key to large language model is always to tie them into business needs and process in a way that makes sense. And for the consumer side, with the development of large language model, the applicable scenarios of the AI products are rapidly increasing. We're seeing more and more uses of AI. So it's like a blue ocean. So this year, we might just see more really popular apps and that develop based on the large model. For example, like the previous product we've been introduced, the data invest focus, and also the OOT diffusion. All of these are the seaside that the company is trying to explore on. So we hope we answered your question. Thank you. Awesome.
spk00: Thank you. We'll now take our next question. This is from Anthony Chang from BE Investment. Please go ahead.
spk05: Hi. Dear management, thank you for the answers. I would like to follow up your previous answer that there are indeed many different application scenarios for your business model. I can hear that you have clients in financial institutions, telecom, and pharmaceutical manufacturing, local government. But which client base are you going to focus more, and what are your strategies for those client bases? Thank you.
spk01: Yeah, thank you. I'll translate here. Anthony just asked a question. The current customers of the company are actually very wide.
spk12: We have a lot of customers, including the business situation we designed, including the scene, including the pharmacy, or the three-generation telecommunications business, the bank. We have a lot of customers, including the local government. We have a lot of corresponding customers to make.
spk01: The question is, which part will our future customers focus on? Our main strategy is to focus on the clients in which scenarios.
spk12: This is probably a question for Anthony. First of all, in the future, the entire product will be divided into 2B and 2C.
spk04: The previous question may be more concerned about the division of the 2B industry. In the 2B industry, although the large model has the ability to promote all industries, we also agree with the previous question. In terms of the industry, we still have some focus. In terms of the focus industry, we will mainly include the call center, smart finance, and high-value industries like this. which are relatively good in terms of infrastructure and high in terms of digitalization. We have a very good collection in the past. We have more than 1,000 large-scale customers. They may come from the call center industry. In addition, there are many banks, securities, and insurance that come from the financial industry. Whether it is in the domestic market or in the overseas market, this is a globalized industry, and it is a very huge industry that continues to grow and AI can restore energy. In these industries, we will continue to dig deeper, and through the development of large-scale technology, we will be able to embrace AI in these industries. At the same time, because of large-scale technology, we can quickly refresh and change, and further release such a huge value in the industry itself. In addition, we will also focus on the new consumer market. In the past, in the development of artificial intelligence technology, the consumer market did not have a particularly large display. But today, in the new technology of large-scale, we will see that in fact, including the examples we just mentioned, such as DIV, DIAF, Daily Invest, Investor Focus, and OOTD, which can be very direct in the field of consumers, can quickly generate transformational value, and also include some hardware. In the next two months, we may also have some hardware, including ESG, that will be transferred directly to the hands of consumers. Therefore, in the 2B industry, we will focus on very important and strong foundations, including the huge industry that can continue to grow. At the same time, we will consider that in the part that can not be covered by the original AIS technology, such as the C-end, including the sea, we will further invest and expand.
spk01: So Anthony, thank you for your question. Here's a conclusion first. Your question is actually a very good one because it's a very important question which customer we're going to focus on. So first, we wanted to answer that there's two dimensions. First one is actually business to business. And second one is actually business to consumers. So like you've been previously talked about, we have a very large customer base. We covered the industry from manufacturing to finance and also to the couriers, maybe all of these clients are within our customer base. So for these customer bases, we're going to dig deeper into their customer needs and we will rely on their business development process, their strategies, to see whether or not they are strong enough to carry more AI technology applications. And we will focus on their pain point to deliver customized large-function models, combined and integrated AI solutions. So for the business-to-business scenario, we will further rely on 1,000 delivery cases, which we acquired within this 20 years, more than 20 years journey in a commercialization experience. and we will be further dig on to deliver better application and solutions to them. However, based on the new technology development process, we believe the large-range model would be a great turning point for the application in the business-to-consumers scenarios. So we will further focus on the 2C side. For example, like the previous product we've been mentioning about, the OOT Diffusion, it's actually the technology name, it's not the product name itself. The OOT Diffusion is the algorithm we're going to introduce to our consumers. We'll deliver a product based on their algorithm. And also the DIFF, we've been privileged to talk about it, the daily invest focus, we're going to deliver to the market very soon in May as well. Other than that, we also have the hardware that's focusing on the ESG side. You know, our company's vision is always to improve everyone's lives with AI technologies. So we wanted to deliver the hardware products that really solve the pain point as well as the issues in the disabled or the under-deserved markets demand. So we're going to introduce this product very soon, as well as in May. We were going to press out release for this ESG product. And we're going to constantly introduce new products in the 2C side to explore the application and the market on that part. So here's a nutshell that for B-side, we'll dig deeper into our customer base and to give them better customized, better experienced products based on large-range model and the other related AI technologies. And for the 2C side, we're going to further explore into the consumer's scenarios and focus on the different underdeserved business segment or the mass consumption business segment, we'll make sure that all of our products are entering into the right commercialization process. So here's the answer to your question.
spk13: Thank you.
spk00: Thank you. We'll now take the next question. This is from Isaac Chan from Han Grand Holding Group Limited. Please go ahead.
spk08: Thank you for picking my question.
spk07: We have noticed that the company has disclosed its plans to initiate overseas expansion and expand into the consumer market. Could you provide information regarding the company's B2C strategy and overseas expansion strategy for this year? Thank you.
spk01: Thank you, Isaac. Mr. Yuan, his question is, we also released the strategy for the sea and B2C this year. What is our specific strategy in this regard, or what is the specific strategy to expand the market? That's probably the question.
spk15: Mr. Yuan, can you hear me?
spk04: Okay. Sorry, I was out of tune. First of all, we believe that a very important business strategy this year is all about the transformation of the business model. Based on this transformation, we believe that in addition to the traditional B2B market, we will continue to grow and maintain a steady growth. In addition, there are two very key strategies. One is the overseas market, the international market. The other is the B2C market, which is aimed at consumers, and provides a large number of sustainable products. As for the overseas market, since last year, after we went public, we have a basic survey of the global market, including the Middle East market, Southeast Asia market, and the European and American markets. we will find a very interesting phenomenon. In fact, the more developed countries and regions in the world, from the point of view of AI and technology applications, I don't know how everyone feels. In fact, since China started moving the Internet, applications have been leading the world. So today, in all the developed countries and regions around the world, we will see that there is a very strong demand in the market. But in fact, from the application, for example, supply level, is far from being satisfied. So for us, in the past 20 years, we have very successful and mature application cases in the entire China-China region. We are very confident that we can quickly push these cases and applications to the global market. So regarding the layout of the global market, in fact, we have completed the structural changes and layout of the company in the Middle East and the United States. In the future, we will continue to quickly promote mature products, including innovative products, to the international market. So this is the first international strategy. The structure of the company has been completed, the whole globalization, or the strategic layout of key countries and regions. The rest, in the second half of the year, we will see a lot of products directly facing the overseas market, such as QC, QB, will continue to be presented. This is the first one. The second one, We talked about the product of消費者 before. The product of消費者 is a very important point of the ability of the big model today. It is also a very important direction of how AI can really explode. So including what we talked about, based on OOTD technology, we will soon launch new applications for the消費者. Including our past big model, including RPA, including a technology platform based on in-depth learning, such as DIV. We will directly focus on these investors. There will be some very profound market analysis and market insights to give them reference. Of course, in the second half of this year, we will have a very clear and complete pipeline. We hope that in a very short time, there will be new products that can continually enter the market. For XiaoAi, we are not an application company. We are a company that has the complete core and basic capabilities of the big model. The most important thing for the big model itself is to be able to complete an application ecosystem. At the beginning of the application ecosystem construction, there will be some innovative products that will continue to be invested on this platform. So I believe that we ourselves, including our eco-cooperative partners, will have a lot of products in the second half of the year. This is why we say that internationalization and the C-end market are two very important strategic strategies for AI large-scale transformation this year.
spk01: Thank you, Yanzong. Thank you, Isaac, for your question. So first of all, we wanted to answer your question one by one. First of all, I said regarding to the overseas business expansion strategy, First of all, our topic today is always centered with the commercialization. So based on the B2B market, we will still dig deeper to make sure that we have a robust and steady growth upon our original customer base. But for the overseas one is that we've already established just our strategies. We've been conducting a lot of market analysis and research upon the global AI application scenarios, including the MENA area, Southeast Asia, as well as the United States and Europe. There's a very interesting phenomenon that the one that are more developed in R&D standard, R&D level or R&D performance, that the AI application is, however, not so satisfying. So there is a blank area between the technology and the actual applications. So we think our company is actually quite good to deliver. We are quite experienced. So we are going to bring more mature and better experienced products to the overseas market. So our corporate structure has adjusted accordingly for our overseas expansion. So at the end of this, at the second half of this year, we're going to see more and more product we're going to bring to the overseas market. to further enhance and expand our product matrix and product lines. So the second point is about the consumer side. This year, we're thinking the AI capabilities is now at a specific time point that can enable these consumer side products to be more satisfying and better experienced. So based on the more applications, based on the LLM technology framework, as well as RPAs and also deep learning, all of these technologies, we're going to utilize those and to deliver better product to our consumers. So regarding to the product we've been introduced previously, it's like DEEP and OOTDs, that'll be the first two application we introduced to the market, and then there will be more. So, in a nutshell, the B2C and international expansion that we are, we've been firmly believe that we will leverage on the robust capabilities of AI technologies and we will witness a significant expansion in B2C market as well as the consumer market. Especially we wanted to further, you know, highlight on the end goal of the company that is really delivered a product of the AI for good. So our mission is to ensure the AI technology is not only transformative but also inclusive. to real creating the solutions, not just technologically advanced, but also empathetic and accessible. So by doing so, we aim to make a real difference in people's lives, bringing AI technologies to those who need it the most and improving their quality of life. across the board globally from B2B to B2C. So yeah, that is our strategies and answers to your questions.
spk13: Thank you.
spk00: Thank you. We will now take our next question. This is from Zheng Yang from BE Investment. Please go ahead.
spk10: Hi. First, thanks for your presentation. I have some question regarding IMD investment. So as we know, the IMD is very important for the high-tech company like Xiao'ai. Well, I'm just curious about how much is your IMD investment? And after the investment, when are you expect to turn the profit? Well, in the meantime, we have the liquid gap. Thanks. Thank you, Teresa.
spk01: This question goes back to Kelly. I don't know if we have a chance to see the possibility of profit. The question is like this.
spk11: Okay, thank you for the question. First of all, in terms of R&D investment, we expect R&D investment to remain at a level of 50% of revenue in 2024. Because we still need to maintain the advantage of such a basic sustainability. And then the main direction of R&D investment in the company is still this mass product and large-scale model. But of course, we will also use commercialization as the premise. We will consider the consideration of this cost ratio and ROI. In terms of profit, it is divided into several directions. First of all, in terms of income, most of our income in 2023 comes from QB and China. In 2024, we expect to have about 20% of online growth in this area. At the same time, we are also actively developing overseas business. In 2024, we also expect to bring some increased business. In terms of operating expenses, in 2023, our sales and management expenses have dropped by 15%. As our revenue scale improves, we expect that the operating efficiency in 2024 will improve. Based on the above factors, we expect that in 2024, there may be a chance to achieve a large-scale reduction in losses and even a chance to achieve profit. Then we will continue to use this long-term collection of technical strength to combine this market demand to realize the commercial transformation of technology. At the same time, by continuously launching new products, expanding the product line, and improving the quality of the products, we will also build a sustainable business growth curve. We will also strive to improve efficiency, profit efficiency, and strengthen our profit capacity. In this way, we look forward to using better profit and loss results to reward our shareholders. Thank you.
spk01: So Theresa, here's the answer to your question. First of all, we will be utilizing on our large customer base that we will anticipate a continued growth estimation upon the TB side. However, our revenue from this segment has been robust and we expected to sustain a solid growth again on next year's basis around 20%. So this projection will be reflected on our confidence in the strength of our current business operation and the potential of the Chinese market. And also, that is not only for the 2B side. Like the 2C side we've been previously talked about, there will be more product introduced to the market. We're utilizing this wolf pack strategy, you know, to introduce one application, then another. There will be a lot of application going to be introduced to the market. There will be anticipated a revenue, incremental revenue will be generated from the 2C side as well. So in terms of the R&D investment that you previously asked about, currently speaking there's around 50% estimation, 50% of our revenue will go into the investment of our R&D. It's going to remain at a significant level, but going to be lesser in terms of the ratio of the R&D fees compared to last year. So our primary focus on R&D investment will be still in two areas. One, MUST, the model as a service product, and the development of Huazhang LLM. So these initiatives are the forefront of our technology offerings and are crucial for maintaining our competitive edge in the AI industry. As well as for the projection and estimation for the profitability, First of all, the revenue scale, like we've been previously talking about, there's going to be a 20% of revenue growth from B2B side and also domestic market side. But there will be actual additional upside from ROTC side as well as the overseas market. As for the operation expenses, in 2023, our SG&A expense rate was already being reduced to 15%. So with the expansion of our revenue scale, we expect the operational efficiency will be further continued, and there might be a further improvement in 2024 as well. And for the R&D investment, we still, like we previously talked about, there will be around 50% of the revenue goes into research and development to maintain technological edge. So based on that, we anticipate the company could significantly reduce losses in 2024 and may even turn a profit. So in terms of cash flow, with the increased revenue and optimized cost, we expect operating cash flow to become positive. So we will continue to leverage on our long-term technological accumulation aligned with the market demand to commercialize our technology by continuously Continuously launching new products, expanding our product lines, and perfecting our product matrix, we aim to create a sustainable growth curve for our business. In a nutshell, our financial forecasts and strategic plans reflect our commitment to a balanced approach, sustaining our core business while pursuing new business opportunities, and investing in innovation with a keen focus on our commercial viabilities. So we believe that this strategy will enable us to continue our growth journey, to deliver value to our stakeholders, and to make a positive impact in the field of AI technologies. Thank you for your question.
spk00: Thank you. Seeing no more questions in the queue, let me turn the call back to Mr. Yuan for closing remarks.
spk03: Thank you, operator, and thank you all for participating on today's call and for your support.
spk00: Thank you all again. This concludes the call. You may now disconnect.
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