Xiao-I Corporation (AIXI) on Q4 2023 Results - Earnings Call Transcript
Operator: Good day ladies and gentlemen. Thank you for standing by, and we warmly welcome you all to the Xiao-I 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 Berry Xia, IR Director of Xiao-I. Berry, please proceed.
Berry Xia: Thank you operator and greetings to all participants. Welcome to Xiao-I's 2023 earnings conference call. Present with us today are Mr. Max Yuan, Chief Executive Officer, and Mrs. Kelly Weng, 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 statements 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.
Hui Yuan: Thanks Berry. Good day everyone and thank you for joining us today. The year 2023 marked a turning point for the general TV AI sector with tremendous growth on the horizon. I think it is undeniable not easy. 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 hosts 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 Hua Zang LLM, which is spearheaded the growth of our MaaS business by 48.5%, reaching $19.2 million. Simultaneously, our non-MaaS business also experienced a 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 with you in July, 2023. We launched our own ChatGPT, Hua Zang Universal Large Language Model. In simple terms, it encompasses a wide range of capabilities and advances that take 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 Hua Zang ecosystem, which was built upon the strong foundation of our Hua Zang LLM, 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 a unique and branded conversational AI experience. In just a few months since its launch, we have successfully implemented the Hua Zang 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 Hua Zang 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 the development capability for our ongoing success, and our ability to create innovative solutions in the rapidly evolving field of AI technology. We are dedicated as we're meeting the needs of our customers, by listening to their feedback and requests, and responding with new solutions and enhanced features. As of March 31, 2024, 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 seven individuals with doctorates. 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 around the universities and research institutes. I'm pleased to share with you our December 31, 2023, we had a total of 258 patent applications, including pending expelled and transferred cases, excluding granted patents. We also patented 318 patent grants and registered 137 software copyrights. In 2023 alone, we filed 36 new patent applications, received 39 patent grants, registered seven software copyrights. Among these, there were six patent applications specifically related to large models, all filed in 2003, and the 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 trial. It is worth nothing the high popularity of OOTD on GitHub and the discussions on platform X indicating significant attention, from potential consumers and promising prospects for product commercialization, to further strengthen our capabilities. We have established joint laboratories with as many institutions, such as the Institute of Software of the Chinese Academy of Science, its 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, our post and telecommunications and Peking University. Together, through our ongoing commitment to research and development, we are poised to conquer new horizons and shapes to future of AI technology. Moving on to another key strategic focus, globalization, our efforts to reverse global expansion gained momentum, with the establishment of two overseas subsidiaries in the U.S. 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 see opportunities in new markets. In conclusion, 2023 was a year of unprecedented growth, innovation and a strategic expansion for Xiao-I, as we embarked on the journey ahead. Filled 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 2024, we expect that the Hua Zang LLM, is set to further strengthen its commercialization efforts, delving deeper into understanding and meeting customers' needs. We expect our B2B operations to continue, to exhibit a robust and consistent growth strategy, with around 20 of growth rates on a yearly basis. At the same time, the event of LLM 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 for achieving innovation and meeting consumer demand more effectively. Hence, we further expand our business into the B2C market. On the front of our 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 a very exciting progress regarding several new products, including OOTDiffusion. As I mentioned earlier, it's a new network architecture for realistic and controllable virtual trial and the Diff. Daily investor focus platform net utilizes the once-the-air technology to provide capital market analysis and the insights are part 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 face opportunities to shape the world through target-edge AI solutions. Now, let me turn the call over to our CFO, Kelly to go over our financials.
Wei Weng: Thank you, Max, and welcome to everyone on the call. Before I go into numbers, please note that all numbers presented are in U.S. dollars, and all comparisons 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 basis point expansion, bringing our gross margin to an expensive 66.6 percentage, and tiers the cherry on tops. As pioneers at the frontier of cognitiveAI, we've unveiled our large language model. This innovative model has prepared our R&D investments to unprecedented hits, underscoring our ongoing 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 increased 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 shine in the last quarter of the year. I'd also like to bring to your attention that, the rise in the cloud platform product is actually driven by the development of our MaaS business. As by nature, our MaaS business is mostly delivered through cloud platform products. In 2023, our MaaS business grew by 48.5%, reaching $19.2 million, with the primary contributions attributed to our Hua Zang large-language model. At the same time, the MaaS business accounted for over 30% of the total revenue for the first time. On the profit 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, sending 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 out that it was mainly driven, by the strong growth of MaaS business. In boarded the core concept of providing AI models as a service to users, rather than directly selling the models themselves. Our MaaS business model effectively reduced the barriers to using AI technology, in bearing a border 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 printing expense increase was driven by a 118.3% first in R&D expenses, which reached $52.4 million. This reflects our focus investment in the advanced Large Language Model. We accept our last latest release, Hua Zang, will pay a pivotal role in our long-term growth as our core-creating model metrics, owing the subjective 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 private 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.
Operator: Thank you. [Operator Instructions] Thank you. We will now take our first question. This is from the line of Brian Lantier from Zacks Small-Cap Research. Please go ahead.
Brian Lantier: Good evening and good morning to those joining from the East Coast. I just wanted to touch base the OOTDiffusion 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 cloud service, or do you think that could be a new model that you'd be looking at?
Hui Yuan: Thank you for your question, Brian. I'll need to translate a little bit here for our management team for better communication efficiency. [Foreign Language]. I'll translate the answer from Max. So first as for the product 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. It will be conducted based on the subscription. And as for the first edition will be coming from other subscriptions, but then later, there will be one-off generative on business models as well. Based on the picture that generated, the service the gap - the like additional payment as well. So that is the information for our understanding. We hope we answered your question. Thank you, Brian.
Brian Lantier: Great. Thank you. If I could just follow-up with one other question regarding the, I think you called it the Diff, 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'd be marketing to some of your banking clients?
Hui Yuan: [Foreign Language] Brian, for your question as regarding the Diff daily investor focus, this product is actually a new platform dedicated to deliver as an agent, or co-pilot for our potential investors, 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 investment analysis, but rather than, we will be further expanded into the research report writing, the asset writing, or even the market analysis reports, et cetera. All of the vertical industry applications, the scenarios that might rely on the report writing scenarios we cannot further penetrate into. So as for the 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, market sentiment, or even sometimes per incident alert from the capital market side. To give our retail investors a fully data support on their investment. Make them more confident, make them resourceful upon the data side, as well as the information side. So these platform is developed based on our large language model together with the multi-agent workflow, the agent 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 consumers' 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 consumers. 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 this information in the market. So that would be an answer to your question. Thank you.
Brian Lantier: Great. Thank you so much for that.
Operator: Thank you. We will now take our next question. Please stand by. This is from the line of [Wilson Lou from Foration Investment]. Please go ahead.
Unidentified Analyst: Yes, this is Wilson. And it sounds very attracting and interesting. So I have a question for you. I would like to ask how do you view the future development trend of the fixed data model industry?
Hui Yuan: Thank you. All right. Thank you, Wilson. I'll translate for Max as well. [Foreign Language]. Yes, I will do the translation right now. So here's the conclusion first, Wilson. Is that is a time point for the commercialization of large language model and AI technologies. The general thinking in the industry is that we need to create AGI. One must stack up scale and computation of power and with a notion that the larger - the model, the better its performance, which is the 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 stowed on the idea. There is 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 language 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 M-to-price level large language models, we do not require such high performance. You don't need a cannon to shut its 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 processed 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 that develop based on the large language model. For example, like the purpose product we've been introduced, the data invest focus, and also the OOTDiffusion. All of these are the seaside the company is trying to explore on. So we hope we answered your question. Thank you.
Unidentified Analyst: You're welcome.
Operator: Thank you. We'll now take our next question. This is from [Anthony Chang from BE Investment]. Please go ahead.
Unidentified Analyst: Hi. Dear management, thank you for the answers. I would like to follow-up your previous answer that there are indeed are many different applications, scenarios for your business model. I can hear that you have clients in financial institutions, telegram, telecom, 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.
Hui Yuan: Yes. Thank you. I'll translate here. [Foreign Language] Anthony, thank you for your question here is a conclusion first. Your question is actually a very good one, because it is a very important question, which customer we are going to focus on. So, we wanted to answer that there are two dimensions. The first one is actually business-to-business. The 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. For these customer bases, we are going to dig deeper into their customers, 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. 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' journeys in its 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-function model would be a great turning point for the application in the business to consumer's scenario. So, we will further focus on the 2C side. For example, the previous product, we have been mentioning about, the OOTDiffusion, it's actually the technology name is not the product name itself. The OOTDiffusion is the algorithm we are going to introduce to our consumers. We will deliver a product based on their algorithm. Also, the Diff, we have been previously talked about, is the daily and vast [ph] focus. We are going to deliver - to the market very soon in May as well. Other than that, we also have the hardware that is focusing on the ESG side. Our company's vision is always to improve everyone's lives with AI technologies. So, we wanted to deliver the hardware product, but really hope the pain point as well as the issues and disabled or the under-deserved market demand. So, we are going to introduce this product very soon, as well as in May. We are going to press release for this ESG product. And we think that we are going to constantly introduce new products in the 2C side to explore the application and the market on that part. So here is a nutshell that so we said, we will dig deeper into our customer base and to give them better customized, better experienced products, based on large language model and the other related AI technologies. And for the 2C side, we are going to further explore into the consumers' scenarios and focus on the different under-deserved business segment or the MaaS consumption business segment. We will make sure that all of our products are entered into the right commercialization process. So, here is the answer to your question. Thank you.
Operator: Thank you. We will now take the next question. This is from [Isaac Chan from HandGrant Holding Group Limited]. Please go ahead.
Unidentified Analyst: Thank you for taking my questions. We have noticed that the company has disclosed its plans to enter 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.
Hui Yuan: Thank you, Isaac. [Foreign Language] So thank you, Isaac, for your questions. So first of all, we wanted to answer your question number one. First of all, I said regarding to the overseas business expansion strategy, that first of all - our topic today is always centered with the commercialization. So based on the B2B market, we will be still dig deeper to make sure that we have a robust and steady growth upon our original customer base. But for the overseas one, and it 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 is a very interesting phenomenon that, the one that we 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 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 the second half of this year, we are going to see more and more product. We are 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. So this year we are 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 our LLM technology framework as well as RPAs and also deep learning. All of these technologies, we are going to utilize those and to deliver better products to our consumers. So regarding to the product we have introduced previously, it's like a deep and OOTDs that will be the first two applications we introduce 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 highlight on the angle of the company that is really deliver the products of the AI for good. So and 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 are 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 yes that is our strategy and answers to your question. Thank you.
Operator: Thank you. We will now take our next question. This is from [Zheng Yang from BE Investment]. Please go ahead.
Unidentified Analyst: 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-I. Well I'm just curious about how much is your IMD investment, and after the investment when are you expecting to turn the profit? Well in the meantime would there have the liquid gap? Thanks.
Wei Weng: Thank you, Zheng. [Foreign Language] This question goes up to Kelly. So actually 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 and estimation upon the TD side. However, our revenue from this segment has been robust and we expect it to sustain a solid growth again on the next year's basis around 20%. So this projection will reflect on our confidence and strength, our current business operation and the potential of the Chinese market. And also that is not only for the TD side, like the - 2C site we've been previously talked about. There will be more product introduced to the market. We're utilizing this wolf pack strategy, to introduce one application then another. There will be a lot of application going to be introduced to the market. There will be anticipate a revenue for incremental revenue will be generated from the TD side as well. So in terms of the R&D investment that you previously asked about current speaking there's around 50%. Estimation 50% of our revenue will go into the investment of our R&D. It's going to be remain at a significant level, but going to be less or 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 Hua Zang LLM. So these initiatives are the forefront of our technology offerings and are crucial for maintaining our competitive batch 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 talked about there's going to be a 20% of revenue growth from B2B site and also domestic market site, but there will be extra additional upside from our 2C site as well as 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 further improvement in 2024 as well. And for the R&D investment we still are currently talking 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 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 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 vulnerabilities. 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.
Operator: Thank you. Seeing no more questions in the queue. Let me turn the call back to Mr. Yuan for closing remarks.
Hui Yuan: Thank you operator and thank you all for participating on today's call and for your support.
Operator: Thank you all again. This concludes the call. You may now disconnect.
