I'd now like to turn the floor over to today's host, Dr. Tao Ke, CFO of Helport AI. Sir, the floor is yours. Thank you, Christian. Good day, everyone. My name is Tao Ke. I'm the CFO of Helport AI. Our ticker is HPAI. Over the next 15 minutes, I'll give you a brief introduction of Helport, who we are, and why we are truly differentiated, and hopefully, based on which you can raise your questions, and we can have our in-depth follow-up as you need it. So let me skip to slide three. Why we are special? First of all, unlike any AI companies, we've already had a proven, profitable business model at scale at our contact center core. You will see that at a pretty reasonably small scale, at $30 million revenue, we've already proven at this core we can be very profitable, unlike many other competitors, still trying to figure out their business model. On top of that, we've already, in the past year, when we opened up our U.S. office, we've already had early success in the U.S. market, in financial services such as mortgage, insurance, wealth management, as well as with one of the most important strategic partners, Google. We've also already proven ourselves to be profitable in that space. Thirdly, we've already had a very clear midterm milestones, using M&A as the accelerator. So, in today's presentation, I'll also briefly touch base on that. And we've had a very great top-tier global management teams to ensure we have the right execution. And at this moment, we also believe right now is the best timing for the current investors to get in and invest in us. So without further ado, let me move on to the next page. Who we are. We are a company currently globally headquartered in Singapore, but we do have global presence in the United States, China, and the Philippines. Our mission is to empower everyone to work as an expert. We are unlike other purely based on the large language model based B2B AIs. We combine both the human expertise with the latest and greatest AI technology together to really focus on knowledge-based empowerment in the areas we support our client. We prove that our model, our solution, is already very profitable at our current core customer contact centers. But we also prove that in other industries, our solution can also be very successful. We list ourselves on Nasdaq about a few months ago under the ticker HPAI. At this moment, if you look at the right-hand side, this is roughly our current scale. We have over 30,000 active users. We have over; we're supporting over 5 billion conversations, and our latest financials indicate that at $30 million revenue, we're doing roughly 25% profit margin at this moment, and for our customers, you can see a few interesting names I will only like to highlight a couple, such as Google, Google Cloud, and Accenture. These are the top brand names we've successfully closed and have been working with them for the past year in the U.S. What type of problems are we truly solving in the core of customer contact center. We've proven ourselves with the right solution to address to the owners by addressing how to create values by addressing the customer contact center agents of handling their user experience as well as for supervisors and managers and how do they manage the process seamlessly and with 100% transparency, and specifically, like, what type of values we're delivering both on the revenue and cost side. On the revenue side you see on the middle column that we significantly provide huge values in terms of things like sales volume improvement as well as customer retention. At the same time, in typical customer engagement, we tend to be directly addressing a lot of the pain points by the owners, such as operating cost reductions, training period reductions, as well as reducing quality inspection penalties. So a combination of both the cost side and the revenue side is really truly the differentiation that we almost always deliver to all the clients that we're serving. That's also our differentiation against other players who tend to still more at the concept stage for telling the story and showing them with a business plan. But we've already delivered this over the past decade in Asia. And now, in the past year, we've successfully also proven ourselves with the first success together with Google Cloud, in Hawaii Department of Human Services, together with our local partner, eWorld. What type of product are we delivering? We are mainly provide two products. One is our core called AI Assist. This is offered as a SaaS solution by subscription. We provide real-time guidance as well as other supporting functions such as quality assurance, voice cloning, and other. The core is the knowledge-based empowerment. To support that, we also do find for many of our clients, especially in the U.S., they're expecting end-to-end solutions for their specific client scenarios. So we do offer not only our AI solution, but we also combine this with our BPO partners to deliver AI + BPO solutions to our customers. Therefore, customer just can give us a turnkey request, and we deliver not only our AI Assist, but also together with the BPO seat that we provide them with through our BPO, our HPAI-certified BPO partners. In the end, we do not really replace any human beings. Our true belief is that we are able to really empower everyone to work as an expert. This expertise usually comes from the client's internal best practice. Very quickly, I will show you. I will skip through a couple of slides. This one basically indicates the structure of our SaaS product. The core is the knowledge base that, again, we combine the latest large language model together with the client-driven expertise, as well as, in many cases, our own expertise in specific industries. Then we have a few tools. The main tool is Agent Assist. That's the real-time Agent Assist, coupled with the other two supporting tools, quality assurance and management suite, that, together, we deliver truly the real-time 100% accurate end-to-end solutions to any of our clients to be able to really deliver both on the cost side and revenue side impact. In the core, there's another enabler that we're recently developing that will be on the market pretty soon over the next few months. It's called AI Voice Cloning. Using this, we are able to. Each agent can use their own his or her own voice to initiate five or six windows to for the conversation with client. And they only need to take over whenever there's a clear indication that the conversation is reaching to fruition or there's some issues that he or she needs to get involved. So therefore, we do feel that this particular functions will likely to revolutionize the entire customer contact space. To support that, on the next page, you'll see the second supplementary model that we connect both the demand side and supply side for many of the client global solutions, so client needs. And we are using our AI platform together with the BPO seat that we've accumulated over the past few years that we can truly deliver integrated AI + BPO solutions to address global enterprise needs. And what is really our potential? How do we see the market? From this slide, you'll see that there are three horizons. The very left one is our current core, which is also the financial numbers you've seen at the customer contact center space. This alone is already significant enough. Total addressable market, globally, around $400 billion. And the addressable user around 35 million users globally. Even for AI empowerment, the sum is over $10 billion. And for the space we are today, this can easily provide a 10x potential. But we are certainly not just satisfied with this alone. We already made significant progress in the second horizon in the middle, which tends to be 10x bigger. These are, we call it professional B2B knowledge-based empowerment. Many of that is related in the sales space, in the specific areas such as mortgage loans, insurance, real estate, wealth management, healthcare staffing. You see, each of this space is very different from the customer contact center core. However, the intrinsic expertise empowerment is similar. The why? Because usually in any of this industry, the top players tend to be at least 10x, sometimes 50x more productive than the newcomers or the entry-level players. So our AI software, combining with the expertise usually we accumulated or client accumulated over decades, combining of these two, using our tools, we can easily empower them to be effective and as we said, work as an expert. So that, we've already proven this. We can be very successful, even with only one year's effort, in the U.S. market. Again, this space is far bigger. We do feel this is really the near-term or mid-term future for HPAI. But we certainly are not only satisfied with this. We have already also planned out our third horizon, which is the very right-hand side. We call it Empower Everyone to work as an expert. We developed an open platform called Helport Developer Ecosystem, HDE. In that way, we can really empower everyone to leverage our AI software, use almost no code, combine with their customer base, as well as their, more importantly, their expertise to truly innovate on their own. We just provide the platform behind it to make it successful. How do we get there? What is really the mid-term milestones? On this slide, we indicate, like, this is the mid-term milestones in our mind. We are roughly today at around $30 million revenue as of today. We do see that, through our organic growth, we are able to deliver, with conservative estimation, another around $25-$30 million organic growth over the next three years. On top of that, if we acquire, in our mind, acquire mid-size BPO players, that we can easily get over $20 million revenue in the U.S. enterprise space, usually they have 10 to 12 top-quality U.S. customers. So we immediately get access to that. And then, most importantly, we can leverage this space to further organically grow and also leverage the AI + BPO model. We call it Helphub model that can further double their growth. So therefore, I think on this chart, in addition to the trillion-dollar potential, this is how we immediately grow into a sustainable revenue base, roughly in this space, around $100 million revenue base, easily over the next three years. Many people would say, I will skip a couple of slides. Many people would say, "What's your true differentiations?" Over the next two slides, I will give you a quick highlight, especially why we differ from large language model. I think a few things at the top level. We empower people. We do not. We never believe and we never want to replace people. We want to really empower everyone to work as an expert. Many of the expertise truly come from clients themselves. We are very versatile. We start our core at contact center, but we certainly not limit ourselves. Our solution can be versatile and universal. It can be in a private deployment. It can be in hybrid cloud, public cloud. It can be centralized. It can be totally distributed. It can be the empowerment for many of the work-from-home solutions, etc. Essentially it can be useful in any industries, 100% reliable in the areas where we make mistakes. We also know how we make the mistakes and know how to address it. We have a systematic operation improvement protocol to make it better and better over time. Lastly, but not least, we're fast. In many of our POCs, it can be done in a few hours, which is usually how we engage with our first client. The typical deployment is two to eight weeks, very fast. Usually, our competitors takes months, sometimes half a year to really for the initial deployment. But in our case, it can be very quick, which is also why we never charge upfront fee for our engagement. And this is also another way to indicate our confidence very quickly why we're different from large language model. Many people will ask this question. So first of all, our knowledge base is not from a statistical model from the internet, not from the general base. However, we use expert brains, and that accumulated not only by ourselves, but also our client in many cases. So therefore, when we generate this knowledge base, we certainly leverage a lot of the large language model, but it's all being proven and tested by humans. So it can ensure 100% accuracy. When it's being actually used, we use our proprietary small language model. So therefore, the cost structure and latency is far better than large language model. So these are really the ones we believe that truly differentiate ourselves versus a typical large language model. And when I'm not going through the other key features. We have a top-tier team from this. You will see out of the top management. Three of us are from Accenture. We certainly know, like, how the global enterprise engagement works. But we also have the best combination of the latest researcher together with industry expertise in contact center operation, as well as other industries such as credit card, mortgage, financial services areas. One highlight on the high financials, we are roughly at $30 million revenue and 25% profit. So that's roughly where we are. Just last slide on the comparables. This is typically how you see the market. Not only I'm showing the listed companies, but we also comparing ourselves at our current price versus other comparable target. Again, we are far better in terms of proven profitable model, as well as our current pricing is also much lower than similar competitors in this space. Okay. I will stop here with this investment summary, and open up for questions and answers. Okay. Let me see. I will show how do I do this? Do I just rephrase the questions? Yes. If you hit the refresh, you'll see the questions come in. Okay. So Helport reported a 130% year-on-year increase of revenue in for FY 2024. Can you break down key driver for this growth, and how sustainable do you believe this driver are over the next few fiscal years? First of all, we do not see that triple-digit year-on-year growth is the right expectation. This is an indication of our historical cumulation of our business and the legacy in Asia. This, I've indicated that we've been in this industry for over a decade by the founding team. Our founding team is a great combination of industry expertise, telecom, as well as technology. So we form ourselves to be with a goal to be listed in NYSE, in Nasdaq about three years ago through the entity of HPAI that really leveraged the historical cumulation of expertise for the past decade. That's a representation of this triple-digit growth. On top of that, we see that for the next few fiscal years, we are currently all in for investment in the US market. Organically, we will give a projection of a typical market-based growth rate to really plant the seed in the US market, coupled with potential M&A target that we are acquiring to kickstart for the US market. So externally, we give about 25% top-line growth for next year. And we over the next few quarters, we'll start to give more guidance for the next few years from now onward. All right. Helport Developer Ecosystem is likened to NVIDIA's CUDA platform. Do you plan to scale developer participation, and what metrics would you measure this success? It's a great question. Yes. This HDE is exactly likened to CUDA. We've already planned for the future growth. We are to measure the success by active users, the number of apps they develop, number of downloads by customers, and daily active user by those customers. We actually have already tested this platform twice, in the past 12 months, one through a student competition in December last year. We have three winning teams, each in very different areas, such as service for elderlies, as well as secondhand auto sales space, which indicates that our platform is very flexible, essentially universal in any areas. We've also the second example being leveraging this platform to develop a app in the insurance space for a global insurer in Asia. We finished it within a month, within a week, by using this our own open platform. These two give us the confidence that we can launch this early next year and possibly also do a competition, hackathon, with top 20 engineering universities in the U.S. I think that's about it. We're two minutes behind. It's now. Can we wrap this up? Absolutely. Thank you very much. That does conclude Helport AI's presentation. You may now disconnect. Please consult the conference agenda for the next presenting company. All right. Thank you very much. Thank you. Thank you. Bye. Bye-bye.