Try out. We actually license this technology to Google. We are behind the scenes. We're pretty much, I'll say, in the beauty industry, we pretty much dominate this color makeup. And then we also have another set of business, which is B2C, which makes us very unique. So we have our own app. We have a couple of apps, but most of the, probably the known one is YouCam Makeup and then YouCam Perfect. So these two apps, we have a lot of downloads. Downloads doesn't mean too much, but it's a lot. And then also, it's a subscription model. It's a free app. It's a free app. Just download it now. You can do it now, but later, after my presentation. So you download it. After that, and then you try it. You do all the kind of fun stuff. You will try different makeup. You try different crazy hairs, whatever you like to try. Or if you do a photo touch-up. Then, if you want to access some premium content, which is heavily AI-facilitated, leveraging AI, using AI, you need to pay. And then that can be very addictive. So that's why a pretty significant revenue from our company is coming from B2C. And then part of the revenue is coming from licensing to this big corporate. So these two models actually work side by side. Probably you will question me, it's like, OK, so then you cannot focus, and then you probably need to diversify your resources. Actually, it's not. Because what happened is, the engine, so sometimes the engine, which is more like the virtual try-on engine or the AI engine, you try different crazy hairs, the engine is very similar. So we create some fun stuff, and we put it in our app. And then people can try the app. If you like it, like it. If you don't like it, we can quickly switch it because it's our own app. And then at some point in time, if this model becomes, I mean, the engine becomes very robust, we see lots of engagement, we can license to the, say, like a beauty company. So just give you some idea about our company. Because most of the time, especially for the most of investors, male-dominated, it's very difficult to understand our business model. So that's why I just give you an overview. Then I'll go to some detail. So as I said, the company founded in 2015. We've been in the business for almost 10 years. And then we list on NYSE, two years. We went public on October 31, 2022. It's Halloween. I guess we probably should choose another day because that becomes a little bit scary for the previous two years. But anyhow, so as I said, 10 years. So we are working with a lot of brands. We keep on adding brands because I shouldn't say this too confident, but actually, I can say this very confidently because I am the one who actually is working with all these beauty companies. Besides L'Oréal, we pretty much get all the big names. So retailers like Ulta, Sephora, all these companies. Because we really have a good technology. There's not that many competitors out there. We are a global company. That's essential to serve the, these are big guys, the global company, because they operate globally. So we have this, of course, in the US, we have two offices. And then we have an office in Paris. And then the headquarters, technically, the headquarters is in Taipei, in Taiwan. All the product development, everything, R&D is there. That's our CEO. And then Louis is our CSO. Johnny is our CTO. And I'm the President. We have some finance. So all this team has been working with our founder and CEO, Alice, for more than 15 years. I'm probably the youngest one. I've been working with Alice for 15 years since her previous company. And then some of them have been working over 20 years. So I am here. I'm actually. I used to say I'm ex-Intel. Actually, now it's ex-NVIDIA. It's a little more catchy. So my last job before I worked with Alice, actually, I worked in NVIDIA. So this is our advisory board. It's all coming from some beauty industry, like Shiseido or ex-Snap. And then we also have Dr. Feldman as our advisor. So as I said, we are using. We start with the beauty. But now we're getting into more than beauty. We are going to skincare. That's a very, very exciting area for us to grow. I'll talk a little bit deeper later. And then we are getting into fashion. So you try different, like eyewear, jewelry, like athletes. And then we also do some fun stuff with the generative AI. As I explained, we have a B2B. We have a B2C. These two work side by side. They help each other. And then the R&D team can be shared. It's not like two separate R&D teams. Because the engine, fundamentally, the engine can be very similar. So when we started this idea 10 years ago, it's relatively new. Now, almost all the beauty companies have this technology. That's why they say, if you want to sell lipsticks, you have to have a virtual try-on. Because people go to your website, they start searching this virtual try-on. That becomes essential. So it saves lots of time, especially during COVID. During COVID, you cannot go to the store and try. So that one becomes essential. All these brands and retailers try to get the virtual try-on engine into their website or app, so they can start trying this. And then, as I said, we get into more than just beauty. You can try nail. More than just makeup, you can try nail. You can try hair, like Madison Reed. So they have a hair color kind of thing, so you can try it. So I'll spend a little bit more time on this one. It's our new area. So this one is very AI-driven. For the makeup, we're still using augmented reality as a mentor because you need to show. You need to show the color and all kind of things, but the skincare and the aesthetic beauty is really purely like AI. Especially for, let's start with the skin, so when we started skin about five years ago, that's when our company, like again, Estée Lauder or the likes, you can do makeup. Can you do skin? And then our R&D just thinks about, OK, so let's do skin, but skin, we need to use in diagnostic. Skin is not about trial. It's about analyze and recommendation, so that's why we started working on skin. So actually, our first customer is really Neutrogena, and Johnson & Johnson, they give us good access to their database. Because we started using the data for the AI, you need data. Everybody knows that. So without the data, you cannot really do AI. So that's why we have the opportunity to access a huge database with working with Johnson & Johnson. And then later, we started working with La Roche-Posay. Although they are L'Oréal brand, but they are skincare. So they are working with us. So we get access to tons of data. And then we started training our engine. So the idea here is, you just show up in front of the camera. We don't need any special machine. It's just an iPad. Especially iPad or iPhone getting so good. The camera is getting so good. So we are doing that. And then in five seconds, five seconds, it shows you skin concern. We start with four concerns, like a wrinkle. And then we get into eight concerns. Now, at this moment, we can identify 15 concerns. Since we can identify 15 concerns, it covers a lot of most of your skincare, I mean, the skin condition. So actually, the medical field started using that. We see dermatologists, aestheticians, they are using that. Because they used to use a very big machine called VISIA, a big one, probably like $20,000, and you need to pay all the maintenance fee, but now it's a subscription model. You only need to download our app and put it into the iPad. You can start diagnostic process, and then it's very accurate. Because as I said, I don't think we have this in our investor deck. But if you're interested, we can provide more information. We work with Dr. Feldman. He's a professor of Wake Forest, the medical school. So he's also on the American Board of Dermatology. So he did six research with us. He published six papers to verify the accuracy of our app so that's why since we have a scientific proof, so that's why people started using that. Because all his papers talk about the methodology, the sampling, how he picked the person. Because he picked the client just to reflect the real population so after that, his conclusion is your tool is accurate, fast, and consistent. That's very important so that's why we get into the skin diagnostic. Of course, the brand using that. The brand puts this into their website so before the customer gets into the product, because sometimes the customer doesn't really know what the problem they're trying to solve so they do this diagnostic and then AI actually tells them, like graphically, so show you where your problem is and then what's the product recommendation so that's how this is being used. And then last, actually, two weeks ago, we announced this aesthetic beauty. But what happened here is, once we get into more like a medical field, we started working with the dermatologists and aestheticians. However, the thing here is, aestheticians sometimes not only do skin. They also do some non-surgical treatment, like fillers, Botox, or some injectable product. So that's why aesthetics can do some simulation. Because really, the big problem is that the customer needs to know what happened after they do this treatment. So like two weeks ago, we announced this Aesthetic Simulator. So it can simulate 27 different non-surgical operations. So we tell you, the customer just shows in front of the camera, which can be an iPad. And then we tell you, after that, the doctor starts to do the diagnostic process. After you do this treatment, if you do like OK so four needles in this area, what will happen? So we simulate. So that one, it can be a huge market for us to explore. So these two, the skin and the aesthetic beauty, get us a new market. I won't say away from the beauty. It's still in the beauty. But instead of just doing the makeup and then we get into a new market. Because the problem with the makeup is, it's dominated by this big company. If you have all these big companies as your customer, you pretty much have all the beauty industry. So that's why the new area to grow is really on the skin and aesthetic beauty. So then, as I said, we are using AI. We bring AI into the new level, which we create our own GPT. So GPT is just a word to get people to understand. But basically, this one is an AI engine. So we call it PerfectGPT. We are actually, of course, we don't need to re-spin the wheel. We are using some of the existing. We license some existing API from this company, the LLM. However, we create our own RAG. I don't know if you're familiar with that. But basically, RAG is an LLM inside of LLM. We train that RAG, like become a beauty expert. We don't need to do this general conversational LLM because we can license them. And we train this specific RAG into a beauty expert. So that's how everything happens. Because we have so many data, remember. We have tons of data. We work with so many brands. So actually, they are willing to work with us. So actually, at some point in time, we are in the very early stage. We are in the very early stage of working with some big brands. So ideally, they will have a digital AI-driven beauty advisor. We create a persona of M·A·C Cosmetics. Because we know M·A·C's communication guidelines. So we train the engine. So basically, what happened here is, you show up, of course, you just get into the GPT. So you type something. And then, for example, you ask them, OK, tonight I'm going to, say, like a gala. Just recommend me some product or makeup. So then we'll take a picture of you, and then start a conversation. We recommend the look for you. And then also, you say, oh, because the light can be a little bit dark, and then the thing is a golden black. We give all this conversation, and then they create the perfect look for you. So basically, this AI engine can sense the environment, which is you, and then understand your need, which is personalized. And then make a decision for you, give you the best look. So that's why this is something we just announced in June. So we are working with some early partners. So that's a very exciting something coming. So we have a skincare. We have an Aesthetic Simulator. And then we have this GPT. So while this B2C is our core virtual try-on on makeup, we have so many new areas to grow. So yeah, so that's why we've been doing AI since day one. We are not just doing AI because everybody talks about AI. You have to understand the customer's face. That's really a very fundamental thing for AI to understand your faces. So that's why I just give you some idea. We have a very deep technology background on the AI. As I said, and then we have data, lots of data, which is very unique because we work with brands. And then we have our own app. So that's how combination we can get all this data. Training our skin engine, it probably takes us like 70,000 highly curated data to train the engine. So yeah, so I'm not going to all the detail about the feature of our app. But the app is very interesting. That's why it's very addictive. It can become one of our revenue-driven drivers. So however, some time, I'll go to the revenue. So our revenue is quite, it's really quarterly. Every quarter is a little bit different because based on the beauty brand's cycle. So you can see, actually, every quarter it goes a little bit different. However, we maintain growth every year. So 15% in 2021 through 2023, and then 13%, and then 11%. And then the gross profit also grows. So actually, in general, not pretty stable, but growing. Especially you are working on a very traditional market, which is the beauty and skin. So it's not like grow like a crazy three-digit growth. But within this area, we maintain a very healthy growth. You can see the net income and the margin actually also grow pretty well. And then the good thing is, we maintain positive cash flow. So we will put this, you can access all the information from our website. And then you can see, financially, we are pretty healthy. We not only maintain this double-digit growth, but we also are cash positive. And also, we have quite a lot of cash reserve. For a company which is like our sizes, it's pretty much like unusual. So the reason we have the cash reserve and everything is to make sure we can continue serving our customer. In the meantime, we get into the new market, something like skincare, aesthetic, and then the GPT, the AI. Because it requires lots of R&D effort. And also, go-to-market, it takes some effort, the resource. So that's why we maintain very good financially. And then for the outlook, as I said, we pretty much, at this moment, of course, we have a lot of potential to go into a new market. But based on our understanding, it's really, it takes time to grow this new market. So right now, our forecast is still pretty conservative based on what we have now. So in 2024, we assume, again, 12%-14% growth. And then just pretty much maintain quite stable the way we grow the business. So you can see, we just released the Q3 yesterday, or yeah, this morning. Yeah, this morning. So all these numbers are new. The revenue, $6 million. And then we grow 10%. And then all this, the gross profit is $30 million. And then also, we grow. But the thing here is, if you think about gross profit, we have both B2B and B2C. B2C, usually, the gross profit can be a little bit lower. So we use B2B to balance that. So that's a good thing about us. But also, the B2C maintained a very strong growth momentum. Operating expense is $30 million. We grow a little bit. Although we are getting to all this new market, but we maintain the very healthy growth under the control, everything like expense. So that's what we expect. That's what the number is. And then we will maintain this kind of trajectory. And then we'll see potentially, so this one is a number of a brand because that's also a good indicator. The more brands working with us, they give us all this momentum. Because what happens is, they work with us, and they're going to renew next year. So all this retention fee, the renewal. So as I said, we work with all these technology partners and all these big beauty companies. I don't know if you know that, actually, The Estée Lauder Companies just announced a new CEO, Stéphane de La Faverie. Actually, we worked with Stéphane since 2017. Very good friend with us. So actually, I'll stop here. And then I'll leave like four minutes for you to answer the question. You're trading near your low. The market's not really rewarding you for doing that. What are you trying to do to sort of work out? Or why do you think that is? Yeah. Your fee is a little high or whatever. I think there's a couple of reasons, but we can talk about the detail. But basically, the idea here is, as I said, we are in the beauty industry. Most of the analysts, they probably either analyze beauty or they analyze technology, so we are in the intersection of both. That's why sometimes it's a little bit difficult getting to a model, try to give us a fair value. That's why we have not that many analysts to just try to work on that. That's the first thing. And then again, the trading value, that's why we are here. We want more people to know us because in the beauty industry, pretty much people know us, but in the investment industry, people still don't know. That's why we want to introduce ourselves to you, so that's yeah, so very new. That's why, I guess, a couple of reasons. Marketing, we need to get people to know us more. Are you the app on the app store that says Artistry and YouCam? Is that your company? The YouCam, it's a Perfect Corp. The Artistry actually is the one we create for Amway. Amway? Yes. Because they all say perfect. Yeah. Because we create, so sometimes we create this mobile app for our OEM customer, like Amway. But our app is YouCam Makeup by Perfect. Sometimes like the Artistry, that one basically is Amway. We create this for their beauty advisor. Yeah, but if you search YouCam Makeup, CAM is like a camera. YouCam Makeup, yes, CAM. And then that's us. I have two questions for you. One of them is just if you could provide some metrics around customer usage to help me understand, are people using the platform and say, wow, this is fantastic, I'm using it now every day instead of every week? And the second question is, how do you deal with the issue of the colors you see on the screen of your phone or your computer or through your camera are not the actual colors that we see when we look at each other? Yeah, the first question, we can actually, Jimmy, maybe if you, we can provide more information to you. So we do have that question because we actually have a server to have. The second question is an interesting one, which we already resolved. That's why all these companies working with a couple of things. First is, we have a couple of patent technologies. For example, we do balance of the light. Because as I said, it's the engine, the AI engine. We look at the lighting and then also probably the devices and try to balance the light. And then we actually go through what we call the color picking process. So we actually, that one at the very beginning is for human. We work with the Artistry for the brand. So they look at the color. And then we have a platform they can adjust it. We have a tool for them to adjust it, so that's why we make sure the color is right. So the first thing, we do some patent technology to balance the color. And also another thing here is, the interesting here is we do iPhone and Android. So iPhone issue is pretty stable. For the Android phone, we actually test like hundreds of different phones to make sure the color is right. So that's why all the beauty brands, they verify it. And then we confirm the color. So that's why our digital color library, like 800,000, is a very valuable asset for us. Thank you so much. If you have questions, you can reach out to me or Jimmy, our IR director. We'll provide you more information. Thank you.