And thank you all for joining this presentation of the Southwest Ideas Conference hosted by Three Part Advisors. Our next company is Perfect Corp., trading on the New York Stock Exchange under the ticker PERF. And here to talk about the company is President of America and Chief Growth Officer Wayne Liu.
Good morning, everyone. Thank you for being here. So I'm Wayne. I'm Chief Growth Officer and the President of America. And also, I've been with the company from day one, so part of this co-founder. So today, I would like to introduce our company to all you and then see you have some idea about who we are. So let me just put my clock here, make sure I'm not going over. Okay. Great. So first, I'd like to introduce you to Perfect Corp. because we are a very special company. The business model probably needs to be explained for you to understand. First, we are a technology company. You can see the AI here. AI actually is our core technology. And then we've been doing AI for the past 10 years. Okay.
We are a technology company, but our technology is specifically applied in the beauty, and right now it's getting into the wellness industry. Okay. So that's one thing. We are using technology and in the beauty. For most of you here, you're probably not using the product which our customers are using because we are dealing with many of our customers like Estée Lauder Companies, LVMH, even Walmart. You've been, you know, you work, probably some of you shop in Walmart. However, you are not shopping the beauty product. Okay. So what we've been doing here is we try to use technology to help this beauty company to enhance their offering. Okay. So give you an example. If you want to try something, right, try to dye your hair or try a different makeup, it's a pretty intensive process.
If you just want to try a color, if you don't like it, how do you deal with it? Right. But we virtually provide this technology for the customer to try. For example, if you go to Walmart, walmart.com, you want to try a hair color, you can just try it in a second and try a different color. If you like it, purchase it. Okay. So our technology actually helps the brand enhance their sales, enhance their conversion, and also enhance the customer engagement time. So, and then also very special about our company is that we are a B2B company. We are also B2C because our core technology can provide, eventually provide to the end user. So we are actually creating this licensing model as a SaaS technology to license to a beauty company and then this retailer. In the meantime, we have our own app.
We put this technology into our app, and then our customer can use the app, and then, you know, the app is free. It's a public app. It's free. However, if they want to have some enhanced or like premium content, they have to subscribe to it. Okay, so just to give you an idea about who we are, and I'll go to more detail. Okay, so as I said, we've been in the business for almost 10 years. Next year is our 10th anniversary, and then we started in 2015. Okay, so our mission is really to empower the individual to have this technology and then define the beauty. Okay, define the beauty who they define their own beauty. And then we have about 330 employees. I'll say two-thirds of them are really on the technology side, architecture, R&D, and product development.
Most of these technical people are based in Taipei, Taiwan. Okay. So they developed products, and then we have a team globally. We have a team in all different countries to support our customers. Okay. So just to give you some idea, I mentioned about how we are using the AI. So at the very, very beginning, okay, so if you want to get people to really try your product, you have to understand who they are. Understand who they are basically is their faces. Okay. So, you know, facial recognition, I mean, we are not really doing the face recognition. We don't need to know who you are. We just need to know your faces. So facial technology is not something like fancy because lots of companies can do that. However, due to our level of detail, it's amazing because even Google licensed our technology. Okay.
So if you go to Google like a search or a beauty product, they offer a virtual trial. Actually, we are the ones behind that. We power that because Google's the facial identification. They can only probably divide your faces into 1,000 meshes. That's how detail they have. But in our cases, we can identify 4,000 meshes. For Google, they don't need to, right? So they don't need to do that detail. But for us, yes, we do because we need to understand every detail of your faces, your skin tone, like eyelashes, in order to give you the best idea, okay, the best trial experience. So that's how we started. We're using AI to do facial recognition. And then gradually we started using machine learning, trying to understand your skin condition. Okay. We actually have about 70,000 highly curated data of your skin. Skin mainly is a photo. Okay.
So that's why we developed the AI Skin Analyzer. So you can show in front of the iPad or the phone, whatever device you're using. In a couple of seconds, we identify 14 different concerns of your skin. Okay. In that case, we can recommend products. Actually, lots of aestheticians and then the medical spa are using that. Okay. So we are using AI very intensively. So right now we are using generative AI. We create our own so-called like a subset of the large language model. Okay. We call the PerfectGPT. That one is a new offering we're trying to push into the market. So basically, it's an assistant. You're talking to an assistant. It's like a GPT. And then the GPT can like scan your faces and understand who you are, your skin, your condition, and then recommend products. So that's how we're using AI. Okay.
So again, we are a global company because our customers are global. So we need to be in the places where we support them. Okay. That's our management team. So Alice Chang is our CEO. So it's very interesting here. All this executive team here, I am probably considered the last tenure working with Alice. I've been working with Alice for 15 years as the youngest one. Okay. Most of them have been working with Alice for more than 20 years because Alice is a serious entrepreneur. So this company is the second company she founded. The first company she founded is our, you can see if you look at our investor list, CyberLink. CyberLink is one of our investors. Alice is the previous company. Okay. That company is public in Taiwan. Okay. So it's a software company. So all the management team is very experienced.
And then we work in harmony with Alice for many, many years. Okay. So that's one of the core experiences we have. And then myself, actually, I'm coming from the technology background. My last engineering job is working with NVIDIA. Okay. I started my career working with Intel and then NVIDIA. Then I jumped into more like an entrepreneurship. Okay. So that gives you some idea. And then we have an advisory board. Mainly it's from the beauty industry. You can see that I'm from Shiseido and then also Snap. And also we have Dr. Feldman, who is actually a professor from Wake Forest School of Medicine. He worked with us to validate lots of our products, especially like skin. Okay. Skin is serious. You claim your skin analyzer is very accurate, but how accurate it is? So we're actually working with Dr.
Feldman about four, starting from three, four years ago. And then he did a series of very intensive research on our product, compared our product with currently the devices actually the dermatologist is using, and also compared our product, the AI-driven product with the practitioner, the doctors. And then he compared and then came up with some results. He actually published six papers in this professional journal, okay, talking about the accuracy and then the consistency of our tool. And the last one actually he published early this year is talking about bias. Okay. Because AI, you know, people think about AI, the best thing is it can be biased. So he did a very intensive study, used a Fitzpatrick Scale to compare our product, the AI result with the doctor's. So actually the result came out was very exciting. Okay.
It means you cannot say like a zero bias. It's very, it's impossible, but it tends to be pretty fair, okay, compared to the setting. All this, you know, the talent, the expertise we have in our advisory board is really helpful. Okay. As I mentioned, we are using AI in the beauty and wellness industry, including skin, beauty. Also we get into the fashion. The fashion is mainly accessories to allow you to try eyewear, okay, glasses. If, say, like GlassesUSA is our customer, you go to their website and see different trials on the glasses. Also we do some fun stuff in our app using generative AI. All these cool things like, you know, change your outfit, change your style, create a photo for your LinkedIn profile, this kind of thing, which people are like crazy about this.
So that's why they're willing to pay for the premium content in our app. Okay, so as I mentioned earlier, we are combined of B2B and B2C. And some of you may have a question: is, would you kind of like shouldn't you just focus, right, in one area? Actually, it's not. That's interesting here is we are focused because lots of the development, the engine which we develop can be used in both sides. Okay. Usually, we create an engine like an AI, generative AI engine, and we put it into our app, which we have like a full control. And then we can see how our customers react with this technology, and then we refine that.
So at some point in time, when this engine becomes very mature, and then we present it to the B2B, the customer, the large enterprise customer, the retailer, we show them how the interaction with the customer in our app, and they are very happy because this engine has been tested already and they see some results. So that's why we leverage our engine. So our engineering team is probably just one. They don't need to like specifically create one engine for B2B and one engine for B2C. They create an engine, and then we can sell to both. Okay. So that's how we leverage our technology in both B2B and B2C. Okay. And then as I mentioned, so the beauty industry, which we do the virtual trial, we pretty much have most of our customers. And then the market which we are trying to expand is actually the skin.
So it's heavily, as I said, using the machine learning to learn your skin condition. And then we can just do this to analyze your skin and then do recommendations of the product and the routine. Okay. So that's how this works. Yeah. So basically, you can use AI to learn and use AR to show. So that's why lots of people do AR like a trial. But the thing is, if you want to do the trial, the real trial, your trial engine needs to be intelligent. They have to understand you, understand the environment. For example, the lighting, right? Different lighting and different devices you are using, they can adjust by themselves. So it's not just simply as an AR trial. It's an AR trial backed by the AI, the intelligence. Okay. As I mentioned, like skin and aesthetic beauty is the area which is booming. Okay.
So because even the younger people right now, they take care of their skin. So they want to spend more time. They want to spend more money on their skin to make sure they are, you know, it looks healthy and beautiful. Okay. So that's where we are getting to that. And then, as I mentioned earlier, we have a product PerfectGPT is kind of like boiling down all these components we have. So we are using a large language model to license some of them, and then we develop our own special track inside this LLM. And then, so in that case, we can connect all the components we have.
So if you have a beauty problem, if you have a question about which makeup you want to wear, you ask this GPT, and the GPT will probably scan your faces, ask a couple of questions like which location are you going to or what kind of like environment, lighting, this kind of thing. And then they come up with a recommendation of the product. Okay. So there's a look. Okay. So go wearing this look, go to the party, and then you can try this look. The most amazing thing is we provide a virtual tutorial. Okay. You can try this, and then there's a virtual assistant teaching you how to make this makeup. Okay. So that's pretty amazing. So we are actually just launched this one, and we are trying to get into the mainstream market.
So that one potentially is a game changer because it actually increases the productivity because probably most of the things we hear from the beauty industry or the wellness industry is the knowledge because all these beauty advisors, when they recommend a product, when they talk to the customer, they're more like a consultant. They need to have intensive knowledge. However, for the beauty industry, you know, sometimes the turnaround rate or all kinds of different reasons, it's very difficult to keep a beauty advisor with extensive knowledge. So this is why this AI assistant can really help. Okay. Yesterday, we were actually in a major, like a, you know, spa and resort. So they are talking about their aesthetician. They don't have enough knowledge to recommend a product. But with the intensive knowledge from the AI training, it really helps. Okay.
Because this aesthetician not only provides the service, but also they recommend products. Sometimes, like, one product is $500, very expensive. You need to build this trust with your customer, right? So if you don't have knowledge, you cannot talk about your condition and what kind of combination for the recommendation, then it will be very difficult. Customer kind of like a skeptical. But with this kind of AI-based knowledge, they can definitely feel very comfortable to talk about this and then give the recommendation. So this one is not just for fun, right? Of course, it's fun. Like you're talking to a beauty advisor, it gives you all kinds of different ideas. However, actually by training this engine, we already inject all the knowledge into the engine. Okay, and then, you know, it helps. It helps.
It really helps the beauty industry, the beauty company or different retailer for their transportation of the knowledge. So that's the one thing which is very important. Okay. So that's PerfectGPT. Okay. And then also the problem with this beauty and the wellness industry is everybody wants to get into AI. Okay. Of course. However, the talent, you probably know this better than I do. The talent with a real like AI knowledge, it's scarce. Like it's not that many. Most of them is probably grabbed by all these Silicon Valley, the big company. So it's not that many talent for the beauty industry to create this kind of AI. So they are lagging behind. Okay. So but with our help, because we've been working with them for almost like 10 years, we know how it works. We have all the knowledge. And then we build this AI.
It's more like their factory, right, so we can provide this AI talent and create what they need and train the engine they need for them, so this one is really, it's a game changer for this beauty industry, so we are trying to push this, especially next year. We are getting to like a main focus on that. Okay, and also one thing we would like to talk here is this one is not just a chatbot. You can think of this as an AI engine. The difference between just a plain vanilla chatbot and the engine is the engine actually can sense the environment and understand what you need, the requirement, personalize, and give a recommendation, which is making a decision. It's different from a traditional chatbot. Chatbot is just a, "Where are my orders?" Tell you. Okay.
But now this one has the intelligence, senses the environment, which means your faces, your condition, like which location you're going to, your lifestyle, senses the environment, and then personalizes the decision. Okay. Because they tell you which product you can use, what kind of makeup, and teach you how to use it. Okay. So that's very different. That's why we call this, it's not just a traditional chatbot. It can be a game changer. Okay. As I said, we have all this, the AI technology. I'm not going to repeat it here, but basically we have very deep knowledge on the AI. Okay. And then the AI actually is not created from scratch. It's created with all this data. So talk about competition. Okay. That's very important. Probably the investors really think about, you know, what's your competitor? Okay. So of course, there's a competitor there.
But in order to get into the level of AI, what we are offering, you need all this kind of data. It's not easy to get all this data. For example, like as I mentioned, like , 4,000 point meshes of your faces. And then over 70, okay, so right now it's a 90,000. So by database, still talking about 70,000. So we are learning every day. So 90,000 different data points to get us a skin, the condition. Okay. And all this data is coming from like an expert area. Some of them are coming from our partner. Okay. So like we work with Neutrogena, Johnson & Johnson. Okay. Previously. Okay. Now they're a different company. So we get the data, they trust us. So we train the engine with the data a nd also we do clinical trial. We work with on the medical field.
And then also we have the app. So we can have tons of data to train our engine. So that one is really critical. For the AI company, without data, they are not an AI company. Okay. They're basically just a model. But we have data to train the model. So that's why it's a real product. And then as I said, well, 10 million training data from faces. That's a combination of, you know, our customer and also from our app. Okay. So I just have a podcast with AWS a couple of weeks ago. We are talking about how we work with AWS. And then amazingly, so we have like 200 million hits every day to their server. 200 million. The unit is million. 200 million. You can see how much data and how much user we have.
Combination of our app and also our customer, the B2B side. So, 200 million access to AWS per day. So, it's a very, very powerful, you know, the data stream from our customer and from our B2B customer and our B2C customer. So, I cannot emphasize any more on the data, the importance of the data. Okay. So, that actually helps. But we have lots of competitive barriers. Okay. That one is really part of that. You cannot expedite it because in the past 10 years, we're building the trust. We collect all data to train our engine. It's very difficult for a company like in a year to try to get into all this data. Like, you know, working with Google and working with Snap and all these companies. So, that's something that really is a treasure in our company. Okay. Yeah.
So that's why, because we have data, so we can get into very accurate the skin analyzer. So that's why right now it's a dermatologist, an aesthetician. I'm trying to start using this to replace their very buggy machine. Okay. That's really a disruptor in this skin industry. Okay. And then of course, we do all this, you know, try out on the fun stuff. Try different like earrings, watches, glasses. It can be a fun stuff to add on. Okay. And then our mobile app. So we have a couple of mobile apps, but most of the two stand out is YouCam Makeup and YouCam Perfect. YouCam Makeup is mainly on the beauty. You can try lots of things. It's a fun stuff. It's more like a playground for some of the beauty lovers. And then also we have a YouCam Perfect.
That one is more on the photo, like a touch. Okay. So and then lots of AI, generative AI features in that app. So you can try lots of fun things, like, you know, change the thing, swap the background, seamlessly. Okay. So these two are the main contributors of our B2C's revenue. Okay. Yeah. And then just give you some idea about what you can try inside the YouCam Makeup. You can try different makeup, of course, hairstyle, hair color. And then, you know, like getting to some very fancy background. Okay. So and then we can reshape your faces because we can identify your face. Of course, we can manipulate it into some really fun effect. Okay. And then the YouCam Perfect is a photo editing app powered by the AI. Okay. So this two apps actually perform really well.
Especially, we add this generative AI features. People are willing to pay more money, okay, to subscribe to the premium content because they want to get into the generative AI feature. Okay. Yeah. It's a generative AI again. It creates lots of interesting features and also useful, very useful tools. It's not just for fun, but it's very useful. Okay. Something like an AI makeup transfer. We can transfer makeup. So if you see, probably you don't, but some of probably your significant partners, also your daughter, they like a Taylor Swift look. They want to try it. Okay. This one, we just snap a photo, and then we can transfer Taylor Swift look on their phone, and they can try it. So we can work with associate with the brand and to associate their product into this look. Okay.
So for example, if you want to create a Taylor Swift look, probably the makeup you should use is from MAC Cosmetics. The eyelash is from Benefit Cosmetics. So that's all the fun stuff. You know, so that's why I guess, you know, based on this technology, the business opportunity, it's like huge. So that's why technology is one thing. We just need to leverage it and then get into the transfer into like a monetize it. Okay. So yeah, that's all the detail. Probably you're not interested, but all the detail about what we can do with all this technology. We change your hairstyle. We just launched with the Unilever. They are the first one using generative AI to change the hairstyle. Okay. They have lots of hair shape products. Okay. Like a shampoo, hair styling.
So using generative AI in a couple of seconds, their customer changes different hairstyle. Okay. Seamlessly. As I said, we create a professional hair shop. Okay. So I'll probably just not go into all this detail. And last part is going to the financial. Okay. Some data. Of course, you can read all this data from our publication and public available data. But just to give you some idea, okay, we are growing double digit. Okay. So grow every year, pretty stable. Okay. So and then the gross profit actually is maintained pretty good. The reason some of you see this variation about gross profit is because of the combination of B2C and B2B. So the B2C part, the gross margin can be a little bit lower. B2B, of course, gross margin is higher. So sometimes the percentage of these two varies.
That's why you see this, the gross margin vary a little bit. Okay, and then, you know, for the adjusted net income and the margin, we maintain a pretty healthy growth, so we will predict our forecast is we'll continue this kind of the growth, and then, yeah, and then we have a positive cash flow, and then we have no debt, no liability, and we have quite a lot of cash in hand. Okay, so as more like a so-called technology, emerging technology company, our financial position is very healthy. Okay, so and then even it's like interest rate and all kinds of things, market variation, inflation, it really has a less impact on us. Okay, so very, very healthy on the financial side. Okay. For the outlook 2024, we try to grow, maintain this growth like a 12%-14%.
And also because still our market, like the beauty industry, right? So our main customer, they maintain some kind of this like even single-digit growth. So that's why in this industry, for us, provide technology, we add in a little bit more on that. Okay. For based on our market. Okay. Yeah. So yeah, as I said, you know, all this, I don't need to read through all this. And then you can read. Okay. So business is going strong. Very unique market. And then we are in a very good position because of our technology, our financial background. And then all this competition is considered pretty small. Okay. Like a small company. So a company like our size, it's very, we don't see that kind of company in our field. Okay. So this we also, it's very interesting.
You see our report; you can see SKU. The SKU means the product we digitize. It can be a color like a lipstick. It can be a type of hair. It can be a skin product. Okay. As you can see, the number actually is a good indicator of our business because the customer will digitize more product and then they spend more time, I mean, more money in our technology and offering, so that's why we always use this the SKU as the very important indicator, and also think about this. If I am a brand, okay, so say like a Estée Lauder or Clinique, they digitize; they create a SKU in our database, and then later, because they sell through channel, like they sell, so right now they even sell through Amazon, right? Sephora, Ulta.
So when we also work with this company, they can actually take this. It's more like a library. The color is more like a library. They take this color and then activate on their channel. I mean, like, you know, Amazon or Sephora. They don't need to reinvent the wheel to recreate it. So that's actually a huge benefit for the retailer. So that's why retailers like to work with us, right? So with like Walmart, Sephora and Ulta. So that's why they don't need to reinvent the wheel. They have all the library. So that's why increasing this, the digital library, all this SKU is very important. It's critical for us. So that can be a very important indicator. You can see continual growth. Never stop. It's just getting more and more and more. Okay.
Yeah, so as I said, as a company, we are, you know, small, relatively small company, but we have multiple avenues to drive growth. Okay. If one area gets hit by impact by some kind of like an uncontrollable condition, for example, economy or something, we have another avenue, kind of like a try to compensate it. Like if B2B is not doing well, our B2C can compensate it. If a B2C is not doing well, our B2B can compensate. So it's always good to have a different kind of avenue for the to achieve the growth. Okay. Yeah. So we built this partnership, as I mentioned, Google, and then some of this YouTube video has a virtual trial powered by us. We are Snap, their beauty actually powered by us. And also in China, Alibaba, WeChat and Douyin.
In Alibaba and WeChat, we actually embedded in Alibaba's platform. Okay. So if any virtual trial on the makeup, that's powered by us. And then we also create a so-called mini program for WeChat and Douyin. So mainly to serve our global customer. If the customer is like a Dior, they want to activate in Douyin, we can easily help them to do that. Okay. So that's pretty much the service. To have a more partnership, it's very important for us because our customer, the B2B customer, they're selling or they partner into the different platform. So we are increasing. Hopefully, we can announce some very encouraging news, you know, very soon. So we are working, continue working with all this big platform customer. Okay. Yeah. This is some of the example of our customer. Okay. We also commit ourselves into the ESG.
Of course, by doing the virtual trial, you save lots of the carbon dioxide emission. We actually have a study by just trying virtually without really taking the sample. It saves like a 1.2 million tons of carbon dioxide. Okay. For our, just to give us some simple explanation. And then one of our customers, Kao in Japan, actually did a really study. So by using virtual trial instead of offering this sample for the hair, hair color, they save like 50 tons plus like of the carbon, the plastic waste. Okay. So really, they'll go virtual is one of the key for the ESG. Okay. So, you know, I'll probably leave for some time for the questions. So it's our company, if you have any questions. And then also we have our IR Director, Jimmy, at the back.
So if you have any question, now is the time to, you know, open up for the question. Okay. No question. But yeah, go ahead. Yeah. Yeah. So just we have a tender offer last year. Okay. So we have a tender offer. And then for all the cash, we are trying to do for, of course, you know, we'll try to leverage this to see if we have a probably it's into the M&A. But I will say I'll try to be cautious here. But the thing is we are looking for some, you know, potential M&A. But as I said, the problem here is in this industry, we are really like a standout. You know, it's not that many competitors. And then the technology, which they have, we already have and we have a better.
So that's why we are trying to get some M&A target, but that's actually become a little bit challenging in our field. Yeah, it varies. It used to be like a B2B actually is about 70%-30%. And now actually we are more like a half and half because of B2C actually going pretty strong. So it's probably like a 50%-50%. But you know, it varies. It varies from quarter to quarter. But right now it's maintained probably like a 50% something. Yeah. It's not necessarily declining because sometimes the B2B grow, B2C grow faster, right? So B2C grow faster. So that's why percentage varies. So B2B is more like a stable. Okay. Because you're working with all these big companies, it takes time. Usually a project takes time to launch and then, but B2C can be explosive.
So that's why it always is the percentage kind of like vary a lot. So I would say B2B is more stable. B2C has more like a potential to grow pretty fast. On a brand side, it's pretty ratable except for one notable quarter where instead of growing, you know, 20 brands in the quarter, you were like 80 brands in the quarter. I'm curious what made that quarter. Yeah. So that's an interesting, you know, good catch because sometimes, for example, when we work with Google, okay, so Google suddenly they give us like a 50 or 40, 40 brands. They want us to activate them in Google's platform. So actually we get all the SKU. Or for example, Walmart, last year we started working with Walmart. They give us like a 4,000 SKU.
It's just like if you work with a big platform, sometimes you see this up. Yeah. You see the peak on. Yeah. So you can see that whenever we have an opportunity to work with a big platform, you see the peak. Yeah. So that's a good question. Actually, it's proprietary because as I mentioned, most of the data we try, especially like the skin, the skincare, that data has to be meaningful, right? So we get the data, it's not from the public domain. Some of them is really from the partner. Yeah. As I mentioned, some of the partner, Estée Lauder or even like Sephora, yeah, like Walmart, right? So that provides us data. And also some of the data we come up with the clinical research. So that one is really proprietary. It's not like a publicly available data.
So it's a little bit complicated, but just to put it simple, we do more like a clean house. So if we train the engine with a specific data from the brand, so that engine actually we cannot sell to other companies. But the algorithm and everything we've been training, we can use it. We can leverage that. But we cannot sell the engine as is from company B to company A. Okay. Yeah. Okay. So I guess my time is up. And then as I say, Jimmy will be here for the rest of the day. And then you can have a question, you can talk to him. Thank you. Thank you so much. Thank you.