AI Is Reinventing Fashion: Startup Pitches from Retail Rebels 2025

Great.

Hi everyone, I'm Keerti. Just checking. I'm the CEO and co-founder of Chimera. We're an AI fashion photography tool. It does exactly what you see on the screen. Design teams can use it to convert their sketches into renders, and marketing teams can use it to do full-fledged campaigns. We work with some of the largest brands in the world. They say that the customers you choose early in your journey decide the kind of product you end up becoming. And so the logos taught us to be better. You'll see the best quality skin detail and product accuracy when you use Chimera. This is all that you can do with the tool. You can take a sketch, convert that into an image. It's able to crawl your website to understand your photography guidelines, the kind of models you cast, the kind of grain you have in your images and produce campaign ideas. It also understands the calendar year almost like an assistant marketing manager pitching ideas to you. You can select one of the ideas and it can instantly produce lifestyle images, video campaigns, PDP shots, UGC-looking content, prints for billboards, ads, and localized PDP for different markets. It's important to compare, so I generated the middle image on ChatGPT, which is the first tool anyone approaches to try and generate images, but their pilots fail because the fabric rendering or skin detail is not accurate. When you see an AI image like that, an untrained eye would say, "Oh, that looks great." But actually AI can do better. So if you see the lighting, the kind of skin detail in Chimera, it is unparalleled. It works for apparel, footwear, bags, beauty, spectacles, sunglasses, appliances, home, and jewelry. While we look like an AI company, we're also the modeling agency of the future. We're able to study common culture faces that move product and create AI models. This also prevents the stray chance of AI producing somebody that might look like a real person. So we design exclusive models for our brands, which are only available to use in their workspaces. We're also able to produce digital twins of real models. Now, you're not gonna use a tool to produce 10,000 images for your PDP one by one. So we design custom design bulk workflows for brands. So if this is your requirement, you want a model styling with certain shoes and you wanna produce 5,000 images, you will be able to do it instantly along with a PDP video with just one click. Case studies, super important to showcase what we do. So Adore Me is a Victoria's Secret brand. They use Chimera for influencer ads, user-generated content. The use case was super interesting because they couldn't find women over 50 to wear lingerie and pose in their bedrooms. And so they used Chimera. They're very interestingly combining real content with AI content. So the shots in the middle are real. Combined with AI. These are the top 10 ads for the company today, much lower cost per acquisition than any other real ad used. Brands are using AI to bulk generate models. If they're launching in a different country, they can swap the model to localize it for that country. We work with Superdry. These are some campaigns they wanted to shoot in Japan for their famous Osaka t-shirt and did not have to travel to Japan. All these are live on Instagram. No one can tell that this is AI. This is Gus with the Superman movie collaboration. They wanted it to look like AI because Superman— I mean, those backgrounds do look AI. You are able to scale up Chimera images to really high resolutions. We've built our in-house upscaler that brings in the kind of detail you want. Steve Madden has a bigger problem. They have summer sandals launching in NYC, they have winter boots to launch in South Africa, Ramadan and halal images required in the Middle East, and bridal season in Australia. So their New York studio still produces content the exact same way that they used to. I'll be honest, I haven't seen companies trying to use AI to save money. They're trying to use it to increase their sales. They're trying to use it to contextualize their content for different countries. So we're able to take the New York campaign and localize it for different countries. Another interesting use case, they're showing their shoe on workwear, party, and on a different ethnicity, increasing reach for the brand by 102%. So again, in the past world, they didn't have to do these images, but now they can. Banners, email marketing, social media. We do a ton of plus-size work. A lot of brands just come in to do a plus-size render on the app because that is so critical. Lots of apps will say, we'll show you sizing in real time, but what happens is that Glamrs sells. If you produce a plus-size image that looks just like your PDP shot, it is very different. We're able to create faces looking at data for the brand. So this particular brand appeals to a sort of woman that has big lips, big eyes, has a color that is specific. We're able to study that audience and produce a model for the brand that will appeal to them. A vintage brand. I mean, travel back in time using AI. Why are we limited to today? Images in ads with two models get double the ROAS than one model. So actually, for this brand, we've been able to increase click-through rates simply by swapping one-model ads to two-model ads. No one likes to be lonely. Model swap. So lots of times you might lose rights to a model. We've seen brands legally approach the agencies, take permission to swap the model, so that they can continue to use that image. Kids is a huge AI business. I have a 2-year-old. I think it would be a nightmare to shoot kids. In Europe, there are huge laws around how many days you can shoot a kid, the kind of doctors on set. It makes sense to shoot campaigns for kids or even PDP using AI. We've been seeing 80% cost reduction, 80% time saving, 50% increase in click-through rates and 70% increase in reach for brands. Quick view of the tool, you can all log in. It's live. It's a self-serve tool. We also have a large full-service business if you don't have in-house capability to help you sail through your first year of adoption. But the tool is very, very efficient. You can choose your direction. You can start from scratch. You can start from a Pinterest link of your mood board. Create an image, edit your image, and use it. It's really simple. Under 10 minutes. Great. Everyone here gets a first free month so you can log in, go to the website. There's a free trial. Tell, tell your teams to log in and we'll help them with an onboarding session. Thank you. Thank you. Thank you.

Thanks everyone. I am very Southern, so I hope the accent doesn't come, you know, that everyone's able to understand. Um, let's get the slides up. I think we'll be good to go. Okay, so you know when you shop for clothes online, right? Everyone's had that experience, but you have no idea how they are going to look and fit on you. Today, that online apparel shopping experience is really confusing, and that confusion starts right after the first click. So shopping for a pair of jeans, right? The first thing that you do, go to the size chart. So this particular brand has a size chart based on body measurements, another one that's based on product measurements. I'm one size in this one, I'm another size on the product chart. I have no idea, right? So you go down to the description, tells me it's got an 18.25-inch knee opening and 11-inch rise in a particular size. Tells me the model's 5'10" and wearing a size 26, and I have no idea what to do with that information, how to translate it to me. So I scroll down, look at the reviews. The top 3 reviews that show up say it runs large. One says it's right in the middle, and the other says that it runs small. Super frustrating, right? And really confusing. So what happens for customers is that you end up either buying multiple sizes or you abandon it altogether. Forget about the jean, close the website, and never come back. And we see this every day with the clients that we work with and their shoppers. It's this broken experience that's persisted and cost brands way too much for far too long. So last year, this is just for US-based apparel brands, $63 billion lost to just returns. We're seeing less than 2% conversion rates for most companies, and most, most customers are spending less than 40 seconds before they just bounce off of a website. So that's where we come in. My team, we are fit and styling experts, um, and we help brand— a brand get their customers into the right fit the first time for them. So we've developed a patented virtual try-on technology that allows a brand's customers to see exactly how clothing is going to look and fit on their body when they're shopping online. So when customers see a product that they like, they can create an avatar from just two photos and then see exactly how the garment's going to fit in different sizes, different colors. They can combine different pieces together, and then they also see our color-coded fit map. Now you'll notice that these avatars are not photorealistic. They don't have a face. Um, my background is actually in psychology, and we did extensive studies for what type of avatars really speak to customers and make them feel comfortable, and which type of avatars actually make them focus on the fit of the garments, not critiquing themselves, not critiquing their own bodies. And we also provide styling and outfit building tools. So these allow customers to style their own outfits. They can do full layering. They can add accessories like shoes. Um, so I wanted to show you this reel that one of our clients made about our collaboration. And it does have sound, so just warning you.

So many years I struggled with putting looks together. And as a child in the '90s, loving the movie Clueless, I always dreamed of having my own virtual styling assistant to help me out. That dream is now a reality with our latest tool, StyleMate Jordan. It's like Cher's iconic styling tool, but even better. You can mix and match tops, bottoms, and jackets with ease, and even customize Jordan's skin tone and shoes to get to look just right. Not sure how to style your next outfit? Let StyleMate Jordan guide you. Create your perfect look, then add it straight to your cart. Style has never been this simple. Now you can walk out with confidence knowing your outfit is on point. Dapper Boy, where clothing fits you inside and out.

Yeah, so if you don't know that brand, really cool company. They were a Shark Tank company, um, but love seeing those kinds of content, right, the customers are putting together about our collaborations together. We also do elevated size recommendations. And the reason I say elevated is that we're actually matching a customer's body measurements to that specific garment's dimension specs. Any of those 3 types of technologies that I just showed you, they can be easily added to Shopify sites and WooCommerce and Salesforce sites and all of those things. And then about a month into when we work with every customer, we set up what we call a customer experience dashboard. So this gives summarized data about a brand's customer body profiles, the trending products and colors and sizes, and the outfits that customers are building. And we track all of that also alongside sales and returns. And the brand owns the data, right? We get to use it, but it's the brand's data. The brand owns it. And we've had brands use this to inform their marketing campaigns in real time. So we live in this world, right, where opportunities come, but they also go really fast. So we just saw this with Taylor Swift mentioning Funfetti sourdough. right, in a podcast, you saw Pillsbury immediately jump on that, produce the product, and it sold out right away. So for one of our customers, we noticed a trend where lots and lots of shoppers were using the technology to visualize bridesmaids' dresses in sage green, more than double any other color. So we were able to share that with the brand, and they were able to immediately take that customer data and produce Instagram Reels that featured that specific color that their customers were were using on their website. And then we were able to change our tool on their website so that the very first dress that customers see before they start customizing was that sage green. So it was both of our companies working in alignment to capitalize on that customer trend. And so far, all of this has been really paying off. So these— this is real impacts from real customers. So we've seen— and this has been over the course of 6 months to a year. So we've seen 105% increases in sales. We've been able to see 46% reduction in returns, and that's on the low end. We've had customers that have seen a lot higher than that, and we've seen 243% more engagement, more time spent engaging with products. And during a recent fitting trial right across a bunch of different categories— blazers, jeans, chinos, dresses— when customers just use the brand size chart, they got into the size they preferred only about 28% of the time. When they leveraged our technology as well, they got into their preferred size 92% of the time. So as you sit here and you think about your business, you think about what your company is doing, what are some of the metrics that you really want to impact? Could be sales, right? Could be conversions, your average order value, rates of returns, customer engagement, and how deeply those customers are engaging with you. So with the type of technologies that I showed you today, you can see measurable, quantifiable impacts in less than 3 months' time. So think about— we're heading into a new year. We have the first quarter coming up. You could start to see demonstrable change, and that's change that you can showcase to not only your team members, your boss, but board members, shareholders. And you can get started with these kind of technologies in less than 1 month's time. So our current customers have seen anywhere from 2,400% and up return on that investment. And if you were to tell me today, right, I could put in money and invest in something and I get that kind of return, right, I would take that deal all day long. And we're not just a vendor, so we really are your secret weapon. So we have team members who are apparel experts, we have AI and machine learning experts. We're really beside our customers every step of the way. We're a lot more of a partner and we actually run a functioning apparel brand. So we do own an apparel brand and we're also in the trenches day-to-day in that space. And we can really help you stand out. That's what my team loves to do. We're white-labeled. No one really knows it's us behind the scenes with the brand partners that we work with. It's all about them and about letting them shine. And really, the only way that you lose is by not trying. We've never had a single client have a negative impact to their top or bottom line, right? There's no negative impacts. Um, so why don't we just try it right now? So you actually can take out your phone, you can scan this QR code. It's going to take you directly to that styling tool that you heard about in the Dapper Boy reel. You can change out outfits and you can try in real time. Now, you also, if you don't want to scan the QR code, you can go to dapperboy.com. At the top menu, it'll have a thing that says Stylemate Jordan, and you just click on that and it'll take you right to the tool. Okay, so we have absolutely never done this before, but when I was talking to the team at PI Apparel and just learning about This is an esteemed audience, right? You all are retail rebels. So I would love to just offer an exclusive kind of VIP offer that we've never done before. If you want to book a demo while we're here, you can get no-cost integration. We're going to waive that first month of service and really show you what we can do. And please connect with me on LinkedIn. I'm also on the app. So if you send a message through, you want to book a demo, myself and Maeve, who's sitting here in the front row, we're going to be around. Thank you all so, so much.

Hello, everyone. My name is Robert. I am the co-founder of Leapfrog AI. Let's see. Yeah. So as you can see here on the left and both right sides, Leapfrog AI, we work mainly with fashion brands. We have a professional service layer, and we have our own SaaS tool. We are located both in the UK and in Amsterdam. And we are also an official partner of NVIDIA. That allows us scale, security, um, better compute, GPU power, which is something that you need in this day and age. We work with a variety of very cool brands, um, like Tommy Hilfiger, uh, like, uh, G-Star, Gymshark, Calvin Klein, Lululemon, and also Philips. I am aware that Philips is not a fashion brand, but it's also good to work with with some other brands to also learn new ways of working that could potentially travel back to the fashion space. We are, we mainly focus on sports and lifestyle. So these type of brands, as you see here, by the way, the visuals that you see here are fully synthetic. That means they are fully digital. We do a variety of things, as you can see here on both the left and right side. We start on the left where you see different types of optimization like garment recoloring, reposing, comping, all done by AI that can really speed up things really easy for you guys to get started with. Doesn't need a lot of stakeholders. And then when we move up more to the right, we see image to video where you can just start with a static PDP pack and we turn that into beautiful videos and we do that at scale. For, for a lot of brands. Sometimes we put out like 300 videos a week for some of these, um, of our clients. And then next to that you see one static PDP shot put in an environment, and then we do digital talent as well. Um, and here you see a very detailed, um, graphic or sort of a, sort of a roadmap. And I want to show you guys this because We don't just offer a SaaS tool. We help and guide brands and we work very closely together with the art directors, with the management teams in basically planning out your strategy to roll out AI within the business. And we help you find how all of these assets are and can be combined and how you can sort of unlock new abilities by doing so. But I can also imagine that it's a little bit boring. So let's jump into some examples. So imagine you have a PDP pack like the one you see here, but you also have different colorways. Now, normally you would send it to like a Photoshop retouching studio. Maybe it's not the right color, maybe it takes too much time. But with AI, we can now quite easily recolor based on just a hex code. And we get from brands back that they really like the accuracy. They like how the, the garments are being treated. The lighting, the material, etc. So that's really good. But also right now it looks maybe a bit— yeah, you can't really use this, right? You can't really use this on your website because then everyone will look the same. But we are also able to repose the models so you can put them in, um, yeah, all sorts of positions that have been signed off by the brand. So we work together with you guys on what kind of poses we are able to achieve, then we lock that into the system and then you get these type of shots. We also get feedback from clients on product accuracy, that they really like that, that the stitching, that the, that the logos and everything is just accurate. And we make sure that we have a good quality assurance and quality control process, um, in place as well, because yeah, we work with premium brands and they want premium quality content. So you can actually, from just two shots, a front and a back shot, get this entire Yeah, all these visuals in all of these different poses in all of these different colorways. And that's pretty cool. What we can also do, if you want to localize your content, let's say for APAC, EMEA, et cetera, then yeah, if we've shot this model already in the Ecom Studio, then we are able to localize the talent 100% in your lighting, 100% styled in the way, the hair for an example, how you want that. And basically in almost any ethnicity and any type of person that you'd want, as you can see here. And also, if you want to style the hair in a different way, we can also do that. And if the hair needs to be behind the ear or it needs to be styled in a different way, we can— normally we do workshops with you guys and then find out how you want to portray your models. So for one of our clients, their second biggest market was actually Japan, but they worked with a lot of EU models. So their brand, they shot everything in their e-com studio in the EU, but showing, uh, EU models in Japan is not maybe the best product market fit. So what we did for them, we created digital talent for them, both male and female, and we digitized their entire e-com page and added Japanese models, and we work together with local talent scouts to find the best fit for them. But they are all digital people, and we made like hybrids of a little bit Japanese, a little bit, um, South Korean, and, um, kind of like how it is really in reality. Um, so we have this entire overview of a variety of different models. I think right now we have over over 400 premium models for premium brands, and we can also work together with you guys to create your own. So if you have certain models that perform well, or if you want to move in a certain direction, then that's all very much possible. And here are a couple of these models, slightly larger. You can license them, or you can own them, like depends on what you want to do. Some you can only license because, yeah, some other brands are already using them. And some brands are actually fine with them being used by multiple brands, so that's an interesting development. And here are some more of these guys. And, um, yes, some are maybe more for premium, some are maybe more for, uh, like your, like your e-com, some are maybe more editorial. But if we double-click on the guy Adrian there on the right, then imagine if we have Adrian here and we put him on a body which is also fully digital And often when we work with fit models, because that's normally how we work, so the, the photograph— the, the clothing is actually photographed in a studio and then we put the digital talent on. But often we find when we create digital talent that there needs to be some adjustment between the digital talent and the fit model, because sometimes we have a person with a slightly wider neck or a little bit of stockier build, and then we do adjust the face that is a perfect match for the body. So maybe change the jawline a little bit. But when you can only do that once, obviously you can't have the same guy on your platform with different jawlines. But if you then have, or, and if you then have your static PDP shot, you can then put that person in an environment. And in this case, in this environment, this is based on a real-world situation. So everything here is, real but also generated. And what we also do together with brands is create these, um, made-up worlds like you see here. So this environment is totally generated, and then together with the art directors, CMO, and these, these type of roles, we decide and we explore, uh, maybe we want some ivy on the wall in the background, or maybe we want to place a certain tree, or maybe we want to have a more spacious environment. So all of these things we are capable of creating and then basically building the world that your brand wants. And we can do that at scale. We could do that 100% consistent. This is what we are now doing for some of our clients. And, uh, yeah, we can do this both with real people or we can do this with digital talent. And, um, yeah, this is just a preview of if you have your full PDP pack, we can then turn it into video as well. And then we've got two more examples of that where we work with— this is based on real people, so they actually exist. So this is a full PDP pack that we are then able to put into motion. And this is basically our bread and butter. This is what we've been doing for the last year at scale. and then we've got one more which looks rather nice. And together with, uh, let me click because the tiny videos are maybe a bit too tiny for this screen. And then you normally will work together with you guys to find out, hey, what is the type of movement that fits with your brand? If you don't have videos already, do the thumbs need to be in the pocket, out the pocket? Does the model smile or not? What's the type of movement? We lock that into, into our system and then we scale these type of operations. And we have our own SaaS tool together with our professional services to help you guys scale and roll out your newly found AI developments. And that's it for me. If you want to reach out, you can go to LeapFrog AI or speak to me or my partner at the end, Ben. Thank you very much.

Hello. Well, we're going to jump right in. Perfect. So last but not least, it's very great to be on stage here. As well. We've been to many of the PI events before, so being part of the Retail Rebels is actually really great. And my presentation is going to be a little different. I'd love to take you all on a bit of a thought experiment journey, of a bit of a visual journey, and I'll start by sharing a bit of a story. So, last week, a shopper actually booked themselves a demo through our website. Not a brand, not a retailer, just a regular person who wrote, "I just want to know what size I am." And it hit me. We've nailed logistics, payments, personalization. But in 2025, we are still, as a fashion industry, struggling to answer the simplest question, "What's my size?" And Now, that story might sound a little strange depending on if you already could guess what we're doing. But we're actually a B2B SaaS company. My name is Marita, and I'm one of the co-founders of Size, easy to remember. That's size with AI. And a fashion tech company on a mission to finally fix sizing and fit. So when end consumers start booking themselves demos meant for brands, you know something's really broken in how fashion communicates fit. And if we look into the numbers, they also speak for themselves. I went too fast. Now, sizing and fit are fashion's silent profit killer. We've heard it today as well. 33% of product profits are actually lost to poor fit. And that's due to a number of reasons, right? So we look into outdated size charts or communication on the PDPs, low fit accuracies, rising return rates. All that contributes to that. And something bigger is changing though. So AI is no longer just assisting our shopping. It's actually starting to shop for us. And imagine telling your digital agent now, I need a dress for my sister's wedding. No filters, no scrolling, just one perfect match already bought. And that's where the industry is heading. And I think we've all seen it in the last couple of weeks and months, especially all probably tried it here and there, or at least the majority of us. And here's the catch. AI can't buy what it doesn't understand. So right now, fashion isn't really machine-readable. And we think that whoever teaches AI what fit means wins in the future of retail. The next shopping revolution, so, won't be about better recommendations. It will be about trust. Which brands will AI trust enough to represent, to recommend, and to buy from? Those who understand their products and their customers deeply. So that's kind of how we set it up and where SISE comes in, because we are building a product-customer data platform for fashion, connecting every product with every body. And think of it as your data foundation that allows fashion to finally speak the language of AI. So really connecting the whole value chain within your organization. Now, how does it work? We combine our product data or your product data, fabrics, measurements, patterns with anonymized customer and behavior data of that individual shopper that is on your sales channel, PDP store, wherever you want it to be. And the algorithms almost create a living feedback loop, so each purchase ease of return, and each review continuously refines your product's fit intelligence. And the results? Fit predictions that get smarter every day across products, categories, and seasons. And our platform has two core modules. So there's a little bit of a glimpse into it after all. And each solves a different, a different part of the sizing puzzle. So we have all the extensions that help shoppers pick their perfect size instantly. And they update obviously automatically as the data evolves. But it's all living, for example, in this case on the PDP, as you could see the different modules through a recommender, dynamic size charts, automatic notches, but all really based and core in your data platform. And on the other hand, deep dive into FitIQ, which is delivering product-level fit analytics for your teams and pinpoints really where products and sizes underperform. And each one delivers immediate ROI. Together, they really turn fit from a cost driver into a profit lever. Now, here, I believe we should be able to see what something like this can look like in an agent and conversational format to really engage with your customers on, for example, in this case, on the PDP in a more conversational matter. And what we see a lot while we look at this is that you don't want just a random agent going and coming and just be able to read what's already on your PDP because for the past couple of years, that was also exactly the problem that humans weren't able to dissect whatever we wanted to communicate about fit. And this is really where it comes in. Your own database, that is going to be the game changer. Now, we're already working with leading brands across Europe and the US. We are the number one sizing solution, I would like to claim, in Germany as well. We're Berlin-based. We've been featured in different outlets like Vogue Business and Elle just lately, where it was really, you know, kind of this thought leadership on sizing and fit and how that evolves. Now, our partners really do see double-digit improvements in conversions, returns reduced up to 30%, 25 to 30%, and average order value increase. So really both the top line and the bottom line to ultimately going to the double punch effect that we would love to always call it on the sizing and fit front. And imagine this. A shopper's digital twin knows their exact fit. An AI stylist pre-selects clothes that feel made for them. And brands can predict sell-through before production even starts. And that's the world we're building with Size, where fashion becomes intelligent, data-connected, and truly sustainable. So from just size charts to an intelligent fashion system. And we're now onboarding US brands. Into what we would like to call our next innovation cohorts. And if you're ready to see what modern sizing really looks like, come find us outside after the session or scan the QR code, connect with me. I'd love to chat. And yeah, we're SISE, building fashion's AI future and one perfectly fitting experience at a time. So thank you. Thank you very much.

Okay, thank you so much, everyone. I would like to invite all of the companies back on stage so that we can answer any questions that may have been presented by the audience. And then perhaps also if the audience wants to just ask some questions, feel free to do that as well. All right. Any questions for our panelists today? Anything you want to expand on? Yes. One second. I'll give you this.

No problem.

Everyone's innovation was really super cool. So, thank you all so much for for taking the time to explain your companies. I just wanna understand a little bit more about how SISE works. So it's not just the company size charts that fuel what it is that you're doing. So how do you get enough other crowdsourced data in order to ensure that the system works as expected?

So there's different levers and different levels of data structures. Thanks. That's actually a really great question because, as you said, it's not just generic data that you would find on any PDP. So we go directly— for example, if you work with a brand directly, we go directly into PLM systems or their Excel files or wherever they have all their sizing and data specs essentially stored. Sometimes— so that's the minimum basis. But then sometimes we also go further into— we call them our different data layers. So for example, with some of the brands we work with, we go all the way to FGI data, where it's really, you know, kind of after the fact that it's been produced to understand how each garment of which factory essentially comes out, because we base it off each individual product and each individual size and how it's been constructed. And sometimes there's just variations, so we can really get down into the differences of maybe how it's been produced. So there's different layers, but the base layer is usually always what's been sent off to production, so every brand would have it as we speak with that.

Awesome. Okay, so we have some questions coming in. The first one is, with efficiency improvements, are there also cost savings with the technologies presented?

Yeah. Yeah, we see at Ecom Studios that sometimes cost savings up to 40% can be achieved, which is pretty massive. So one of our clients also doesn't need to do any more video anymore because We just do it based on photos. So that's just one example.

I'll take the next one. What's the best path to adopt AI imagery? What are customer reactions? Very good question. We recommend brands take the slowest moving products on their website. The bottom 10 performing products, change the images to AI images. Don't convert your entire catalog into AI overnight. It's what you sell. And then see the data on those lowest performing assets. If by changing the images you've been able to increase the conversion, you'll be able to convince your companies, your bosses. You'll have proof of data. And that is the best way to adopt AI in imagery on PDP. If you want to do a campaign, I think an extension of a current campaign is the most interesting. You can use 20 products to shoot a campaign, but there are 30 other products that you need to sell. So do a campaign, physically shoot it, use those images to extend the campaign for the rest of the 30.

Did anyone else want to answer that one?

Well, there are many paths how you can start. It depends a bit on where you are as a business. What you want to do. We see that garment recoloring and reposing is really easy to start with because it doesn't involve a lot of stakeholders. Um, digital talent is a bit more difficult because often then you also need management teams and those kind of things. Um, but image to video is also really easy because, yeah, we see that if you add a video to your PDP packs or to your PDP pages, you can get like 10% add-to-basket increase, which is real nice. So, and most brands really know how they want to portray their brand. So those things are quite easy to execute on.

Awesome. Okay. So the next question is, can you each tell me how your product would assist in the footwear industry, specifically any data points you can recall?

So, I actually shared a Steve Madden example where the same shoe was being showcased in 3 different settings: day, party, and work. We've seen 102% increase in reach.

So, I'll talk about this one really quickly. So, we get approached all the time from footwear companies wanting us to do sizing and fit, you know, for footwear. We don't do that yet, but the same process that we've gone through for apparel is what we would replicate now, and it would be a lot more efficient, and it is on our roadmap to add that.

That.

Yeah, we had some examples on the slides as well. They were quite tiny but were for New Balance. We can do product demos as well for the shoes, like slightly turn them around, those kind of things, with 100% product accuracy. Obviously, you can't fully rotate a shoe unless you have enough imagery, but that's also possible. And like you said, putting things in situ, putting things on people, putting things in motion, making people feel how the product will be used and will be experienced. That's real nice.

Awesome.

I mean, I can take it as last. I feel like this question can be interpreted so many ways. So I'll take my stance on it. But from a sizing and fit point of view, if it's also about what type of data would be needed, in our case, it follows the same principle on the last data in this particular case. So really getting down into how the shoe is produced, How the shoe is designed that would feed into obviously how it works. And I mean, the big obvious one is reducing bracketing. So people stopped buying shoes of the same one in two different sizes altogether, almost like eliminating bracketing altogether.

That's awesome. That's a really big problem and that's a great solve. Okay, so the next question is, all brands fit different. Are you sharing data to improve fit across the market?

So I can start, and then I'm sure you also have a point of view on this. I love this question because, yes, and that's the inherent problem. Every brand fits differently, and also within the brand, there's different collections that fit differently. And this is exactly why size exists at the end of the day. Now, in our, in our particular case, in our FIDEQ, for the specific brands we're able to do is share exactly how to improve fit in different markets.

Yes.

With for that brand. If it's then across the more of the standardization, I think that's almost a philosophical question that I always love to explore because at the end of the day, the question is always like, do we even need sizing labels at some point in time if we can even just make sure, you know, this is the perfect product that's going to fit regardless of what sizing labelers would have? But yes, the short answer would be there is data shared back to A, the brands, also to retailers that would make that improve on like actually understanding what their customers look like to improve it.

Yeah, and similarly to what we talked about earlier, we're looking at the garment dimension specs for every individual garment. It's not like, oh, our jeans fit this way. It's every specific garment. All of that data then, as she mentioned, it gets shared back to the design team. So we've seen teams actually change the fit of clothing based on the data that they're seeing come from customers. And we also have a really big market in in the uniform space. So we have several large multi-billion dollar customers in that space, and they have to fit everyone. It's huge size ranges, and we work a lot on even the uniform collections they're, they're going to present to, say, Carnival Cruise Lines, right, or a Delta Airline, looking at the population that wears that uniform and then recommending the right pieces to serve as the uniform for that company, right? You can use that kind of data to be able to do that.

Anyone else?

I'll take that one. How do you rectify the fact that AI models are replacing human models and human shoot production? You all saw the quality on screen. It is inevitable. I think what we can do as AI companies is make sure that we take everyone along on the journey. My favorite customers are photographers. My biggest effort is to educate models on how they can license their rights. So if we take everyone along and if everyone's learning, we're going to be all good. But this is something that is there in our inevitable future.

Yeah, in our case, we did not really see that happening. What clients did do, so the brands, they licensed the model likeness. We created a digital twin of them, um, and then we opened new possibilities. So one of our clients want, uh, 350 images for Never Out of Stock, uh, but they need it in 2 weeks and they need it for 21 models and they need it for like a ton of looks. You're never going to fly out everyone to that location. You're never going to book everyone, but now you can. So it actually gave them more work, but the models can stay at home. Uh, for the other client that localized their talent for Japan, they would have never shot those models with Japanese models. There's no budget for it. So actually, yeah, it's not happening what has been described here, at least not in our experience. Maybe it will in the future. But yeah, I think the models will be fine.

Nice. So one of the questions that were asked is, there is an obvious generational gap in the use of apps. Boomers and pre-boomer are often frustrated and frightened by technology. How can this be addressed?

I love this one so much because I get this question all the time because, you know, it's an— it's a tool where you're taking photos, right? And you put your phone down. But we've had customers in their late 70s all the way down in that uniform space, right? It's a wide range of workers from early career professionals all the way to those that are retirement age. How many people in this room your parents or your grandparents sit and play games on their phone, right? Probably almost everyone. So even when you get to different age ranges that didn't grow up with technology in their hand or in their pocket all of the time, they still use it. And most of the tools that we're talking about up here are pretty easy. We've tried to make the user experience pretty easy to use. So we've seen it used across a wide age range, and that's been really fun actually to watch.

That. Yeah, I find it hard to convince 50 to 70-year-olds, but post-70, they're all for it because they've seen these transitions in the past. One of the photographers, big fashion photographer in New York, has seen the transition from an analog camera to a digital camera. And so he was one of the first people to log in and start playing with it. And so I think that's what we need. People to look into the history of time and see transitions that have already happened and then embrace this one.

Maybe just to put a bit of a different lens on this because there's also says, how can this be addressed? I think a big one is also making sure we test with them. So the experience we've made is that, for example, I would say a vast majority of our clients, German heritage brands, I would say, Their audience is the 50+ audience, 60+, actually 60+ sometimes. And it's the exact challenge. And what we've seen is that we need to adapt our technology and our user experience to them, to do lots of testing, do A/B testing, to not force a certain type of user experience on them, but to really see what is the easiest way they can engage with it. And it's honestly also sometimes it's a transition period. You introduce something to them. And then you need to iterate and iterate to sometimes then get them to where they ultimately would need to be. So I think it's almost like, honestly, a case-by-case and brand-by-brand experience that we need to tailor to because there is not a one-size-fits-all. There's no pun intended in that. But there is really— you have to look into who your audience really is for a certain product and then adapt and test from there.

Well, thank you all so much. That was really awesome, and congrats to you all for the innovation. Let's give them another hand.

Thank you.

Thank you.

Thank you.