Rezolve Ai PLC (RZLV) October 2026 Capital Markets Day Transcript

Before we begin, a brief reminder. Today's presentation, including our remarks and the Q&A, contain forward-looking statements within the meaning of the safe harbor provisions of the Private Securities and Litigation Reform Act of 1995. These include our 2026 revenue guidance and ARR targets, margin and cash flow expectations, cost savings, our strategy and path to profitability, acquisitions, our products and AI technology, market opportunity, and our partner relationships. These statements reflect management's current beliefs and assumptions and are subject to risks and uncertainties, many outside our control, that could cause actual results to differ materially. Please do not treat them as predictions or place undue reliance on them. For a discussion of these risks, please see the written disclaimer accompanying this presentation and the Risk Factors section of our 2025 Annual Report on Form 20F and our other SEC filings. These statements speak only as of today, and except as required by law, we don't plan to update them. Thank you. Today's Resolve AI presenters will take questions from investors together at the end of the program, following the financial overview. Questions will be taken through the web platform only. If you are here in the room or joining online and would like to ask a question, please submit it through the web platform at any time during today's presentations. We will do our best to address as many questions as possible in the time available. I will now hand over to Daniel Wagner, Founder, Chairman and Chief Executive Officer of Resolve AI.

Thank you, Ermi, and good morning and welcome to Resolve AI's first Investor Day. Thank you for all being here, for those of you who arrived in person. I'll start with the market, where we sit in it, and the strategy we put in place to outperform and drive substantial profitable growth. We will then spend the next few hours showing you everything we've built running live. E-commerce has already reinvented itself twice, and it's doing so again right now. The first era ran from 1995 to 2010, and it was built on search and catalogues and keyword box interrogation. The second ran from 2010 to 2024, and it was all about mobile, with a phone in every pocket, advertising targeted through social media, and checkout moved to that screen. The third era has already started. and it is agentic where technology conducts search and transacts autonomously on behalf of consumers. Historically, if you wanted a new pair of sneakers, you would go first to Foot Locker, then to Nike, then to Adidas possibly, and you decide after reviewing three sites yourself. Give that job to an AI assistant and it sends countless agents off to hundreds of sites all at the same time. Those agents interact and interrogate what they can access across the whole internet and come back with a curated answer. Imagine a hundred merchants questioned by a machine on behalf of a shopper who never visited a single one of them. Multiply that across every shopper and every question. Merchant systems are facing a hundredfold increase in activity already. This is an unprecedented change in behaviour, and the vast majority of companies are simply not ready. E-commerce, as we know it, is finished, and what replaces it is arriving faster than anyone expected. The retailers who move first will take enormous share, and the ones who wait will spend a decade catching up. Most retailers can see this coming and need an immediate solution that can support their end-to-end commerce journey needs. And we at Resolve AI have spent 10 years, 10 years building that solution. Michelle will talk you through exactly what that opportunity is worth right after me. But let me start with the numbers because they make the argument better than I can. In the first half of this year, we delivered $130.8 million of revenue. That was more than 20-fold what we delivered in H1 2025 and nearly three times our revenue in the whole of 2025. We're targeting at least 500 million of annual recurring revenue as we exit 2026 and we go into 2027. And our strongest trading period is still ahead of us. Our next job is profitability. And we have a strategy to get there faster, built on growth we can sustain. We are operating from a position of strength. We have the team, the technology and the partners in place to succeed at scale. From here, we are growing what we've already built, and that costs us a fraction of what it took us to build it in the first place. That must be my mother calling me. It's obviously very serious. Our strategy starts with our mission. Resolve AI is the infrastructure backbone powering AI-driven commerce for merchants, financial institutions, hyperscalers, and technology companies. We start with merchants, and the same infrastructure we build for them can be sold to every other part of the chain, from banks and payment networks to the largest technology platforms in the world. Brainpower is our own proprietary language model trained from first principles for commerce and protected by more than 30 patents. We all know AI can talk. The problem is it can make things up. And in a live store, one invented price costs a merchant the sale and the customer. Hallucination is the reason most retailers will still not let AI sell on their behalf. Brainpower was built to solve that problem, and we will show you exactly how later this morning. With the technology built, the job is now distribution, and we are running three growth engines at the same time. The first is organic growth, driven by our own go-to-market sales team selling directly to enterprises around the world. The second is distribution through partners, whose marketplaces and sales forces put us in front of customers we would take years to reach on our own. And the third is licensing that infrastructure itself so that platforms, banks, and payment networks can run on the data, intelligence, transaction, and payment rails we have built. Together, they deliver against five priorities, every one of which you will see proved today. The first priority is win the enterprise. We have built one suite of products that carries a merchant from the moment a shopper starts looking to the moment the money lands. Discovery, conversation, recommendation, merchandising, loyalty, checkout and payment all run on one shared layer. a merchant integrates once we ended June with well over a thousand merchants and our job now is to move every one of them from first deployment into full production across the whole suite today we will show you all of it running on live enterprise sites the second priority is own the payment influencing a purchase is worth something Completing it is worth far more, because that final step is where the economics of commerce sit. We are building ResolvePay to lift conversion at the moment of payment. It will put more of every sale back into the merchant's pocket by removing 2% to 3% transaction fee that they've paid on every single purchase for decades. Beneath every product sits infrastructure, which we own outright, from our commerce-tuned language model and data pipelines to the verification layers that prove why an agent did what it did. Platforms, financial institutions, and enterprises can license those rails from us and save themselves years of expensive building. The fourth priority is scale-through giants. Microsoft, Google, Tata Consulting Services, Tech Mahindra and most recently MasterCard give us marketplaces, enterprise sales forces and delivery capacity that would take a decade to assemble on our own. They already sit in the room with the enterprises we want to reach and they hold the budgets and the relationships. The fifth priority is compound the margin. Our acquired businesses are being consolidated into one operating platform. Our revenue mix is shifting towards software and recurring revenue, and every new deployment costs less to serve than the last. Everything you hear today comes back to one of those five priorities, and you can track our progress against every one of them. Here's how the day runs. I think I've run through a couple more slides. There's our priorities. Here's how the day runs. nine of us are presenting today alongside two panel sessions and that is deliberate because this company runs far deeper than one founder with a story to tell Michelle Fisher, our chief marketing officer, follows me to define agentic commerce and set out the size and shape of the market we then open up the platform layer by layer in the order a shopper moves through it from getting a merchant found to turning into a visit from turning a visit into a sale to turning that sale into a customer who comes back to completing the checkout. Laurence O'Toole, our VP of SEO, AEO, and Discovery. David Ingram, our Chief Experience Officer. And James House, CEO of Resolve Reward, will then put the live product in front of you running against real deployments. Naga Samineni, CEO of Resolve Pay, will give you a glimpse into the future of payments with a preview of ResolvePay. Shovic Manerjee, our group CTO, closes that section with a look at our intellectual property and the technology we built to hold it all together. Steve Perry, one of our non-executive directors, and Elizabeth Lachler, our EVP of the Americas, will then explain why this moment is different from every earlier wave of retail technology and what it looks like from the inside of the payments industry. After the break, you will hear from two of our partners, Kimberly McKinley from Microsoft and Surab Atri from Tata Consulting Services about the agentic commerce landscape and why they chose to work with Resolve AI. Arthur Yao, our group CFO, and Kate Goosen, our deputy CFO, will close with the financial picture and our path to profitability. Today's Resolve AI presenters will then take questions from all of our investors. We are taking these through the web platform, so if anyone sitting in the room or online would like to ask a question, as Ermi said, please submit it there. We'll do our very best to get through as many as we can in the time available. The product is live in the reception area or outside, and throughout the break, for those of you who are with us in person, I encourage you to go and experience the products firsthand. I'll leave you with one thought before I hand over. I started my first company made in 1984. I know you can't tell because I look so youthful. And put business information online before most people had even heard of the web. In 1998, I founded Vendor to run e-commerce as a hosted service. Years before anyone called it software as a service, and Oracle went on to buy that company. Alongside it, I founded Attract, which built the search and merchandising schools that decide what shoppers see, and I took it to the London stock market. Each time I saw a new way of buying before the market did. Argentic commerce is the next change in how people buy, and it's already here. Resolve AI is the only provider that gives merchants everything they need to meet this new paradigm. From discovery through to payment in one place. I was right about the previous changes to e-commerce. I'm right about this one the only difference is this time the prize is much much bigger this is the most exciting company I've ever been involved in and this is the most exciting time that I've ever experienced in my life in technology the transformation of what we're seeing with agentic technologies and artificial intelligence is breathtaking and transformative not just for business but for our lives I'm very very happy to be here, running this business, in this market, that has such infinite potential. Michelle's going to show you just how big. Please welcome Michelle Fisher.

Thank you, Dan, for setting the stage. Hi, everybody. I am so honored to be here today to get to talk to you about what it is that we are building for and who we're building it for. My name is Michelle Fisher. I'm the Chief Marketing Officer here at Resolve AI, and I am absolutely thrilled to be a part of Resolve AI. I joined about four months ago. It's been about two decades for me in retail, starting all the way when I was selling bridal gowns to being able to be at the intersection of infrastructure and emerging technologies and storytelling with storied companies like Disney and Amazon. To get started, I don't think anybody is going to be surprised in this room that commerce is going through a monumental shift it's a total redesign and someone is going to build that infrastructure and every single thing that we're building is ensuring that we are the company that is going to be building it and transacting with it the very nature of shopping has gone through a fundamental change merchants spent years developing strategies and many of you may have even experienced this where they put billions, millions and billions of dollars into strategies to improve their search to be the first thing that people see when they go to Google and now, all of that is shifting to if you don't get chosen in the first three to four AI recommendations you're practically invisible as a brand. 42% of shoppers consult with LLMs according to an Adobe traffic report And actually, from the same report, shoppers referred to retail sites through AI convert 61% more often than customers who come through other channels. That's not a trend. That is an unbelievable change. So we'll go through a little bit of this big shift in the next slide here. Agenda Commerce is going through a multi-trillion dollar shift in a $30 trillion industry. Retail is the demand signal for the global economy. It's impressive how in just such a short period of time we've seen retail shift from the old way that we used to go shopping, which I will go into in just a minute, to now $3 to $5 trillion going through what predicted to be going through agendic commerce and through agents. Bain has actually predicted that 15 to 25% of commerce, or 15 to 25% of all e-commerce by 2030 will actually be going through e-commerce as well. And just to restate, 3 to 5 trillion in 2030 will be going through agents as well.

So merchants need to be ready.

They need to ready their catalogs with machine-readable data or face being invisible. at the moment that a customer comes and has their query. If you are missed at this point in the three to four AI recommendations that people get when they're doing their shopping, at best you can consider that a lost opportunity. At worst, you consider that a missed sale, and that's what we're trying to solve. The sales funnel has essentially collapsed, and I'll give you an example of how that changes. And many of you have probably experienced this before yourselves, where you've gone and, you know, for example, with me, I'm going to be in New York City again. I'm based in Seattle at NRF, and I'm going to need a winter coat. When I go and I go shopping and go to Google, this is the old experience, I've got all of these different recommendations, and they'll be sponsored products at the top, and I'll probably scroll past those and keep scrolling and scrolling and scrolling endlessly. I might have to go to page two, page three, and I'll give up. altogether. And I'll go to a site that I already know, to a brand that I already know, where I'll be met with thousands of different categories, different filters, different colors. I'll have to pick my size. Am I petite or standard? Don't answer that. We know that. And it's such a frustrating experience. And it's not just a frustrating experience for me as a customer. It's a really frustrating experience when I actually get to the product that I want and it's out of stock and I give up entirely and go to a different brand because that merchant actually knew who I was. I went to that brand specifically because I returned an item three weeks ago, I had been in their store, I have a credit card on file and yet they can't actually track me and talk to me like their own customer. And why they can't do that is because there's data that is located in silos across an entire organization whether or not it's the customer behavior in the CRM or it's the catalog data that's in the PIM or the where my order is data that's gonna be with supply chain it's all in different areas now the infrastructure that we're talking about is connecting the dots between that moment of discovery within AI and LLM recommendations all the way to capturing that moment once you enter the site, which I'll go through in that new experience which we are calling Resolve Commerce. So now let's fast forward to the happy future. And this will be the experience that I will experience as a customer when I'm working with Resolve Technology and a retailer. So now let's go back. So I need that coat again. It needs to be a warm winter coat for NRF in January. And what I'm going to do is I'm actually just going to go to my favorite LLM. And this is the flywheel that we're talking about. I go to my favorite LLM, I type in all of the context that I need because it's actually not just NRF, I'm also going to need it prior for the ski season, it also has to be business casual and how do you do business casual when you look like a marshmallow in these winter And so I go to my favorite LLM, three to four recommendations later, I click through and I go directly to a site, and then I'm captured by this wonderful concierge that greets me at the storefront, on the digital storefront, and says, welcome back. Already knows who I am, already knows what I've bought, already knows what colors I tend to like, what kind of things I may have sent back, for example, and even gives me recommendations of things that I may want next based on my purchasing behavior. That's the kind of personalization we're talking about. So not only have I skipped all of these massive frustrating steps, I have also been able to find exactly what I want in a very short period of time and they've upsold me to all of the hat glove accessories. So now that's the experience of Resolve Commerce. Let's move on to the actual transaction which is Resolve Pay. They already have my credit card information. And when Resolve Pay is live, there will be an elegant handoff where essentially I transact through the exact same platform. And there will be a balance that's live on my site, or that's live within my account that I'll be able to go and spend again. And it will incentivize me to actually come back because who doesn't love a balance? And then Resolve Reward, through loyalty, will re-engage me with offers that are available within my own bank payment apps that has scrolled through and seen all of the different things that I've purchased and given me an offer that is personalized just for me for that store that I can go back and redeem whenever I choose to go back and the merchant will have offered that up and it will actually, they'll pay for it once I actually get there. And finally, there's Resolve Insights. Now, this is the part that actually really excites me, and I'm excited to have James up here to talk about it a little bit, because as somebody who has been in retail for a really long time, both in consumer goods especially and in retailers as well, insights are super, super valuable in the era of AI. It's something that is monetizable in hundreds of different ways, and I can say that also having been in that business for a long time. So being able to take those insights and eventually turn them into something that will drive your discovery and your visibility, taking data that comes through conversation and being able to enrich it in your PIM so that you have machine-readable data like we talked about, you're able to discover it or use it for discoverability in LLMs, that's all driving the sale. Instead of missed sales, what you're seeing is that flywheel getting stronger and stronger and stronger. every single time that it's getting used. We're trusted by well over 1,000 customers and I know you see a lot of these logos, they're familiar to everybody. This is what we are doing today. We are helping retailers to get chosen, get paid, get real incentives that drive a loyalty base with AI and drive higher and higher likelihood of being chosen the next time that a customer comes and does a query and being chosen in those three to four recommendations. The longer that the flywheel runs, like I said, the more valuable it becomes. And we are the only company building the entire sequence of discovery all the way to checkout, all the way to insights, all the way back to being chosen again. this is the new conversion loop that we're talking about essentially like I said sales funnel has collapsed and now we think of it as more of a flywheel and we're doing it with one layer that is no rip and replace for a cut for a retailer that as we know has a lot of legacy technology our customers today are mid to large enterprises, 200 million GMV in both the hospitality and in the enterprise merchant space. However, we're actually aiming up the curve to over 500 million. This is not a pilot. This is a full transformation. This is a board decision. So it's with my honor to be able to present to you the first person who's going to go a lot deeper into all of these aspects of getting chosen, which is Lawrence O'Toole. Thank you so much.

Thank you, Michelle. I must confess, I can relate to that shopper, and I brought the evidence. This is everything I've purchased so far this year, sorted into three columns by how I chose it, or should I say by how AI chose it for me. On the left, AI researched, evaluated, shortlisted and recommended everything on that list. From a sensible German electric car for the family to a second-hand car for my daughter after she drove the first one into our house, yes, really, to a wood logger chopper, something else for shifting logs, I don't even know what it's called, an electric chainsaw. My point is this. 80% of my expenditure was here, was fully researched and evaluated and recommended and shortlisted by AI. Two years ago, that would have been zero. In the middle, this is where the volume is. Low value commodities, over 150. Items that I wasted my time researching manually, comparing potato peelers and waste bins and extension leads and car shampoo. My car doesn't care what car shampoo I use, and nor do I. I would happily hand all these over to an agent. I will, as long as it buys reputable products from reputable retailers with a good returns policy. And finally, still manual for now, the stuff I care enough about to read the reviews and actually watch the YouTube videos. But for me, that list is getting shorter every single year. I'm Lawrence O'Toole. I spent my career optimizing websites for search engines and more traditionally now, recently, for AI search engines. What my purchase habits tell me is if you are missing from the AI shortlist, you're going to miss out on the sale. And there's two factors driving this that I want to cover. First is machines are reading more data than humans these days, and the humans are telling the machines much greater context about what they want. I want to look at each of those in turn, and then look at what that means for merchants and how we can help them. So, according to Cloudflare, 62% of traffic on the web now is bot traffic, and it's growing. It's almost two to one. That gap is widening. Why? You make a query to an AI engine, as Dan mentioned earlier, and it does multiple queries behind the scenes, reads dozens of web pages. You hand that to an autonomous agent that's running 24-7, and that multiplies and multiplies I think what's really interesting is human security did a research last year, and it said, well, where are these AI agents going? 87% of the pages they're reading are product pages. Why? Large language models have training data, and it has cut-off dates. So to offer agentic commerce, to offer great recommendations to clients, they need accurate information. They need accurate product feed information. That means descriptions. That means conversational attributes so they can match the right customer to the right product in the right moment. They also need things like agentic decision-making factors like popularity rank and return rate. You'll notice that Google, Microsoft, OpenAI, et cetera, have all added these conversational attributes to their product feeds. Google recently announced that retailers that meet their best practices for agentic commerce feeds see a 4.5% increase in conversion value and 5% increase in conversions in the following month after implementation. So the AI platforms have articulated for us what it means to be successful in agentic commerce. And as consumers, we're articulating more about what we want. Google, again, said that queries in AI mode are three times longer than they are in traditional search. Our own research into Grot Conversations showed that 85% of them are longer than 10 words. ChatGPT has researched 75% longer than 10 words. As consumers, we're sharing greater context than we've ever done before. Why? Because we get better answers. And so that means we don't just express what we want, we express why. A couple of years ago, I'd have searched for a backpack and then gone through 10 organic links and visited lots of websites. Now I can describe that I'm looking for a backpack that fits a 17-inch laptop. It's waterproof. It's got rugged zips. It's going to go on a bike a lot. The retailer's catalogue needs to match that context. And if it does, then it stands a great chance of getting shortlisted by the AI agents. And AI agents, large language models, the platforms out there, They understand that consumers, we still like to window shop, but they will present a shortlist to us. Very rarely do they give a single best answer. Our research shows only 3% of the time for unbranded queries do AI answers contain just one brand. Even if you're named and your brand is mentioned in the prompt, 76% of the time alternative competitors will show up on that shortlist. And the thing about shortlists are consumers like them. Growth Memo did some research that said 74% of time, consumers don't go beyond the shortlist. They're happy with the options, and they evaluate and purchase from there. And that varies by category. Some are higher in other categories. I've spent 25 years optimizing for search engines. And what I've learned over time is that I used to help brands get to number one on Google. Now it's about being on the shortlist consistently. and most retailers are not ready. Most retailers are running on a Google Merchant Center feed that was built a decade ago that doesn't really understand intent. There's millions of Shopify stores that are arguably technically enabled for agentic commerce and yet they don't have the context that the AI engines require. It's not enough to be named as a brand. It's not enough to be well known. You need to add the live conversational attributes, the real-life context around your products so that large language models, these AI agents, can match the right customer in the right moment to your products and services. And also, you need to ensure that your marketing claims are corroborated across the web for AI to trust you. This is interesting. Our own research showed that 97%, 97 out of 100 of the top US retailers publish no way for an agent to check out on their site. That's the opportunity in one number. And that opportunity compounds because the sources and websites that AI trusts today are the ones that will be coming back to tomorrow. And we're building the solutions for tomorrow, today, for our retailers to capitalize on this opportunity. Our optimisation layer for agent e-commerce helps the merchant win the sale, whether that happens off-site on a platform or on their store, whether that's bought by a human or whether it's bought by an agent. It's one platform, three layers. We land once, and then we can expand into the other areas. Our SEO platform has done what digital marketing teams always need. Optimise your performance for Google and Bing. That market hasn't gone away. It's still there, and it's still critical. The Answer Engine Optimization Platform helps you understand how you stand across ChatGPT, Google AI mode, Gemini, Claude, Perplexity, and so on. It helps you understand your brand's visibility, its perception, which products it sells, the merchants, and which sources the AI uses to frame their answers. And finally, our Argentic Commerce Platform helps optimise at scale. And this is the one I'd ask you to remember because it clearly differentiates us from every single other SEO and AEO platform out there. Our agentic commerce engine reasons about the why behind your product. If you think about every product and every catalogue out there, someone, a designer, built a product with a consumer, B2B or B2C or a set of consumers in mind. But often, that's just lost across the e-commerce supply chain and ends up with a couple of bullet points on a PDP page, a product detail page. We think about the why. We think about the real-life context. What are these scenarios, the applications, the use cases, the time and the occasions that would give rise to someone to need to buy these products? And we put that back into the content in a way that helps sell the products for humans. It helps search engine bots find it, and it's irresistible to AI agents. Here's a quick preview of what that looks like. So let's say I'm trying to sell men's jackets. Our framework, our research framework, thinks about the key commercial criteria that are important to customers when they're buying that. We can build a set of research prompts that are representative and check any of the major platforms out there. Once we're there, we can help you understand your visibility, your perception, whether the top products, the top merchants, and what are the key sources that the large language models are relying on to formulate their answers. We can then give you and your marketing team a set of precise data-driven recommendations to help you improve your visibility. Beyond that, with our agentic commerce engine, we will reason about your catalogue. We can ingest your whole catalogue, we can think through our contextual engine about all the scenarios, all the applications, all the use cases even possible objections, key entities we need to mention and we can put real life information on the product page who's this for, what's it suited for, this is ideal for we can think about the agentic conversational attributes and enrich a feed, so this is no longer just a rain jacket this is a rain jacket for commuting in inclement British weather or for hiking or for dog walking. We go through the whole catalogue and enrich absolutely everything you need. We can build the technical foundations and tests to help your team get agentic ready and we can run experiments so you can drive real ROI. In essence, we can tell you how you're performing across AI engines, why you're performing like that and what on earth you need to do about it. Get that right, and the sale happens four ways. It can happen inside the AI platform. It can happen agent to agent, machine to machine. It can happen with click and collect in-store. And this is where our location-based technology kicks in. With her permission, when she enters a zone, even down to the collection bay, we can ensure that we trigger an alert to staff so that coat isn't ready the moment Michelle arrives in the collection bay. Not only that, we can use that to trigger offers, loyalties, and post-sale follow-ups. All on the stack a retailer runs today. And finally, the fourth way the sale happens is the way it's happened for many years. It's that she'll arrive on your website, ready to buy mid-conversation, and the next 30 seconds is the difference between making the sale and close browser tab. But that's David's territory more than mine. So over to you, David.

Thank you, Lawrence.

Hi, I'm David Ingram. I've been operating in e-commerce for about 30 years. You can tell that. Starting with delivering some of the first e-commerce solutions back in 1995. In fact, when I started, there were no e-commerce platforms. We had to custom build each one. there were also no merchant accounts for online retailers we had to convince acquirers to accept our customers on a case-by-case basis it was extremely laborious so I've seen and I've lived a large part of this evolution in e-commerce over this time but honestly I've never seen anything like the opportunity that's presenting today So I'm going to talk to you about and show you some of the other elements of Resolve Commerce, but I'm going to start by outlining some of the context that all this sits within. Familiar phrase, right? We see it everywhere. This term, agentic commerce, this concept, it's unfolding before us at absolute lightning speed. Everybody's talking about it, and it's a huge topic. So I'd like to give you a bit of a model with which to think about it, and it's a model that I've found to be helpful over the last couple of years during this journey. So firstly, AI assistants are starting to replace search as the entry point for e-commerce. So we used to start shopping on a search engine. We'd find a set of results. we click through to the brand's website and then we continue from there but now consumers, folks like you and I we're starting that journey on an AI assistant not on a search engine we're still ending up on the brand's website but not from that traditional referrer this is great for sellers But also, as our agents become more capable, many of you will have already seen this. Some of us are actually completing purchases right inside our agent's brand surface. If you think about that now, increasingly, we're not only starting our journey, but also completing our journey on the AI brand surface. So we never actually see that carefully crafted, beautiful brand experience that retailers have been optimizing for human users for 30-odd years. That's not the end of it. Because in some cases, and increasingly in the future, we're actually empowering our agents to buy for us. So we're giving our agents an objective or a goal, if you like. We're giving them some permissions and some constraints. but it's our agents that are doing the exploring. It's our agents that are deciding, and it's our agents that are actually executing the purchase. So I'll summarize these models in a way that's really easily memorable. Here, agents are helping us find stuff. Here, agents are actually buying for us. Let's rewind. Here, they're helping us buy, right? But here, they're starting to buy for us. It's all very interesting, but so what? So what? Well, here's the what, because for sellers, that brings both good news and bad news. The good news is this. AI referrer traffic, that's users who started a journey on an AI, are referring or converting 60% better versus those consumers that started their journey in traditional search. But the bad news is that up to 41% of that content is not accessible to AI agents. Lawrence touched on this. In fact, even that which is is largely still optimized for human visitors, not for agents. So it's interesting for us as Resolve because this means retailers just cannot sit still. They must take action. If they're to defend against this problem, they really, really need to know how they're showing up on agents and they need to fix that data. And they also need to protect against that dilution of their brand and that loss of ownership of their customers because customers, again, like you and I, we're increasingly training ourselves to shop in different ways. And they've got to attack. They have to be on the front foot if they're going to grab the opportunity that agentic commerce promises them. It's higher conversion. So I'm looking around the room. Most of us have been around for a while. We've been in e-commerce for a while, or we've been on the periphery of it. But until this point in history, right now, it's remained largely unchanged. Search, results, click-through, pagination, filters, sorting, search again, repeat, repeat, repeat. The sort of stuff that Dan talked about. We've seen improvements. We've seen iterations. We've seen evolution. But now everything's changing. It's no longer evolution. It's an absolute revolution. It's not a trend. It's a structural shift. And that's what Resolve is solving for. Most people are thinking about what new AI features to add to their products. But Resolve is building that infrastructure, that platform, for this entirely new mode of commerce. A lot to think about. So let's just recenter our thoughts for a moment. You saw this picture earlier today. At the highest level, Michelle showed you what Resolve was building. She showed you this map. Resolve commerce, resolve pay, resolve reward, resolve insights, and this incredible flywheel that this creates. And as sellers start to prepare for agentic commerce, Lawrence showed you how Resolve is giving retailers these essential tools to know how they show up for agents and why they show up or why they don't and how to optimize accordingly. And Naga is going to explain how Resolve Pay introduces modern payments going beyond that 30-year-old payment paradigm that all sellers have been operating for 30 years. And James is going to explain how Resolve Reward and Resolve Insights help sellers stay competitive and build and own that loyalty in their customers. and how that wealth of data and information that's generated further fuels this flywheel that we're building. Which leaves me somewhat in the middle. And in particular, I want to show you what conversational commerce looks like. So we're going to roll a short live demo. Hey, I'm going to be demoing some of your capabilities to some folks that I have in the room here, and you're going to help me. So, to get us started, why don't you show me a selection of men's leisure wear to inspire me?

So, a broad search.

Right, understood. Digging out some relaxed styles for you. I'm scanning our leisure wear options. The Jersey Lounge Relax Shorts and Stretch Modal Snuggle Sweatpants are great for pure comfort, while the Ponto Performance Sweatpants from Viore give you a more sporty feel. If you're looking for something a bit more polished, the Hadiko cuffed sweatpants from Boss or the Supima cotton straight sweatpants from Marco Pescarola are lovely options for smart leisure. We've also got some versatile shorts like the stretch cotton shorts or the modal blend ultra shorts to round things out.

Comprehensive knowledge of the products in the merchandise. That is great inspiration. And you know what? I'm going to a wedding in Tuscany in August and I think a formal men's suit in a light colour might be the perfect thing. what can you show me? Different type of search, right? Use case, scenario, event.

Okay, a wedding in Tuscany sounds absolutely lovely. I'm rounding up some light-colored formal suits for you. The linen double-breasted suit from Giorgio Armani would be a stunning choice for a Tuscan wedding, and the linen wool two-piece suit from Boss is another lovely option for that setting. I've also found the wool slim blazer in beige from the Couples, if you prefer to build the look piece by piece i tell you what that boss linen wool two-piece looks like the one can you show me the details drilling down now traditional all right i'm grabbing the details on that boss suit for you of course i've pulled up the details for the linen wool two-piece suit from boss it's a lovely blend of linen and wool which makes it both comfortable for a summer wedding and durable enough to last for years we've got it in sizes 44 through 54. you know i've already got some stuff in my fitting room why don't you add this to my fitting room as well then show me what the whole set looks like together the sort of experience you'd get in a store but it's a little tricky to get okay understood it's going to be a fantastic ensemble i'm pulling up the full look for you i've added that linen wool two-piece suit to your fitting room and i've pulled up the full look for you including the linen shirt the leather loafers and the suede belt that is a sharp look okay i love it all add it all to my cart and let's checkout.

I'm not sure I'd get away with that colour in real life.

I see I'm moving those pieces into your basket and getting the checkout ready for you. I've pulled up the checkout for you but I'll need to know your sizes for those items before we can finish up. What sizes should I get for the linen wool two-piece suit, the linen shirt, the leather loafers and the suede belt?

For the belt, 80. For the loafers, 42. The shirt, I'll have a medium. And the suit, let's go 44. Complex compound discussion.

Noted. Sorting through those sizes to get everything into your basket. Everything's all set in your basket. I've pulled up the checkout now so you can complete your payment and wrap this up.

You can immediately see where Resolve Pay fits in.

Okay, I see. Thank you so much for shopping with us. I've got your suede belt, leather loafers, linen shirt and linen wool two-piece suit all on their way to you now. I hope you have a wonderful time at the wedding in Tuscany.

Fantastic. Thank you. I'll see you again. So I very much look forward to being able to show you that once Resolve Pay is on the end, closing that loop. Quick recap. Now, today's e-commerce UX, it's 30 years old. It's changing. Brain power. It's our proprietary AI stack. It's domain-specific, it's commerce-trained, and it's grounded in merchant data, so it won't invent facts. It engages with empathy. It holds a natural, flowing conversation. But it also understands that intent expressed actually translates into goals. The goal is selling. Multimodal UIs like you saw there, voice, web, text, image, they're all interconnected through that conversational context. And it's deployable on any brand surface. So responsive web, mobile app, in-store kiosk, smart speaker, smart glasses. even in your car. So that's conversational commerce. I'll hand to Naga, who's going to pick up the journey with Resolve Pay.

Morning, everyone. For those I have not yet met, I'm Naga Samnini, CEO of Resolve Pay. I built my career starting as an engineer at Microsoft and Twitter before moving to Facebook, where I worked in the leadership of global payments. I then built and exited my own payments company. I joined Dan and the team here about six months ago, and I'm really excited to show you the inside of the early stages of what we're building at Resolve Pay. You have now seen almost the entirety of the customer journey that Resolve AI runs for the merchants, From helping brands get discovered to converting interest into purchases and helping drive repeat business, every retailer wants all of these activities to end up in the exact same place. And that is checkout. And it turns out checkout is that one part of this journey that we currently hand off to someone else today. And it also turns out, it's also the part that the merchant has least control over and has the most to lose from. And getting that right is exactly what number two on the priorities that Dan set out earlier this morning is all about, owning the payment. You see, cash was the last payment method that worked beautifully for the merchant because $100 in sales meant $100 in revenue. You see, nothing at all was actually lost in the act of getting paid. And money landed the moment the sale was complete. And every system that was built since was built actually for somebody else, whether it's the bank, whether it's a payment network, whether it's a shopper. And don't get me wrong, every payment method has brought about a genuine improvement for the people for whom the payment methods were designed around. But it turns out Merchant was the one who quietly ended up paying for all of them. Let's zoom in on this for a second. On what happens today when a shopper pays by card. You see a series of intermediaries start up and take a slice of the sale. And every slice, it turns out, is charged as a percentage of the transaction and not a percentage of the profit that the merchant actually keeps. As we see, the 2.3% of the fee that we are talking about for the merchant seems small, but put in context, it's a fifth of the merchant's profits. And there is the wait. A sale that closed on a Friday afternoon doesn't hit the merchant's bank until the following Tuesday. The industry calls it the two-day business standard. Because as we all know, money and computers love to take the weekend off. That's why. I'll sit with that for a second because that's the part that a lot of people overlook. This is merchant's own money that they've already earned, that the customer has already spent sitting in someone else's banking account for three days. And this happens on every transaction in the entire year. Now, every CFO knows what that means for the working capital for the merchant. And here's the part that I find extraordinary. If you ask anyone in the payments industry whether this experience for the merchants can be better, they'll tell you, of course it can. But when you ask them if they're going to fix it, of course they're not. Because you see, when they take a percentage of the sale, that is their entire revenue. It's this classic innovator's dilemma where when inefficiency becomes the business model, people who are on the inside, don't go out looking for the cure. Now, before I tell you what we are building, I want to be straight about the field that we are entering. You see, payments is actually a crowded space. A great many number of companies have raised a great deal of capital on the promise of building a better checkout, and the results have genuinely been mixed so far. Some of them have actually gotten parts of it right, and they're still going strong today. But a lot more of them, even after raising enormous sums, are no longer here to tell their tale. However, almost every one of those items started first in payments and worked backwards into understanding commerce. But we are actually coming from commerce and working forward into building payments. because we have much deeper context and empathy for what commerce really wants based on our background. And I think that's a meaningfully different place to start from. What we're building is payments that is reinvented. Reinvented around a better experience and better economics for both the merchant and the shopper. And we are uniquely placed to solve this problem. because every single product that Resolve AI sells to merchants comes with the same promise of converting a browser into a buyer. This conversion is that one single thread that stitches and runs through every part of our business. Now, as you have heard from our colleagues today, it turns out 7 out of 10 shopping carts are actually abandoned. When you break it down, extra costs at checkout accounts for about 40% of those abandonments. Lack of trust in storing cart details with a merchant's account for 19%. Being forced to create accounts costs about 18% of cart abandonments. And at checkout, that simply takes too long. and the 17%. Now, on reading this, it actually gets clear for us that what appears on the surface as a marketing problem because the customer lost interest in the product that they want to buy is actually an engineering problem. You see, because these are not the customers who lost interest about the product, they were actually interested in it, but at some point along the way, they just gave up. now think about what that means for a company like ours because we spent the entire customer journey earning a customer's attention sparking their interest in the products and the brand and building their conviction around the products that they actually want to take home and in the final step when it really matters they meet at checkout which is what we don't build today and the entire work that we put in for running this customer journey is left exposed to the sale leaking at the worst possible moment. But if we control this journey end-to-end, what that means is that we shape the problem entirely. Because every step is now built with one objective instead of being handed off to someone else at the point of greatest risk. And that is how it's a commerce argument before it is even a payments argument. And that's precisely why I believe we are the company to solve payments. Let me tell you what we are building. Resolve Pay will be the most beautiful opinionated checkout product that is rail agnostic powered by Resolve AI's own technology. And it carries every single payment option that a customer expects to find today. Whether it's a card, whether it's Apple Pay, whether it is Google Pay, or whether it is pay-by-bank, doesn't matter. The important part is what actually sits behind. The payment details are tokenized and are stored centrally instead of at each individual merchants. And what that means for the merchants is all the benefits of saving the customer's card on file without the drawbacks and the risks of doing such. And what this also means for the shopper is that once they get themselves set up on one merchant in our network, they arrive at the next one with their details already filled in and ready to go. They don't even have to type a thing. And this effect compounds. Every merchant who joins our network makes it better and more valuable for every merchant that already exists and every merchant that's going to come after because of the shoppers that come in already enrolled. Finally, because Resolve Pay will be vertically integrated with Resolve Commerce, that decreases dramatically the friction between intent and customers walking home with their product. The first reason why I find this really exciting is that it directly addresses the abandonment issue that we talked about. Because the card details are never stored at the merchants, we take back the 19% of card abandonments. And because nobody's forced to create account twice, that's 18% of abandonment taken back. And because the checkouts are now faster than before, that's 17%. You see, three of the four largest fixable reasons why a shopper walks away from a sale are answered simply by the design of the product, even before we get into engineering and optimizing the margins. And the second reason why this really excites me is the economics. The Resolve way, merchants can set a cash back rate that rewards the shopper for choosing our recommended payment method. A payment method that carries lower cost of processing and lower cost of service for the merchant. And that reward, well, it directly gets applied and triggered at the checkout. This is what I call a win-win. The shoppers get a better deal. the merchant sees their blended processing costs come down and the merchants' margins improve with every shopper that converts. And that's what we do. Now, before we shift gears, the last thing that I want to talk about this, and this is really important, is that all of this sits on merchants' existing system. We're not asking them to switch to anything and rip and replace anything. All their existing systems, their existing order management systems, their backends, their existing payment processor contracts, they can stay intact. We work with all of them. We sit on a layer above that. I want to finish by looking forward. As you have heard from my colleagues today all morning, commerce as we know it is changing. And what that means is payment as we know it will change too. As Michelle set out this morning, agents are now transacting. increasingly the buyer arriving at a checkout page is not a person at all it's software software that knows who you are that's acting on your behalf that carries your preferences your loyalty your payment methods your payment mandates that's the next buyer and this this and this is not a distant picture that we are chalking up in the whiteboards of san francisco So this is actually what is happening today, live. And it is increasingly accelerating, thanks to all the advancements that the market is seeing today, with Muse, OpenAI, everybody else. Now, think about what that asks of a payment system that is built for the yesteryears. Because a checkout that is built for a human is the wrong shape for the new buyer, which is a machine. Now, the industry hasn't settled yet on how agents will pay. There are several standards that are being proposed all the time, and the industry is yet to coalesce on the one standard. But whatever it will end up being, we are building the layer that is one above it all. We are not a button in someone else's system. So we don't have to pick the winners. We don't have to pick the standards that win. We support them all. And because shoppers' details are already held securely at the network level, what that means is that the agent can now transact end-to-end without touching anything that is sensitive. There is a great deal more to come from here and I'm looking forward to sharing with that soon as we reach the market. Now I know every one of you wants to learn more about what it means with Muse and OpenAI and how does all of this work with Resolve and Resolve Pay. I'm excited to share that with you in the next few days. And with that, I'll hand this off to James, who will walk you through Resolve Reward and Resolve Insights.

Thank you very much, Naga, and good morning, everyone. It's great to be here with you today. I'm James House. I'm the CEO of Resolve Reward. I've spent 30 years in loyalty data and technology companies and in leadership roles within Mastercard and BMP Paribas, amongst others. I think you've just heard from Naga very clearly how Resolve Pay is reducing friction for the customer in the moment of payment. I'm going to talk to you now a little bit about how Resolve Reward is really extending that reach into the broader customer relationship. So Resolve Reward, for those of you who aren't familiar, sits at the intersection of banking and commerce. Our banking partners bring customers, a trusted network, we all trust our banks, and transaction data. Our merchant partners bring a demand for profitable growth. We take the bank's first-party transaction data, be that from a current account or a checking account, a credit card transaction or a debit card transaction, and we turn that into actionable customer intelligence. This intelligence drives more relevant customer engagement for both the banks and the merchants, so we start to create this virtuous circle. Most importantly, and I think this is a really important point, especially in today's economic environment, is we close the loop to the actual purchase. I think every marketer today really wants to understand where they invest their dollars and where it has the biggest impact. And we bring the most powerful source of measurement, which is actually the transaction. So I'm going to take the next 10 minutes, really, just to tell you a little bit more about Resolve Reward and Resolve Insights as well. So as you can see here, Reward is operating at a global scale. We're in 15 major markets, and we're delivering programs to engage over 14 million consumers. We have over 30 major financial institution and payment partnerships, and this really spans the major schemes, as you can see, from Visa, MasterCard, and Amex, to some of the world's leading issuing banks, and also to some innovative fintechs such as Zilch, for example. We analyzed over 100 billion transactions in the UK market. That is one in three transactions alone that we're actually analyzing. And that represents around $140 billion in annual spend. So you can see a real power in terms of the depth of insight that we're deriving. We also connect over 30,000 retail outlets and several hundred merchant partners. And you can see in the corner there some major brands from Starbucks, McDonald's, Disney, Deliveroo, now part of DoorDash, Uber Eats, amongst others. I could go on. We're connecting everyday spend categories here. So we span QSR, grocery, fashion retail, specialty retail, media and telco, amongst other sectors. So we really have every element of consumer purchasing covered. And importantly as well, we've returned over $2 billion of value back to consumers. So consumers are deriving significant value from being part of our programs. We operate a very powerful self-reinforcing cycle. It starts at the center with engaged bank customers. So everything we do for our banking partners is about driving deeper and richer customer engagement. That gives us access to the data that I spoke about so we can understand where customers are shopping, how often they shop, how much do they spend, how loyal are they, how do they switch between different brands. So there's a real, real power. And I struggle, and I've worked in data for 30 years, to identify a more powerful source of consumer intelligence. So we take that data and we derive intelligence from it. That can be segments, that can be propensities, that can be helping our clients make better business decisions as we go forward. Who to target, with what proposition and where to invest. And then importantly, we then can activate on those audiences and measure the resulting transactions. So I think, again, in today's market, there's a plethora of insights available to marketers. I think what we're able to do is actually deliver the richest sort of intelligence activator on it and then measure it. And as you can see, the more engaged customers that we get, the more data we get, the better the targeting, the segmentation, and the propensities are going forward. And that's the compelling cycle that we operate. I think further kind of positive news is that there's a massive growth opportunity for our business. We have significant tailwinds in each of the three markets that we operate in, customer engagement, commerce, media, and consumer insights. Within customer engagement for banks, we've talked about the propensity towards digital payments. Naga mentioned, the shift away from cash. We can talk to the battle for top of wallet status. So every customer now is operating a wallet with multiple bank cards. Every bank wants to be top of wallet. And every bank wants to create new ways to engage with consumers. Let's face it, our banking relationships haven't been always the most exciting. Banks are looking to create new ways to connect with consumers and drive NPS. For merchants, the challenge is how do you drive greater ROI? Most marketing budgets are challenged. How do you deliver greater uplifts? And importantly as well, how can you drive deterministic measures? Obviously, the advertising industry has been heavily governed by proxies like clicks, propensities, and impressions. We bring the definitive deterministic measure in terms of transactions. That said, we're expanding our heritage from banking, loyalty, and card-linked commerce into these three connected markets. Together, they represent a $40 billion addressable opportunity for Resolve reward. Retailers need a better customer understanding and demonstrable ROI. We're connecting these three areas under what we call our finance media network. This enables bank distribution, customer intelligence, and merchant activation to be measured against actual spend. I said one of the key growth areas for our organization was consumer insights. And this is why we're doubling down on what we call resolve insights. We've spoken about how we use data to drive activation to enable people to drive better advertising campaigns We can also use our intelligence to drive better commercial decisions And this is really where we're doubling down as a growth growth driver You can see here. We already have some strong foundations through partnerships with leading global data and insight players This includes Experian affinity solutions here in the US and and CACI, as well as a number of consumer-facing brands, including Deliveroo, Nike, Asda, and Domino's, all major brands who are using our insight. They're not just using this to activate, they're using this to make decisions around which customer segments they want to grow, which locations do they want to build, which categories do they want to focus on, how do they think about time of day in terms of how they service different customers, how do they think about potential strategic acquisitions. I could go on. There's many, many use cases for our insights. Most importantly, this for us creates a high value differentiated recurring revenue stream through what we call data as a service provision. I'm just going to spend a couple of minutes now and show you a short demo video. This is showing how our product is embedded within a banking app. We've kind of made it a generic example, but you could go to any of our banking partners and be able to see how we embed in the banking app. As it goes through, I'll just kind of voice over a few of the key features. There we go. It's working. So the technology is embedded in the client's banking app. It's a seamless customer experience, so the customer doesn't have to move between apps or change browser or anything. It's API deployment within a matter of weeks, and it delivers a modular or end-to-end loyalty capability. And what I mean by that is there's the opportunity to be a collection partner, but also a burn partner as well. And we deliver hyper-personalized rewards, both in terms of earn and burn opportunities. And as well as card-linked offers, you can see here, this is an example within the marketplace, you can convert the cash back you've earned to a whole host of different leading partners based on your selections. This is where we measure the commercial outcome through actual transactions. Everything we do within the app is driven by AI and machine learning, strengthening segmentation, personalization, and measurement. But don't just take it from me. I think the great thing about Resolve Rewards is we've got some fantastic banking partners, both old and new. I'm going to talk first to NatWest, which is one of our longest-standing banking customers. We've had a relationship with them for more than 10 years, and I think that shows the value that we deliver to the program. You can read the quote there from Lewis. I won't go through it verbatim, but we combine transaction intelligence, digital engagement, and relative retail content. And as you can imagine, the transition that NatWest, one of the UK's traditional high street banks, has been through through digitization over the last 10 years, we've been delighted to kind of partner with them during that transformation. Mashrec is a newer partner for Resolve Reward. For those of you who don't know, it's one of the leading fintechs within the UAE. And we've operated and launched a new program with them through our global partner, Visa. So it's showing really how we can operate and replicate our model at a global scale and how we work with distribution partners such as Visa. Both connect real purchasing behavior and demonstrate enterprise durability, measurable outcomes, and importantly, global scalability. I'm now going to hand over to Shovig. We've heard how Resolve Reward creates commercial value across banking and commerce. Shovig's now going to take us through the underlying AI infrastructure that supports everything that you've heard so far this morning. Thank you very much.

Good morning. Good morning, everyone. My name is Shovig Banerjee. I'm the group CTO for Resolve AI. Having built large tech businesses, having led large technology organizations from SAP, Accenture Digital, and of course, having met Dan two decades back in our journey to building vendor, where e-commerce and AI is something which has kind of become the DNA of my existence. Now, imagine the world we are living in today. Some of us have built these e-commerce engines over the last few years. And you saw how unparalleledly we are chartering this territory. Agents are going to swarm across. You've heard Lawrence, you've heard David, you've heard Michelle. Now, today, I'm going to talk about what's the core technology which differentiates us. This is what actually is what you've been hearing from the morning. Get chosen, the discovery part. Get paid, the checkout part. Get loyalty, James just spoke about it. And the whole flywheel of data comes back. get chosen again. This is the commerce, this is the future of purchase. What we are talking over here is that's the stack. But what runs that stack? What it runs the stack is brain power, which is our morals, our voice orchestration, our agents, our agent orchestration, and of course, underneath is the ethics and compliance stack. And, of course, we've got the whole database as a service, which is something very exciting we are building on. I'm going to talk about it in a few minutes. That's the technology backbone of what everyone has been explaining from the morning. I want you guys to take 10 seconds on this slide to understand these three layers actually runs the entire front-facing engagements. and it's ready for a retailer to take on the swarm of the agents and accordingly. Let me just delve a little deep on brain power. I'm going to talk about the model part of brain power today, though the orchestration, the voice, the agentic, entire engine is all brain power. In the day, in October 2026, we keep hearing the words large language models is where the transaction will happen. We keep hearing inaccuracy. Now, if I look at what you see over here is a live commerce environment. Imagine it is expensive. The real world problem is these purpose-built LLMs, which you guys use all the time, is trying to guess. Now, think about the jacket use case Michelle was talking about. machine has to know before it can sell now none of that has ever appeared on the internet this catalog which is getting trained on brainpower is is trained on the catalog in itself it is not trained on internet words now when when we when we build this this not didn't get built with the explosion of LLMs in the last 24 months. This got built over the last 10 years and it got built on single industry category, 300 billion parameters, 30 billion parameters, 300 billion tokens and more importantly it's the results proprietary models. What we do with when we build it ourselves is we can't be the mecker and checker. We have to then benchmark it against everything else what exists and that's that's the part where the catalog requires the insight the model can rank model can pattern match model can converse extraction of the attribute comes across the mindset of the sentiment comes across but it still cannot do it cannot hallucinate it cannot model drift because we are playing with retailers brand it cannot have an impact on the erosion so let me tell you what we do and how we define that this is this is the brainpower resolves ethics ethics core we've got traceware now a common failure with AI agents is that it reports actions but which never took place example imagine an agent agent is looking at a screen it could go through the screen it doesn't understand the management, it doesn't understand a transaction, it might report an incorrect transaction which never got placed. Now what Traceware does, it through logs, it rebuilds that journey and says that transaction happened and that transaction didn't happen. So you have a maker and a checker framework. Our Traceware, our model runs between 99.5 to 100% accuracy on these sort of logs we check on, the agent's journeys. It's important because you can build a model, but you need to check it, right? And then comes auditable AI. You've heard us talking about hallucination-free and model drift, but we need that to benchmark it again. So what we did was the platform of auditable AI gives the outputs against other language model outputs. and that's extremely important for us to be neutrally judged from anybody who is commercially engaged with us. It gives the brands and the users a complete observability framework, a complete monitoring framework in what it intends to achieve. And AI behavior is something we are dealing with. It's human-like, but it's not a human being. So we've got to be very, very careful in what we are deploying to these platforms across these, across geographies. So we are very, very focused on what that does. Now, we've been in the business for quite some time, and something which we had built now has just taken off is any output of a catalog, image, video, audio of a PDP, we have a technology today which actually does the verification that's resolved provenance resolved provenance is exactly what it is it embeds invisible watermark on an image or a video or an audio and a text the future of PDP just got transformed and more importantly if I take it offline it can work on multiple form factors. So we are a very very deep tech company and this has been my founder chairman CEO's vision. This has been the vision of my chief scientist and chief AI officer Dr. Salman Ahmed and some of these brilliant minds I get the pleasure and opportunity to work with. Now let me show you what's the most exciting part we are working towards. You heard Naga, you heard you heard all our stacks on AI. Now imagine this, we grew up in a world of columnar and road based databases. Then came the world of in-memory, you know the Cassandra, the Hannahs of the world. Today, which is the network which is infinite scales in multi milliseconds? It's the blockchain. Imagine a catalog, 20 million catalog. Imagine a hundred million day of transaction like, you know, the festive days. We used to hear and I used to grow up with database jokes, systems would be down. No, this is where the world is moving forward. The brain powers database as a service powers the future of catalog, the future of e-commerce transactions, the future of concurrency on a user on a cart. We disclosed it in our annual report, Dan mentioned it, that we're going to make it commercial. It's almost there we are going to now roll it out across. Across our stacks which you saw is where we are championing database distributed database as a service. And we're always inventing. We're always inventing. We're always pioneering. That's our DNA. Resolve AI labs is one of our research divisions. we've got our teams across the globe right from here in the US across various places in Europe it is there in South America and of course it's in Asia but I run the team in India being the group CTO as well and and every day working for resolve is building inventing and what about my team calls all of us is problem-solving utopians. So that's the world we are building. Thank you for listening in. I'm going to hand it over to Elizabeth and Steve Perry and where we are going to have an engaging conversation. Over to you.

In incredible roles, head of strategy, chief financial officer, COO, CDO, and among many, the greatest successes have been 99% market share of debit payments in the U.K. We're spending debit cards on 3X credit cards. He's also had three terms with Apple Pay in Europe and leading the teams that rolled out chip and pin, which is insert your credit card and add your pin. You want this.

Is it a live mic? Okay, fabulous. and we're on and also tap and pay which here is called contactless he's our non-exec director of resolve ai and on our board so we're i'm just so honored you're here between us we have close to 50 years in financial services and technology again don't do the math and in that time we know that pay has changed and it's been rebuilt again contactless tap and pay which they say in the uk and digital wallets, which now includes our face. It's absolutely been astounding what's happening. This has changed how hundreds of millions of people behave at checkout. But the one thing that we know that hasn't changed is a cart abandonment. Seven of ten shoppers walk away from their cart. In the next 15 minutes, we're going to walk through why that is, what's broken, and how we can do the shift. Steve, you have spent 25 years selling payment capabilities to retailers. What has changed over that time, and what are merchants looking at today?

That's a great question, Elizabeth. Everybody hear me okay? Those 25 years really take me back to the birth of e-commerce. And in that time, I've seen all sorts of friction, layers of friction, layered in the payment value chain. Those layers of friction have nevertheless left e-commerce growing at a fantastic rate. But what I'd like to reflect on is the extent to which it could have grown at a much accelerated rate had those layers of friction not been there. I guess at the time, as one of the leaders in the industry, at least across Europe, there's a degree of culpability for the actions that we put in place. But at the time, they seemed right. So what we've got are layers of friction, but a developing e-commerce economy. What do merchants want? Well, they want that improved. What they actually want to see initially is an improvement in cart abandonment, resales, obviously. The second thing they're looking for is integrated rewards and loyalty, not the kind of network that I created many years ago. And finally, what they need is control. Control of the network, control of the system, and they need to be in a place whereby they own the customer relationship. And, of course, it's to be profitable. That's, I think, what merchants are looking for, given the development of e-commerce through the three phases that we saw Dan present at the very beginning.

No, I love that. I think we should... Can we break it down a little bit more? You know, that North Star that the retailers have always been working on is reducing that cart abandonment. And, you know, we know that's still at 70%, so it's barely moved, really. What is it about checkout process that's really broken today?

This is beginning to feel a little bit like therapy, where I reflect on some of the potential misdemeanors that I'm now owning up to that at the time seemed to be the right things to do. So one of the first misdemeanors was, along with the rest of the industry and bankers, to think about e-commerce as potentially the Wild West of payments. And if we weren't careful, we were going to hemorrhage fraud across the board. So it became a fantastic adventure in fraud management, and that's how we approached it. At the one extreme, zero transactions mean zero fraud. I understand that. We weren't that naive. We were after growth and were after transactions. But the endeavor to ensure that we kept fraud out of the system, which we did rather well, meant that we put layers of friction at every point. Not least of which, back in the day, yes, I'm that old, and you've made me feel very old today compared to how I felt first thing this morning. The layers we put in about inputting card numbers, addresses, CVV, and all those wonderful things created friction. And that was the first problem. The second problem was the level of friction that retailers put in our way. They understandably created websites, e-commerce sites, as if they were catalogs, as if it was their department store. Now, I showed you a picture of my little puppy today, and I can go online and I can buy a collar for my puppy. It's really straightforward. I didn't show you a picture of a very old classic car that I've got that has no capability of Bluetooth or Wi-Fi, but I want to play my Apple Music in it. I need a cable. That kind of search is impossible. It's a layer of friction that means I don't do it. I actually ask somebody else to do it for me, which is sort of where we're going. So as part of my therapy, I see the need to actually remove those areas of friction.

You know, that's a good point when you talk about friction. And when we look at the generations today, we know Generation Alpha are those kiddos that were born in 2010. Right now, that's $5 trillion in buyer opportunity in the next by 2029. And when you talk about them not having the patience for friction, that is true. They want instead of seven clicks to close, they want one. So time is now, really, to be frictionless and to really close and to really work on that cart abandonment. Now, when we look at loyalty and the programs and how they encourage customers to return, can an improved payment experience really complement this effort? What are your thoughts on that, Steve?

Once again, the therapy is really helpful because having dealt with the concept of fraud as being one of the overarching drivers of payments in e-commerce that I was trying to address 20-odd years ago, having felt that we dealt with it, having left the retailer to design their own websites and search engines within that, we then turned our attention to loyalty and rewards. And what we did was to take a leaf out of the book of the merchants and retailers. How did they do it? they gave consumers, once they'd filled a form in and sent it off by a post, a piece of plastic that they would take out at the till in order to enjoy their loyalty points, all of which was fine whilst there were two or three merchants. As that ballooned, and I remember my mother, who's about a foot shorter than me, would flick out her wallet with all those pieces of plastic and she would enjoy loyalty at every point of sale. We tried to do that in e-commerce. And therefore, we layered a piece of friction that was problematic and had no links between that and the payment transaction process layer. So again, we created a solution, but created friction. And we told them, poor old merchant, you take it or build your own.

No, that's a good point. And I think going back to what Michelle said about loyalty as well, is a one-stop, and having those merchants really understand who's in front of them and how that works.

Indeed, but I think part of this whole, and you'll enjoy this process of being, it's cathartic, this process of thinking about what might have gone wrong. You're in this positive space of putting things right. The third aspect of what I talked about, beyond the reward piece and beyond the payment piece and the search engine, is, of course, control. and retailers need and want to be in control of the process whilst remaining profitable. What can you say about that?

Yeah, that's right. And I actually think Naga landed that really well to say retail needs to own payments. And what does that look like now? I mean, they don't have control. And having that hardware and that maintenance and the people overlay, I mean, that's heavy lifting and upgrading all the time when it doesn't have to be that hard. In fact, the answer is the platform that gives them control and part of that entire journey process. and it can be as easy as just turning it on. So I think there's another way to look at it and we're excited to share more about what that looks like.

And that excitement comes from another step back into history. In the early 200s, the invention and introduction of PayPal. If you think of what they did, it was essentially put an account on file, take my payment credentials, hold on to them safely, which meant that when I could shop, I would simply dip into that and take a layer of the friction out. That was very clever. That dealt with a piece of friction. It didn't deal with anything else in terms of rewards, in terms of control, but it did take a layer of friction out and e-commerce took a positive spike upwards, albeit for PayPal at a significant premium, way above the 2% to 3% that we've already had demonstrated as typical card charges today. But it does show that new technologies, the elimination of friction leads to increased sales. And that's what the retailers were happy to pay for.

Absolutely. Retailers absolutely want more increased sales. I love that. And so far, we've talked about the retailers themselves, but we know the consumers are really important on this journey too and how they pay. And how do you actually get millions of people to do that, Steve? How do you share a bit of that with us?

Well, again, I'll go back in history, if I may, because that's where I spent most of my time, it would appear. The concept of chip and PIN, putting a chip on a payment card and then going to the point of sale, and instead of signing and entering my four-digit PIN to authenticate myself, was what we imported into Europe from Asia in the early 200s. And in 2004, I'll give you the example of the UK, as the market leader heading off towards that 99% market share in debit, I took a decision to think about creating chip and pin for the UK market, but in parallel with MasterCard and American Express. You've got to move the market in one go, is what we thought. So that meant conversations with MasterCard, American Express, terminal manufacturers, the biggest retailers, the underground system, buses. Oh, and I mustn't forget the retailers and the retailer associations, as we often did, and 30 to 40 different banking institutions issuing those cards. It was estimated it cost US$3 billion to move the UK market to chip and pin in 2004 prices. Multiply that across all of the markets, but we got the consumer on the journey. We don't face that issue now. First of all, we're not talking about a terminal infrastructure. We're talking about everything being digital. We're also talking about retailers who will go on the journey at their own pace. But I would worry about those that delayed, because the early mover, first mover advantage, is where this will deliver economic rent to the retailers. So it's a very different environment, very different to what we saw historically, but I think it's absolutely achievable. And the best thing of all that I've heard is that a consumer need only enter reward pay once, and then they are mobile throughout e-commerce.

Absolutely. And if we put it all together, Steve, if we move ourselves to the future, what does it look like?

I'm feeling cathartic, which is the first thing, which is wonderful. The second thing is I see e-commerce as being as simple as breathing, by which I mean none of us today think of their breath. I've had a little bit of a cough at the back, and I've been thinking a little bit about my breath, but fundamentally, you never think about your breath. The future of e-commerce for me is I never think in the future about the payment because it's going to happen. I never think about, am I going to get the reward? Because it's going to happen. All I think about is navigating the search engine that gets me the blue suit for Tuscany for the wedding. That's the only thing on my mind. It's the transaction. It's the enjoyment. It's the digital good that I'm buying. The rest of it is my breath. I'll only ever think about it as breath if I'm sitting here today on this stage and I get a text that says, thank you for buying a surfboard on Bonsai Beach. And then I might have a sharp intake of breath. But fundamentally, that's what the future looks like. When my friends, my family, and I just think of e-commerce as breathing.

I love that. And obviously, the retailers owning payments and the consumers having one click and done. So I think the combo is fantastic and here now to stay, absolutely. Thank you so much, Steve. it's been quite an honor. We want to thank all of you in the audience and those of you online. We really appreciate you spending time with us. We're going to come back. We're going to take a short break. So we welcome you to welcome some refreshments, to have some refreshments. We have some live demos outside. So please feel free to enjoy that experience. We'll be back at 11.45 to continue. So thank you, everybody. Thank you, Steve.

Welcome back to Resolves Invest today at NASDAQ. A reminder that questions will be taken through the web platform only. If you are here in the room or joining online and would like to ask a question, please submit through the web platform. And I'd like to introduce and welcome to the stage, Hao Gu, our group SVP customer and partners, and two valued Resolve partners, Kimberly McKinley from Microsoft and Sarab Atri from TCS.

All right, welcome back. Good morning.

It's still morning, right?

It's 12.

Okay, so maybe a little bit after morning. But thank you again for the time and coming back and joining us. Quick introduction of myself. As Ermi mentioned, SVP of Customers and Partners, which means I have the privilege of serving and supporting the 1,000-plus customers that Resolve AI currently supports, but also means that I get to work with amazing partners like Microsoft and TCS and building out our partner ecosystem and allowing us to scale through partners. And so this includes our cloud hyperscaler partnerships, our consultancies and GSI partnerships, our ISVs and payment provider partnerships, all that kind of fits under that umbrella. So I'm very excited today to have two of our amazing partners. First, we have Kimberly from Microsoft, Senior Director of Microsoft's Frontier Company. She works with Microsoft's most strategic Fortune 500 customers, advising them on AI-led transformation. And then we have Saurabh, who leads TCS's Retail and Consumer Goods East Region. And then formerly, I believe you led the go-to-market team for TCS as well. So, super happy to have you both here today. So we got some, over the next 15 minutes, we got some hard-hitting questions where we're going to grill them a little bit in terms of how they're working with Resolve. And I think it's really great to have Kimberly from Microsoft and Saurabh from TCS because it's actually two different dimensions of kind of the technology landscape. On one side, you have Microsoft who sees some of the most exciting frontier capabilities and technologies and how that fits into the market today and what are the trends they're seeing. On the other side, you have Saurabh from TCS who is looking at how do we actually get these technologies live in the hands of our customers and actually creating value. And so I think across those two dimensions, those two lenses, you know, you really get a great sense of, number one, how is resolve position in the eyes of our partners, but then how do we actually exist and land in our customers' technology ecosystem as well. So, Kimberly, we're going to start with you. Almost daily, we are seeing new innovations in AI, like literally every day. New models, new protocols, you know, new consumer AIs that are coming out, and the hot topic, the hot topic today, of course, is agentic commerce, and which again have kind of shifted and disrupted how brands or merchants are thinking about their technology and how they respond to that. Some of them are moving quickly. Some of them are a bit of deer in the headlights. How do you see the commerce industry preparing for the agentic world?

Sure. Everybody here? No?

No. Oh, yes.

Now we have. Yes. Okay. Sure. So I, you know, it's, it is a very exciting time. The technology is changing, you know, daily, including what, I get fed to use at work. It's challenging just to keep up with everything. When I think about commerce and particularly the agentic piece of it, commerce is really everywhere. So we talk about retailers and brands, but think about anything where you transact any business from a bank or the drugstore, anything like that. And so when I talk to my customers about it and I see what they're how they're preparing it's really three ways okay so the first thing is you really kind of have to look yourself in the mirror and say is this a journey that my customer is realistically ready to go on and in and how do I know that the second thing that everyone needs to do is get your data ready and then the third is build that semantic layer so you know we're gonna see some folks move faster in this space you know if you're if you're a true luxury brand you know shopping with an agent is is maybe not the first way that your customer wants to interact with you something where you can save time and really cut out a lot of that friction that we heard about in the last session those are really you know the more ready cases but either way everyone needs to get their data ready so what does that mean it means you know thinking about you know we've got all of this data now but what does it mean how can you connect that customer journey with your data it doesn't just mean unifying it it It means really thinking about your brand, machine ready attributes for your products, all your rich brand history, bringing that together. And then the third is the orchestration in that semantic layer. So again, this isn't just unifying the data. It's how can you take everything that you've just readied with all of your brand history, all your product attributes, tie it to pricing, promotion, fulfillment, and then move it along that seamless customer journey that's ready for agent in commerce.

Love that, thank you. Second question, Microsoft is an absolute titan in the tech industry, literally for decades now. In the last three months I think it added what a trillion dollars in market value. Very glad I kept my Microsoft socks. And it's cloud and AI technologies power the majority of Fortune 500 companies. You guys have the engineering, the development, the go-to-market resources to really go into any market, any industry vertical that you really wanted to. So I guess my question is, why partner with Resolve AI? Why is this partnership valuable to you? And how do we complement the conversations you're having with the customers and our joint go-to-market strategy?

Sure, absolutely. So sort of to the the point you already made, it's really, we compliment one another, and that's why together we have this great go-to-market. So, like you said, Microsoft brings the platform, the cloud, and the AI, and so we're an LLM agnostic platform, and we also have Foundry as well, so developers at our mutual customers can build on Foundry, you know, alongside of us. But what Resolve AI is bringing is that commerce specialization. And so when we bring that in, and especially now, you know, I've loved what I've seen so far today, is really telling that end-to-end story of commerce. And I saw my entire, you know, retail life flash before me in the last one when I was thinking about how far we've come since the early 2000s when I started my career as a merchant. But it's really kind of the commerce specialization plus that enterprise level, you know, governed infrastructure, cloud, and AI that we can do together.

I love that. And I think one of the common things that, you know, for me coming from Microsoft and now joining Resolve is that the common theme around trust, right? And that is so critical and so key. I mean, I think the cliche is that no CIO gets fired for buying Microsoft, right, or hiring Microsoft. And I think that common, you know, focus around building the trust layer, the ethics, the government, the transparency, the auditability, especially in the AI world, is so, so important. And I think this is, you know, one of the things why, you know, we're so excited about the partnership is because we're both so grounded on that common theme of trust.

Absolutely.

Saurabh, I'm going to switch over to you. Obviously, getting the technology right is one thing. it's often harder to, you know, actually get into the hands of enterprise. And I would argue it's even harder to actually capture value from that technology, right? I think everybody's kind of seen that statistic, that McKinsey statistic of 70% of digital transformations fail. I think it's even higher now with AI transformation. So for you, someone like you has, you know, obviously seen a lot of these transformation programs and probably been involved yourself. what are some of the pitfalls that you see on a day-to-day basis and how do you overcome them through the way that you deliver these type of projects?

Thanks, O. Technology comes second to the point of sounding contrarian. When we see successful projects, what differentiates them is they are not seen as technology products. They are seen as business projects. I'll give an example on searchability and, you know, the conversion. We were working with a leading furniture and home improvement customer. And we were talking about how can we increase supply chain conversion, how can we increase, how can we decrease the customer bounces and all that stuff. But when we were talking to the CEO, he said, look, what I want is the conversion ratio, which today is at 1.1. I want it to go at 1.7 in the next six months. When we are working with the business KPI as the North Star, I think everything else comes together. This is the single most understated learning that we have seen. So have the business KPI first, what is it that the customer wants, and then start with the technology as step number two. So this is pretty much what we have learned in our experience when we are working with the customers. I also wanted to touch point on the conversion angle. Today, a simple example, when I was searching for a gift for my seven-year-old around two days back. So, she's a big fan of Peppa. Who is it? And, you know, I was looking specifically at, you know, what kind of ceramic utensils I can buy on Peppa and not to disappoint my 17-month-old son on also George Pig. And goodness me, when I'm searching at all the leading retailers, the search results are not what the consumer wants. And I think that is where Resolve fits very uniquely in solving that specific problem for the consumer.

Love that. And I think you said it really well in terms of not starting with technology but really starting with the use case, the problem we're trying to solve, what is the measure of success, and then kind of work backwards from that. And I think we often talk about it, but actually putting into practice is often a lot harder than it seems. Getting in front of the right stakeholders, making sure that there's alignment and agreement across these stakeholders so that we're actually delivering the great business value and we're actually measuring the right things once the technology gets implemented. So 100% agree. Second question for you. Resolve AI's agentic commerce solutions are now installed in, you know, several of TCS's Paceport innovation centers, which means that TCS advisors and consultants are now using these solutions to essentially inspire customers that come to these Paceport offices and show them how these technologies can transform their business and, you know, and create business value. Obviously, there's a lot of AI solutions out there, right? And there's a lot of companies that claim and say they do a lot of things probably similar to us. And so I guess for TCS, we've had a big press release recently, but what made Resolve AI something, you know, TCS was comfortable in showcasing to customers because you guys are trusted advisors to your customers and why you guys chose it as kind of a frontier AI solution to actually put into your pay support innovation centers. And sorry, I know there's a lot of questions to throw in at you, but any immediate current feedback or responses from the customers on these types of solutions?

So I would like to start with the initial part of the question on why did TCS chose Resolve to be showcased at the Paceport hubs. So for the audience, Paceport hubs, think of it like the innovation hubs wherein we co-curate with our customers some of the solutions together because each customer is kind of unique, at least that's what they will tell you, but we also believe that. Now, there are three things with Resolve, specifically that came out number one was like Kim alluded to earlier without data a lot of the AI projects are having a big risk so resolve works not only with the customer data but also it has retail specific algorithms to solve some of you know the commerce energy commerce issues that the consumers are looking to solve so the specificity of retail and also the ability to work with the consumer retail specific data the second thing is traceability there are a lot of questions today which are coming in from the customers around I want to know how did the agent make that decision how can I trace it back I think resolve gives that and the third thing is the plug-and play resolve is not there and this is also a concern from the consumer is this tool going to replace my tech stack so resolve is not you know a rip and replace you know kind of a technology it sits on the ecosystem that the customer may have the tech stack that they have and works on the investments that are already in there so I think these are the three things that you know we found which are interesting for resolve and to your other question on what are we seeing from the customer side there is a lot of work which is happening today I think it all depends on the maturity of the customer where are they with data today where are they with you know their technology stack today what we are seeing is a common thread is a lot of customers are building their own ai coes i think this is this is something that we are seeing and as part of the ai coe and also the agentic work that kim you know mentioned earlier we are seeing a big interest in that whole conversion aspect that whole discoverability aspect you know how do i improve the discoverability and conversion of the consumers coming at my website. And this is where we are seeing interest in Resolve. Instead of searching, you know, give me, you know, Peppa Pig merchandise, the ability to interact, you know, with the agent and, you know, understand what consumer is really looking for and giving those specific recommendations. And not just recommendations, but completing the whole transaction loop with, you know, payment and everything. I think this is what our customers are finding interesting with Resolve, and some of them are also looking to drive, you know, pilots and point-of-values.

I mean, if I can almost summarize some of that, I mean, some of the things I heard is, I think the specificity, right, the focus around retail, around commerce, and how we've had that laser focus around solving problems in this specific vertical in space is obviously very important. I think you both mentioned that. Again, Saurabh, you mentioned around having the traceability, the governance, which ultimately goes down to what we were talking about earlier around trust, right? And how do we make sure that companies now, especially now where there's AI proliferation is so common that my IP, my customers, my data is not getting lost or is being leveraged for someone else's business outcomes or business goals. And, of course, being very clear in terms of what the problems and what the business value want to solve. So I appreciate you guys kind of, you know, highlighting some of those key themes. So thank you. Now, to close, I'm going to ask a question to both of you. And because, you know, we're doing a lot together. You know, with Microsoft, we've, you know, just in the last year that I've been in this role, you know, We've launched our proprietary models on Foundry. We've done joint go-to-marketing events at ShopTalk and NRF. We've worked on customers together. But clearly, I am very excited. But what are you, Kimberly, most excited about the partnership and kind of what's ahead for us?

Sure. That's an easy one. So I think along with everything that we talked about, really the there is a lot of interest you know most retailers and brands know that we've sort of created you know I'm gonna call it's sort of like a shopping nightmare right like on e-comm now it's just you know sort filter you know all of this and the consumer is really ready for goal-based shopping you know I have you know I think he said it earlier you know I have a wedding in Tuscany what should I wear and what I'm really excited about is that we've you know We're seeing the customer interest in the market, and that Resolve has, you know, that brings that commerce specialization and can bring it to our platform so that we can go to market together and really come and, you know, have meaningful conversations and implementations ultimately with these enterprises that really do desperately need to reinvent their online shopping experience.

And similarly for you, Saurabh, you know, we've done a lot together as well. You know, obviously we had the big press release around the partnership. We've done a lot of enablement sessions with your teams globally. Now we've trained up many of your folks. We've kind of deployed some of our solutions at Paceport. Again, very excited. But same question to you. What are you excited about in terms of the partnership and kind of what's to come?

Right time and right partnership and the right strategy. I think this is what comes to my mind at Resolve. Like Kim mentioned, we are at a cusp of a big transformation. agentic commerce the whole Jenny I strategy and narrative I think we did not have a lot of technology to solve some of the problems that we are talking about you know five ten years back but today and at least for the foreseeable future a lot of companies are going to invest big time in their agent take any capabilities and I believe specifically for retail I think resolve holds a great promise in terms of you know bringing that specificity from the retail domain we're seeing a lot of Jenny I products disrupting what we call as the horizontal streams so think about AI in SDLC you know coding and all but when it comes to the retail specificity I think resolve fits the bill really well in solving some of the business problems around merchandising conversion commerce so I think this is going to be very interesting amazing well Kimberly Thanks, Rob.

I just want to say thank you so much for your time today. Really appreciate it. I think it was super valuable for us to kind of hear your thoughts, your perspectives around the partnership and things we're working on together today and hopefully in the weeks and months and years ahead as well. I will now pass it over to Arthur and Kate, who's going to talk a little bit about Resolve's finances.

Okay.

Well, thanks, Hal. Thanks, Kimberly. Thanks, Aura. It's great for you guys to come and look. Let me see.

Okay.

Okay. Well, good afternoon, everybody, and thank you for staying with us. It's been a great morning, hopefully. I think it was great to see the amount of turnout from everybody and the fact that you guys are all staying. But my name is Arthur Yao. I'm the Chief Operating Financial Officer, and with me is Kate Goosen, who's our Deputy CFO. She's also the CFO of our Resolve Reward business. We spent this morning discussing, you know, the market opportunities, the products, our partners, and our technology. This Investor Day is really for our investors, analysts, partners, to really get to know the rest of the Resolve leadership team. You know, some of you may probably know Dan and myself, but this is probably the first time you started to engage with Lawrence, Michelle, and, you know, David, Shovig, you know, James, you know, Kate. I think these are the people that really does the hard work that delivers these results. So we have, you know, we have this amazing team behind us that you guys probably have heard about but have never seen. So I think this is a great chance for you to be able to meet with these individuals, talk to them, engage with them. I miss NAGA as well. So, again, this is the team that really has really created and be able to deliver the results that what K&I are going to do is just represent the results that they have delivered to. So we don't actually do the hard work. We just consolidate all the hard work that's been done. So this afternoon, K&I is going to go show you three things. What have we built today? What it earns? And how do we get this business to profitability? So let me begin with a journey, okay? Because I think that some of you have been with us, and some investors I was just for the first time meeting was telling us they've been with us for a year, two years. So this journey started, you know, when we started 2025, we have very little revenue. And, you know, in the first half, we basically deliver $6.3 million. And in the second half, 40.5. So for the total year in 2025, we had 46.8 million. And then in just the 90 days, that's the first quarter of this year, we delivered 60 million, which is more than we delivered the entirety of last year. And in the first half, we delivered 130.8 million, which is almost a 2,000% year-over-year growth. So, you know, we started in 2025 with limited revenue and a very unique technology with 30-plus patents, and we set out to build this hyper-growth company. And I think a lot of you may have heard, you know, we're going to exit 100 million AR, then became 150 million AR, then 200 million AR, you know. So we had a vision for this business of creating this hyper-growth company. And in the last 18 months, we've delivered on this promise, right? So by these numbers alone, you'll see that. So our customer base have gone from a little over 100 to now over 1,000. We have built a distribution network with Microsoft, Google, TCS, and Tech Mahindra, and now MasterCard that we just announced. And, you know, what we have done is we've basically this revenue at this order on sitting on this base of install base of 10% growth is really an operating platform. And the last two years was really about building this platform, okay? So now, you know, it is the foundation of what we call winning the enterprise. So we have this set of customers that we really need to land. We've landed. Now we need to expand and deepen. So deepening a relationship costs us only a fraction of what it takes to win it. So now the opportunity is in front of us to really capitalize on these 1,000-plus customers to really deepen and expand and take forward our entire tech stack. Now I'm going to turn to Kate to discuss the number in detail.

Thank you, Arthur. I think I'm double-miked. Hi, everyone. I'm Kate Goosen, and I've spent the better half of the last 20 years working with large global businesses and helping them scale multinationally. I wanted to go a little bit behind the headline numbers that you're all probably familiar with and really tell the story of the headline versus underlying numbers because they're the two halves of the same story. So the key numbers that I want you to remember from this page, number one, the H1 2026 GP of $63.9 million versus the GP for the same period in 2025 of $6 million. The other number I want you to remember is the reported operating loss So if you scroll through 181 pages of the SEC filing, you will see the operating loss of 128.1 million. However, the number I really want you to remember is the H1-2026 suggested EBITDA of negative 32.6 million. And by the way, as a reminder, for 2025, that number was negative 17.7 million. What is behind this reported loss, which seems very high? Well, actually, 41.5 million of it is share-based compensation. And you know how you're able to meet and hear from so many talented people here this morning? It's because of the share-based compensation, because that's how companies of our size can attract the type of talent that we attract. The other number that's part of this loss is 20.4 million of depreciation amortization. I want you to know and remember that neither one of these metrics takes a single penny out of the business. Meaning it's not cash, it does not decrease our profitability. I think that's an important point to remember as we think about how did we scale as a business, right? the other thing that my adjusted EBITDA number doesn't include are the costs that are associated with putting this enterprise together that includes the fundraising fees the costs that go with completing M&A processes litigation settlements acquisition integrations we're an acquisitive business office moves and removal of duplicative roles. All of these things are finite and they're one-time. They do not represent the recurring business that we run every day. So as a result I want you to remember the adjusted EBITDA margin of negative 24.9 million. I want to point out that that is already 256 percentage points better than the same adjusted EBITDA margin that we reported in H1 of 2025 please remember this number as because I will come back to it in a little bit as we proceed so while the loss the adjusted EBITDA loss in absolute dollars is bigger than what it was a year ago as a percent of revenue it is tremendously more narrow and that's how a business of this scale is going to grow right this is exactly the trajectory that you expect and you probably want when you're looking at a scaling business of our size where are growing our revenues against a stabilizing and largely fixed cost base there are a few points on the balance sheet that I actually wanted to touch upon number one is that by the time we exited June 2026 we had a hundred point five million of cash including some restricted cash the reason we call out that number is because I cannot use of it all of it right away towards my full operating model I still use it towards some of my operations but there is a restricted limitation to what I can do with this cash the other bit that I wanted to touch upon on the balance sheet is actually the share buyback program and this is an important point we're a Nasdaq listed company and in all the US listed companies if you want to do a share buyback well frankly you just do a share buyback however we are a scaling enterprise global business stabilizing and growing our presence in the US however as far as the regulators are concerned, we're an Englishman in New York. And as a result, I have to abide by the laws of the United Kingdom, where I need to declare and get approval from the regulatory agencies and the court that if I want to do a share buyback program, it has to be approved. You probably saw this morning, it was approved by the court. So now if we choose to do a share buyback in the next period if the market conditions are favorable now we can do so it doesn't mean that we will do it but this gives us the ability to do it if if we so desire as of right now we don't have these plans but you know we wanted as as we scale we wanted to have multiple ways of addressing the market when we need I'm gonna hand it back to Arthur to talk about how we came together hello okay yeah thank you Kate it is worth for us to sort of look at from our business

from the outside you know we actually instead of just the us talking about ourselves we have a lot of the analysts actually who cover us in the room here today so we have six analysts that cover us and all of which gives us buy or a strong buy rating with an average price around $10 a share. So this really shows that there is a market confidence in our whole business. But before we talk about turning to profitability, I want to set up where our business stands today. We've really spent the last two years building the core assets for our growth. So we have built a go-to-market organization where, and I've talked about this in some of the discussions, where we've hired a set of sales market and some of the leaders here today is part of that that those hiring we train with in-market with infield a go-to-market organization we have four or five of the largest hyperscalers in the world as partners to as the distribution partners for us we have the service partners that we're looking to transition a lot of our lower margin business into so therefore where we can focus on our core SaaS revenue. We have more than 1,000 enterprise customers as our install base, where it's really about land, expand, and deepen. And we have created this agentic infrastructure layer to support our entire product stack. And this agentic layer, which has only recently we started to potentially look at opportunities to license. So we really have created this huge asset set Okay, that took the last two years of building so that we therefore we can grow at this with a high growth company as well as being a profitable company because we've had invested heavily to build these assets in the last two years.

Okay, so with this in place, I'll let Kate talk about our path to profitability, which is critical for how we will need to become a profitable business. okay thank you Arthur can you guys hear me without the great thank you all right so as a lot of you probably have seen we've announced a few weeks ago our path to get to profitable operations so what I'm going to address today is how we're planning to get there. As you probably all know, there are two levers that any company has its disposable to get to profitability. Lever number one, growth margin, and that is what do we sell? Lever number two, operating costs, how efficiently we sell it. These are different parts of the income statement but they actually lead us to the same place and that place is profitability. So I'm going to start by talking about lever number one, which is gross margin. Our current gross margin is at 48.9%, and those of you who cover software probably will say, hey, that's low. Well, actually, we're, at the moment, much more than just a pure software business. We've acquired Reward in February of 2029. reward is a loyalty business that carries structurally lower margins at the gross profit level and we're also a professional services organization we have 700 people who are currently preparing customer catalogs that also inherently carries a lower margin and in its structure our costs for software margin, however, is at 90% or above. And this revenue mix is actually moving in the favorable direction for us in the coming months and in the coming years. As we sell more software, as we realize more recurring platform and licensing fees, resolved margin starts to rise. as the services become larger share of the total product suite, again, the blended margin, again, goes up. In addition, and this is important, and you've heard from TCS, who's one of our key partners, our services organization is moving to our partnerships and integrations. Our partners are going to start driving implementations while we will supply the technology. That's a structural margin improvement for the long term. Now I'm going to talk about lever number two, and that is operating cost efficiencies, which we've announced a few weeks ago. What that means is that we're not going to stop investing, but it means that we're going to start focusing on duplicating, on removing some of our duplicating and underused assets and spend. Once that is fully implemented, we expect circa $60 million of annualized benefit to our P&L. How are we going to get to some of these initiatives that we hope drive this? Number one is going to be around cloud and tech capacity. Number two, we're going to get rid of some of the duplication from the acquisitions that we've made. I already talked about office and surplus space. We're going to focus on ROI-based marketing. You know, our customers, retail, is looking for ROI-based marketing. Well, guess what? We're going to look to get the same. And again, we're going to be more selective about the future acquisitions that we make. As we pursue these actions, we also expect that our one-off costs are going to start falling away such as fundraising fees litigation settlements integration fees restructuring costs these are real costs but they're not part of my recurring ongoing spend these are the real costs that are finite and we expect them to start decreasing when we bring the two levers together we get to a rising gross margin and we get to falling operating leverage where do they meet they meet at an improving adjusted EBITDA and break-even profitability so coming back to 24.9% of adjusted EBITDA margin the actions I just described close the gap and over the next 12 months we expect to get to break even adjusted EBITDA so an improvement of 24.9% margin by the time we exit H1 2027. These actions are actually going to set us on a path towards recurring operating cash outflows in the vicinity of circa 20 million in the second half of 2027. I want to reinforce and this is important that this plan this profitability plan does not in any way jeopardize or implicate our investment for growth. We will continue investing in resolve pay, resolve reward, brainpower, underlying infrastructure, resolve insight, and then resolve commerce. So to reiterate everything that I've just said, right, our GP optimization and our decrease in operational cost initiatives help us to compound our fifth priority which is a resolved margin we're scaling and becoming more profitable it's profitable revenue against optimized fixed cost base each incremental deployment and this is important each incremental deployment that we do it's going to cost us less than the prior one and that is how we're going to optimize our operating leverage. I'm going to hand it back to Arthur to bring it all together for us.

Wow. Okay. Thank you. We're nearing the end. Let me bring it all together for today's whole session. In the last 18 months, we went from 6 million in the first half of 2025 to 130.8 million in the first half of 2026. From 100 enterprise customers to well over 1,000. Onto one platform that's distributed by five of the largest technology companies on the planet. You know, I want to reiterate the $60 million annual cost reduction that we have set out because this is a very important action that we're taking, and it is based upon a lot of deep analysis of our organization. And to achieve that, you know, I'll reiterate what Kay said. You know, we have to, you know, achieve the synergies from all the different acquisitions that we have acquired, We optimize our cloud costs because of some of those acquisitions as well. Consolidate offices, which we've already started doing in London and certain other places. Reduce our legal and acquiring fees. And then, as she said, focus on high ROI marketing. And these five areas are actually all within our control, and therefore we've already executed in many of those areas already. and that would then result in a just even a positive exiting first half of 2027 look we have proven that we have the ability to build a hyper growth company now we're gonna prove to you that we can build a profitable growth company the expensive part building this company is behind us and the most valuable part is in the future so with that thank you everybody for coming and And we're going to go to Q&A next. All right, Ermi, do we want all the speakers to come up? Can all the speakers come up? And then Ermi's going to ask us questions randomly, wherever. And then we'll give the mic to whoever needs to answer.

Okay, we'll move now to questions from investors. From George Alabat Luengo, what strategies are being used, and since when, to prevent cash burn? Who's the question for?

You've got to tell who's going to answer that question.

Dan or Arthur.

Okay. So we'll repeat the question again.

What strategies are being used and since when to prevent cash burn?

Well, we've always been very capital efficient in terms of our management. I think our focus, as I said in my statements, is we're really trying to prove that we can grow. We had a very hyper-growth strategy, which a lot of analysts and investors did not believe. You know, we had to reiterate that time and time again, and then now we're delivering to it. And I think, you know, part of this $60 million reduction is to focus on now moving to a path to profitability because we don't expect to need to raise capital to fund our recurring business. So these one-offs will continue to happen because we're going to continue to do acquisition. We're going to continue to do marketing. We're going to continue to grow our business, but now we need to be in a profitable, high-growth business, not just a high-growth only.

Dragas Dinu, what is the expected revenue growth rates over the next few years? Which channels are expected to contribute most to medium and long-term growth?

I didn't want to answer anything.

Well, look, obviously we have not stated what our growth rate is from a public announcement standpoint. we are going to still continue at a high growth rate because we are an AI company. I mean, we are not building a professional service company. We're not building other types of businesses. We are building an AI-first company, and we have everything, all the assets that we have for that growth. So I don't want to give you a percentage, but we will continue to be a high-growth company, and we'll invest in that way, okay?

Stephen Richgard. Will these share repurchases result in a genuine net reduction and outstanding share count, or will the bought-back shares primarily be used to offset future dilution from employee stock options and long-term incentive plans?

Well, so the share buyback is a deliberate, focused effort to reduce the free float of the company, which we believe is largely held in retail hands. And we are looking to do two things to achieve a different profile of our investor base. The first is to make sure that we are represented by institutional holders, long holders, who buy into the long-term vision of the business. What we've been telling you all today and have outlined to you in the various sessions is that we put down all the foundations to build a market-leading business in the area of agentic commerce and, indeed, other agentic verticals that we may enter into in the future because we own the underlying core infrastructure as well as the products that sit on top. And we came to market as a SPAC, which was not a good journey and one that I would not like to repeat again. And as we landed as a public company in August of 2024, we had no interest in anybody buying our stock. And so the journey from that point to today has been very progressive. We've generated significant revenues. We've grown to a substantial business. We see very high volume of trading in our stock. But there's one caveat to that, which is that the stock is traded primarily by day traders, retail investors, who are influenced by sentiment more than the long-haul institutions we believe would be. So we're focused now that we've achieved so much, laid down the foundations, created a sustainable long-term vision for the business, which is endorsed by major partners, Mastercard being the most recent. We believe that we can now credibly sit in front of long-term institutional investors and put our case to them to buy stock in the market. we'd like them to soak up stock that's already in the market alongside our buyback program. So that is our intention. That is our focus plan in the capital markets.

Some questions from Kimber Sterling. The Monroe facility has approximately 104 million outstanding and matures December 31st, 2026. What is the current refinancing plan, and how do you expect it to be resolved without material equity dilution?

So we have – that's a very good question. We have an extraordinary amount of demand to provide capital to this company. A lot of that demand is focused on buying equity from the company, and we are reluctant to do that, given the current, what we believe to be, undervalued share price. We have other options of other structures, financing structures, that are non-dilutive, and we are exploring those and evaluating those. We are not in the least bit concerned that the Monroe debt will be paid off.

So we have a plan to take care of it and that's why we have a structure in place already. We haven't announced it. That's why it's not in the public domain, but we will announce it once we execute it.

Yeah, lots of options.

Egyen Emmanuel Nagyeki, you've positioned Resolve as infrastructure for emerging agentic economy rather than simply another AI commerce application? Given that AI agents will ultimately sit between consumers and merchants, what do you believe will become the strongest long-term moat around Resolve's position in that transaction layer? And, specifically, what measurable milestones should investors watch over the next 12 to 24 months to determine whether Resolve is becoming genuinely difficult for merchants, AI platforms, and payment networks to displace?

Well, there's a number of people on this panel who could answer that. Shovic and Naga both are capable of doing so.

Could you repeat the question, please?

You've positioned Resolve as infrastructure for the emerging agentic economy rather than simply another AI commerce application. Given that AI agents will ultimately sit between consumers and merchants, what do you believe will become the strongest long-term moat around Resolve's position in that transaction layer? And specifically, what measurable milestones should investors watch out for the next 12 to 24 months to determine whether Resolve is becoming genuinely difficult for merchants, AI platforms, and payment networks to displace?

Absolutely. So all the excitement around consumer AI is real. I am a power user of Agenda Tools and Muse and Dots. I'm looking forward to it and it's going to accelerate more faster than we have ever seen. And what that means for the merchant is that previously merchants used to run retail stores that has changed to an online store now it's become an AI agent in commerce way. But it still hasn't, it doesn't mean that it kills the need for the merchants to do merchanting. So what I mean by that is we said on the merchant side, helping merchants adopt to every new channel and helping them sell more to AI agents for the new buyer, for the AI agents, and as well as we have been doing for the e-commerce work. So that's how I see how our role evolves in the agentic space.

Yeah, I'm going to add to what Nagy said. So there are three ways we look at it. One, to be ahead of the curve is where we are standing. What we thought years back is where we have built today. So we will be ahead of the curve. What we are thinking, we are not disclosing that, is going to always be ahead of the curve, specifically in retail. The portfolio, what you saw, is the discoverability in terms of the funnel checkout, the lower funnel, and then with entire reward and loyalty, and then again, the data inside. So this entire flywheel is the key differentiator, not a pocket or a product. And the third part where our moat will lie is primarily understanding this industry as less is more playbook, and then we expand and grow accordingly. So we want to be champions of this industry with our tech stack, and then we expand. So that's what the moat will cut down to.

Question from Thomas Ford. How are Resolve agentic commerce efforts similar to and different from meta platforms offering consumers with news?

It's completely different. So the Meta Platforms, Muse, which is a great agent, is a consumer service designed to carry out tasks as an AI assistant. Resolve sits on the other side. We sit on the merchant side. In fact, it was being demonstrated out here today in terms of Resolve Pay. but the agents that sit on the merchant side interact with these agents when they arrive help those agents navigate more effectively on behalf of their end consumer the merchant's catalogue, the merchant's inventory and so on without our agent on the merchant side these agents simply arrive and try to replicate navigating around the screen with a mouse and adding to cart with our agent on the other side there is a proper conversation being had between our technology agent and the agent that's arriving, whether it's Muse or Dots or any of the AI systems.

Can you provide your current thoughts on your strategic M&A strategy, including your decision tree on building versus buying? On the decision tree on? Building versus buying.

Well, so, okay.

Again, we always, acquisition is always part of our strategy, but it's not our only strategy. Again, we've said multiple times we have three paths to market, acquisitions, partnerships, and organic growth. We have the organic growth sales team built and operating. We have five global partners helping us sell, and we're going to continue to acquire companies that make sense. We are continuing to roll up search companies, but we also have announced that we are looking at commerce.com so there are many targets in our pipeline and will be continually part of our growth strategy.

Brian Kissinger resolve pay is eliminating transaction fees with that in mind why does someone like MasterCard want to work with resolve what is the benefit to them so we work with MasterCard across a couple of the business units one is in the area of reward where we work with them to provide insight to their customers and to service our offers from retail brands that we that are our customers and in the case of the one we announced yesterday we are helping to provide innovation to the banks that they serve through our agentic capabilities it's a huge endorsement of our capability set and Mastercard's endorsement of it and their resale of our solutions into into customer into banks and other and other of their customers validates the fact that we believe we're one of the only game or if not the only game in town that has looked at the journey from start, i.e. from discovery, all the way through to payment, all the way through to repeat, reward, loyalty and data and then back through that funnel again which we've repeated a number of times today. I don't believe there's anybody else out there doing this. I think everyone is talking the talk and no one's walking the walk. I think we're the only game in town and that may be because we started this journey 10 years ago so we're 10 years ahead of the game or if not 10 years nine years or if not nine eight but certainly many years and we and we have that significant competitive advantage that we are looking to make sure we capitalize on one of the things that you can't afford to do as a pioneer is allow everybody else to come and shoot you in the back we are going to make sure that through our momentum and our growth and the three channels that arthur just talked about, organic, distribution partners, and acquisition, that we maintain our market leadership position and build on it.

Last question from Brian Kusinger. There is wide concern regarding rogue agents. How does your technology help address this concern and protect merchants?

As I explained, the ability for a platform like us to ring fence when you deploy has the underlying tech stack which comes with its observability, its ability to trace, and its ability to audit. So what it actually does is the technology or the agentic layer which Resolve deploys is constantly monitored, it's constantly observed, and it's constantly being defended in the realms of brand.

So in that parlance, the rogue agents will require ethical and governance AI deployed by resolve to the answer to rogue you need ethics and compliance and security and observability which are the foundations which we have been put in place and in addition to our suite of accountability tools which can be deployed by the way by any llm partner they can use our traceware they can use our accountability ai auditory ai rather and our other tools the actual language model that we've built has the inherent defensibility of being anti hallucinatory and we have built that with numerous unique IP that took us many many years to perfect and that fundamentally brainpower our language model which we believe outperforms every other model on the market in terms of reliability is this tenant is the foundational tenant that allows us both to offer the products and services in retail and consumer without human oversight, but also allows us ultimately, over time, to offer that capability set into other strategic verticals, construction, engineering, aerospace, and other verticals that we're not in today that we may move into in the future.

Now we move on to closing remarks from the CEO.

So I'm back on again to draw it all together. so i want to thank you all for joining us today here at nasdaq and online and for the questions that you put to us consumers are changing the way they shop and they're doing it at speed they hand the search the comparison and increasingly the purchase itself to an ai assistant they ask a question they receive a short list and they trust it by 2030 2030, agents acting on a shopper's behalf could orchestrate $3 to $5 trillion of global commerce. This is a fundamental paradigm shift, and for every merchant, it's existential. A brand missing from that shortlist misses the sale altogether, however good the product is. It doesn't matter. If you're not in there, you've got to be in it to win it. our thesis is clear agentic commerce is a new way of shopping and every merchant needs a new infrastructure to compete in it Resolve AI provides that infrastructure a merchant that gets this right will be found by the agent then turn that visit into a sale complete the payment bring the customer back and learn from every transaction today you've seen that whole journey on one single platform, Resolve's platform. Resolve AI is the only company that owns the full stack end-to-end. You've seen today that we've assembled an incredibly strong team to capitalize on this opportunity. Our leaders have built and run businesses at Visa, Microsoft, Google, Facebook, Oracle and Accenture, and many others. And they have chosen to build the next one right here at Resolve AI. As Arthur said, the expensive part of building this company is behind us, and the most valuable part is ahead of us. We're targeting at least $500 million of annual recurring revenue as we exit this year, and the drivers to get there are already in place. As I touched on this morning, I've started and run several successful businesses through several of the great turning points in commerce. Each time, the change looked nascent to most people and obvious to everyone a few years later. Argentic commerce is at that moment right now. Shoppers are already moving, and the merchants who move with them will now capture that value. We've built Resolve AI to help them do exactly that. I hope you leave today as excited about the next chapter as every one of us is. Thank you very much for your support and your time today.