Hi there, and welcome, streaming viewers. I understand we've got some people remotely. I'm Rob Buchner. I'm the COO of Inuvo . Inuvo Inc. is a disruptive ad tech, but not new to the party. We're a 10-year company competing in a very sophisticated landscape right now. I don't know how many of you are familiar with ad tech. I know we've got energy tech, health care, a lot of things going on. I'll try to break this down over the course of the next 25 minutes for you. A few words on my background. I've spent decades working with some of the world's most admired brands the world over, running agencies, networked agencies, worked for two holding companies. I joined the board of Inuvo in February, and I'm now the Chief Operating Officer.
I bring a 360-degree view of the industry and understand, importantly, marketing decision makers, conflicts right now in where they invest their money. I think that's kind of a central theme of today. All right, so here's who we are. We are a predictive AI, a large language model to discover new audiences, new prospects, and actually activate those media buys. All right, here's the disclaimer: do not operate heavy equipment after watching this presentation. A little bit about our story. We are an ad tech built on a proprietary large language model. We've got a leadership advantage in the privacy-compliant landscape, which is increasingly important. You are going to see as I break that down. We have two sources of revenue: a platform business in service of some of the world's largest digital supply chains.
We actually help the digital search business supply those inventories and generate traffic for their clients. We also service agencies, both networked agencies and independent agencies. Then we actually go direct to marketers as well. The technology is built on 19 patents and 6 pending. We've locked up this large language model. While the world of ad tech, at least the legacy systems, are built on antiquated data technologies and they're increasingly wrapping themselves in OpenAI, we're something different than that. Ours is proprietary. I already mentioned the agencies that we serve. I want to mention partnerships. We can integrate this technology at different points in the ad supply chain. It's a very compatible technology, and we'll be mining those partnerships ahead in the future. Okay, here's the landscape in which we compete. 64% of every U.S.
ad dollar is funneled through programmatic media buying platforms across an array of channels: digital, video, connected TV. That second one is a very growth-oriented segment. Social video, retail media networks. Those are large retail big-box stores like Best Buy or Target who are monetizing their ecosystems across platforms. The category's a $220 billion category, and it's growing. Here's the dirty secret: the ad supply chain is crumbling. That's because the legacy systems are built on consumer IDs called cookies. Most Americans don't want their identity to be tracked. If you have an iPhone, your identity and the sites in which you go cannot be tracked. That seriously compromises most legacy ad-buying systems. Increasingly, Americans are just turning to their handheld devices and talking to it for a search. I'm interested in, you know, something for my pool. All of a sudden, the AI comes back to you.
You don't have to go to those websites. We're actually insulated from that because our large language model goes outside and because we're still all going to websites. We're just able to get out in front of that behavior. It's further strained because of these closed ecosystems, which the mega technology brands have built. They hold most of the consumer data. Right? This supply chain is under duress right now. Most marketers, while they may be aware of it, are failing to act upon it. This is where the opportunity exists. We're an anecdote to that. We should have a video. Oh, here we go. One more slide. There are a couple of applications for our technologies. It's really versatile. Up in the upper right, this predictive mixed media modeling.
This is where we look at historical spend patterns from a marketer's budget across all their channels and put that mix against the business performance because, at the end of the day, that's what marketers wanna know. Did it increase sales? Did we grow our share? Which channels are outperforming? Which ones are underperforming? Our algorithms can help marketers make those decisions, and that becomes kind of an on-ramp for our large language model also. Audience discovery. Our technology knows what people are doing in real time, what media they're consuming, and our large language model builds those models with a high degree of accuracy. Those buys can actually be transported into the exchanges, which marketers are already using. Importantly, the idea of aligning your message with the audience, media is really important. We're able to see patterns, perhaps, that would inform the creative brief.
Almost like re-engineering your creative messaging based on the consumption of the media. Our buys can go right into the existing infrastructure. This is a portal. We call this IntentKey. That's our signature product. What this does is it's very user-friendly. You're able to put a prompt in just like other large language models. I'm interested in pet insurance. My dog is a German Shepherd. What it will do is it'll go out and it'll read everything on the Internet in that moment and come back with what we call a concept graph, which is a clustering of those data points. It will give us an indication of audience size for that moment. We'll predict it forward. It will give an indication of brand sentiment, demographics, and we can bring that model right down to a zip code level.
All right, I've got a video that's going to break this down for you.
25% of all digital ad spend fails to hit its target. Data signals are fading. Audiences are harder to reach than ever. Legacy buying systems are still reliant on stalking people around the Internet. Our tech doesn't need personal data. IntentKey AI is a privacy-by-design AI that creates audience models for programmatic media channels. IntentKey AI analyzes billions of real-time signals from the open web to uncover intent pathways and build precise, scalable audiences. How do we do it? We started with AI at our core, not bolted on top of old data, but designed to see the web in a new way. IntentKey AI reads billions of pages of content in real time, organizing them into a concept graph, a dynamic map of how ideas and motivations connect. From that, we create predictive audience models that refresh every five minutes and discover purchase intent before it's obvious.
Instead of chasing yesterday's clicks, imagine reaching tomorrow's prospects first. Here's how we deliver targeting leverage. Our models identify future customers up to a day before any other ad tech can bid on these inventories, while enabling brands to reach audiences across connected TV, display, online video, audio, and more. Because our models flow directly into the platforms marketers already use, there are no extra steps, no extra fees, just custom-designed audiences right where advertisers already buy. The future of advertising isn't reactive. It's predictive. It's intent-driven. It's Inuvo Inc.
Let me explain to you how it works in practice. We're not working with UnitedHealthcare, but we are working with another major health care provider. I just didn't have permission, so I wanted to just run a model. By the way, any of you guys can go to the website right now and run your own models. It works for everything, like any other large language model. Health care is really interesting because right now we're in the open enrollment season. This is when share gain and share loss occurs. The lion's share of the investment happens over this period, and millions of consumers are approaching the open marketplace for a host of reasons. Whether or not you've become self-employed and you need COBRA, or you're aging into Medicare, or you just want to understand the different legal components within your state.
We actually go out when you run a model like this, and it will draw data from all over the country and bring it down to the region in which you place. It gets insight nationally and can drop it right into the zip code level. What we do then is these signals are built into campaign flights. These campaign flights determine where the ads will be placed, whether it's on digital display, connected TV, or on website pages. It's got great elasticity across categories. We work with major technology brands, the biggest in the land, one of the top three auto brands in America. We're in the health care space. We're in the retail space. We work mid-market brands, emerging brands. Here's just another dynamic that I tell you about. Direct-to-consumer branding has been a thing forever. We all buy those brands from social feeds and what have you.
The problem is, as those brands mature, they can't get the reach that they need to draw new prospects into their franchise in those channels. They're paying premium price to get that same audience, and there's audience fatigue. What our technology can do for those direct-to-consumer brands is actually open up their prospecting to a much wider audience on the open web. I want to make sure people understand our competitive advantage. We find high-intent audiences based on what people are engaging in, and our technology scores level of engagement from becoming aware to going deep. Then how that linkage occurs, if you go back to that video, from top of the funnel all the way to the purchase process or purchase decision. Our technology fundamentally is built on not targeting consumers based on demographics. That has been the norm forever.
I wanna reach working moms with kids, right, with $150,000 household income. Guess what? There's a million providers that will give you those data sets. Ours wanted to know why that working mom with kids is interested in a particular subject as it relates to one of our clients. This was a privacy first. Rich Howe here is the CEO and founder of Inuvo . In anticipation of this privacy era, built the large language model. We have a lead on the industry. As people are coveting their privacy, we're able to build these not on the individual, not by stalking an individual's data around the Internet, but by looking at the collective interest in subject matter and congregating where those people are. Right?
Again, this targeting leverage piece I think is kind of critical to our future because I don't think people realize if you can get a 24-hour lead on building an audience and executing that buy, you're not bidding through those exchanges with everybody else. You are, you're buying that audience at a discount relative to others. That's leverage. That saves millions of dollars for a major marketer who's on the system. Because it was built and architected for the infrastructure that's out there, we can pass those buys through in a frictionless model just by pushing the deal IDs through. We sell our services and this technology a number of ways: through agencies, direct to marketers. Both those parties have the option to literally execute their buys on their own. They don't need us on the service end to do it.
That's a huge opportunity going forward because it's very high-margin business. A lot of clients, it's just a sampling of some brands. Yes, Apple's a client, Disney. A travel and tourism. Think about spontaneous trips that might occur. Storms coming into Chicago. I want to go to Vegas. All right. I'm going to go to the airlines first. I'm going to check the weather report. I'm going to check availability at a hotel. I'm going to, you know, whatever it is. There are a lot of different ways in real time that we can, with a high degree of confidence, predict what those audiences are going to do in real time. Importantly, our performance. The efficacy of this technology has been proven for eight years running, and outperforms all the other ad techs that are out here.
This is actually a conservative figure at 60% over competitive platforms, and our clients come back for more. We've got a really high retention rate. Actually, I'm relatively new to this side of the field. That kind of retention rate is unseen in any other aspects of marketing as a service provider. We trade on the NYSE under the ticker symbol INUV, and these two fellows here, Rich Howe and Wally Ruiz, our CFO, have built a really handsome business. We have traction. We have a good trajectory. We have a five-year quarterly CAGR of 24% through Q2 of this year. We'll be reporting earnings shortly. We've got cash on the books, and we've got a $10 million, we've got access to capital through our facilities. We're going the right direction. We're about ready to break through that $100 million barrier.
You know, I've been here for a couple of days now, and I keep hearing the malaise of small cap, micro caps, and the, you know, but we're a proven technology that has traction. Once you get past this mark here and some of the strategies I'm going to talk about, this business will scale to $125 million, $100 million, $150 million onward. The people that built this system have had success building billion-dollar technology companies. All right, just a few words on how we're going to do it and a couple of key milestones. We've added 36 self-serve clients. Those are people who are accustomed with the platform, the IntentKey AI platform, and are on the keyboard executing their own buys without any service from us. We have 42 new clients across our IntentKey AI portfolio already this year.
We're operating in a climate that is confused, but we're on the right side of privacy, and that makes a huge difference. The consultative sales, let me say a few words about this because I've been asked a few times over. How are you going to get more sales? We've got to get closer to the budget decision makers. There's a lot of intermediaries down at the tactical level. If we can use our mixed media modeling technology to help determine optimal spend and optimal performance, that is the most valuable thing you can bring to a Chief Marketing Officer of an organization. Other shifts, we're going to, again, go a little bit further upstream. We want to work more directly with brands. The advertising universe, you guys are 13,000, 13,000-15,000 agencies in America, and they're being washed out. It's really a tough environment for agencies.
Going brand direct with this technology is really important to our future. That's the show. We've got about four or five minutes. If you guys have any questions, go ahead.
I have two questions. First, can you talk a little bit more about the capital market? Talk a little bit about your sales team. Who would the white whales be, right? You talk about moving the needle on the revenue model. Who would be the big, what would be a great win for you?
I've got one in mind. All right. You just take sports gambling, right, FanDuel or any of the MGM platforms. This is not just a national phenomenon. It's a generational thing that's occurring. Brands like that are spending over $1 billion. FanDuel spends $1 billion in America, $1 billion a year. People are making those little micro bets on their phones in the moment. What they're doing is they're going to get intelligence from all the fantasy sites. That would be the obvious place you'd place ads. What about all the other things? What's going on in the city? What's going on with the weather? If we can get advertising, that's, we're not in that business right now. That'd be a whale with real, real direct implications for us.
Would your sales guys go straight to FanDuel or would they go to their advertising agency?
Both. We'll hit them both.
Got it.
We're not here to decouple agencies from the brands which they serve. We've got multiple points of entry, and I think it's my job to balance that.
Is your sales team concentrated on both?
Yes, they are. They are. Some are dedicated to self-serve because that is a big part of our future. It's really high margin, almost 100% margin.
The other question I had was just I was looking at the quarterly sales chart. What happened between Q1 and Q2 this year? It looks like you sequentially declined. That's not the usual case.
Rich, Wally, do you have a?