Good morning, and welcome everyone to a very special event. This launches the year the ChatGPT and Google Bard have clearly signaled that the age of artificial intelligence has begun. What you're about to observe at this webinar is an AI that can generate marketable audiences at will without having to look up information in a database. We call this AI the IntentKey, and it determines and actions the key concepts behind the intent of your consumers. My name is Rich Howe, and I am the leader of Inuvo, the developer of the artificial intelligence that powers the proprietary experience we are about to share with you. For our shareholders, we filed our quarterly financials and accompanying press release yesterday evening. You can access both of those documents at our website. Inuvo was early to the application of generative AI within advertising, having invested nearly $50 million to date. Over the last 6 years, we've also witnessed the performance success that can come from the adoption of our technology, and I would encourage you to review a sampling of those case studies at our website. The Audience Discovery Portal we launched this morning is a place where information about any audience can be instantly generated. Like ChatGPT and Google Bard, the IntentKey AI that powers the Portal is distinguished from all other types of AI by its proprietary model of the language. The reason this kind of AI is so powerful is because humans understand, experience, and interact with the world through language. At Inuvo, we have taken that 1 step further and made the AI's knowledge immediately actionable for advertising. This has never been done before. The IntentKey is itself representative of the collective knowledge of humankind, having been trained on 10's of billions of individual pieces of information. It has, for example, already read and associated virtually everything that has been publicly written about your product, service, or brand and has formed a conceptual understanding of those things relative to marketing. The AI continues to refresh its language model, reading millions of new pages every single day. We built this experience to showcase a sample of this AI's capabilities. We invented the technology for 2 reasons. First, we wanted to solve the privacy issues related to using a consumer's information for advertising. Second, we wanted to unshackle marketing from the limitations associated with using identity-based technologies limited by their dependence on structured datasets. We believe we've accomplished these goals in so doing, have forever changed the advertising paradigm from being about who someone is to why audiences are actually interested. The days of using a consumer's data for digital ad targeting are coming to an end. This fact is self-evident in the ongoing decline and lack of scale associated with using third-party or first-party targetable consumer cookie identifiers. The AI we have developed does not depend on persistent and intrusive user tracking. Rather, this AI has been trained on a more extensive set of public data that allows it to generate knowledge that did not previously exist. This could not be a more perfect evolution of the information age that began in the mid-20th century. Inuvo foresaw this many years ago when we first launched the IntentKey. Aversion to change is a very human quality. However, as the saying goes, "Fortune favors the bold." Those of you who adopt this advertising technology ahead of your competitors will be the ones that lead this age of AI. If you could peer inside our language model, what you would see is a giant web of 10's of millions of interconnected concepts. These concepts are abstract ideas, emotions, people, places, things, thoughts, and beliefs. They play a critical role in all aspects of cognition. The audience for any product, service, or brand does not need to be identified by the identities and demographics of the people within that audience. This itself, I know, is an abstract notion, given marketing has been based on this paradigm for generations. Think about it. What is important about a product, service, or brand are the reasons why consumers have an interest in these things. For the first time ever, an artificial intelligence designed by Inuvo can instantly identify and action these reasons without knowing or wanting to know who those consumers are. This kind of transformational language-based artificial intelligence can and should power not just media, but creative, content, market research, product design. Before we begin, I'd like to point out that for this demonstration of the portal, we have only provided a subset of the data our AI can in fact generate. Our clients get a custom version of this portal designed and optimized specifically for their business needs. What I'd like to do now is turn the webinar over to our Head of Marketing, Katie Cooper, who will walk us through all the information this artificial intelligence is generating at the portal. Katie? Thank you, Rich. Hello, everyone. Again, my name is Katie. Today is a very exciting day. It's my pleasure to take you on a tour of the Audience Discovery Portal. Before we begin, I want to bring to attention again that everything you're about to see here is generated by artificial intelligence based on a language model that does not require intrusive or persistent consumer tracking, identity, or data. Yes, you will be hearing this friendly reminder again later on in this tutorial, as this is a key differentiator for our technology and the Audience Discovery capabilities our technology offers. Let's dive in. First things first, there are 3 key sections in the portal. The 1st is a free form search capability. The 2nd is a section about top audience categories that we see on the open web. The last section, which is also represented in the ticker at the top of the page, highlights concepts that are trending up or down. As Rich said, the audience concepts are the building blocks of our AI. The abstract ideas, underlying principles, thoughts, and beliefs within our language model that play a vital role in cognition. 1 thing to keep in mind is the data that you see here is actually changing all the time because the artificial intelligence behind this portal is continuously monitoring the audiences for any product, service, or brand on the Internet at all times, and identifying the things that are the most engaging at any given moment. If you come back here in another day or so, you might notice that the categories or concepts have changed. While entertainment is number 1 right now, it may not be next week. Our AI recognizes those changes in attention, and those changes are reflected here. Also, almost everything in the portal is clickable, so you can explore as you like. For example, if we scroll down and look at trending concepts. Let's see, we can click on Katy Perry, and the AI is going to generate detailed information on the audience it associates with Katy Perry. In the context of this portal, you can think about Katy Perry, the singer, as a product, and think about the information that's been generated here as the potential audience that's interested in the Katy Perry product. We'll come back and revisit this view here later. We can also interact with the ticker at the top of the page here in the same fashion. This section displays, again, the trending concepts from around the web. You can hover and pause the scroll, and then click into an audience detail for that concept. We've touched on functionality and how concepts are the building blocks to the AI. Let's go to the top search bar here and dig into an actual example. I'm going to type in the American workwear retailer, Carhartt. This brand is generally known for blue-collar workwear, coveralls, hardware and clothing, et cetera. Let's take a look at what our AI knows about Carhartt. As you'll see within seconds, the AI generates its assessment of what the potential audience looks like for Carhartt. Again, generated without consumer data. I warned you earlier, this was worth repeating. At the top, we see some general information on audience size and the growth trend for this audience. I'd like to focus on this circle area here, because this is really where the differentiation of our AI is relative to existing methods of audience creation. It's worth pausing a moment. Excuse me. Worth pausing a moment to see how marketing has been conventionally done for at least the last 2 or 3 decades. With this guy. In the modern way of doing advertising, all the technology and systems typically key off of an identity, the identity of this person or people that look like him, while continuously trying to add information on top of this person's identity. The things in the blue circles here, income, age, demographics, interest, et cetera, this is the way it has worked. You just keep adding more and more information, and then you try to find a bunch of other people who look like this person because you know the same things about those people. That group of lookalikes collectively becomes the audience and who you end up marketing to. Note the size of the circles. The equal size is representative of the equal weight this information plays in the makeup of this audience, despite the actual influence that they play. What we are trying to do here at Inuvo is change that identity-based paradigm. Specifically, we wanted to create a privacy safe technology that was independent of individual identity. We went through language and we said, language could be the proxy for an identity, meaning there are certain concepts that are probably associated with Carhartt, for example. If that's the case, why don't we focus on trying to figure out what those concepts are and then work on improving the AI's understanding of those concepts? Extending, if you will, the knowledge of each concept so that we could effectively get to the same place in terms of its ability to find an audience, but without identity, and more importantly, successfully improving upon that data. With that as background, let's explore Carhartt some more. This section displays a cluster of concepts that the AI has already associated with Carhartt, and the varying circle sizes represent the strength of that concept as opposed to what we saw earlier with the equal sized blue circles. There are actually thousands of concepts that our AI can associate, but for the purposes of the portal, we are only disclosing a set of higher level concepts. Our IntentKey clients, however, receive dynamic just in time concepts. This is achieved by the AI reevaluating the associations based on what's happening in the world related to Carhartt all the time. Think about it this way. The AI has read every page of content ever written about Carhartt. Hey, Carhartt, give us a call. A few interesting things about the Carhartt concepts we noticed right away is Jessica Chastain and Matthew McConaughey. You may recognize these names as Hollywood actors, but somehow they're associated with Carhartt. These interconnections are the AI's way of saying, "Hey, there's a connection here between Europe, Dearborn, Michigan, Jessica Chastain, Matthew McConaughey." Moreover, if we click into Matthew McConaughey and the dedicated concepts for his audience, the Carhartt model is actually inheriting these levels of granular sub-concepts as part of its audience makeup as well. These concepts go beyond what the brand itself may even know and generates connections that were previously unknown and with great influence and great relevancy. How do our concepts in the portal manifest themselves? For Jessica Chastain and Matthew McConaughey, it turns out were wearing Carhartt jackets in the movie Interstellar. The AI figured that out, which, let's face it, that's really cool. What's the importance of that as it relates to the advertising side of the equation? I would like to highlight 3 actionable opportunities that result from our ability to define this audience based on a collection of concepts rather than a collection of identities. Number 1, content. Consider the likely hundreds of articles written about the movie over the years. The AI can instantly associate Interstellar and Carhartt and decide to buy a media spot because the audience that's looking at those pages about Interstellar is an audience that should also be interested in Carhartt. The placement of that ad has nothing to do with the consumer that's in front of the screen and has nothing to do with their identity. Therein lies the privacy component of this technology and the power of it to understand all of these concepts rather than use data and demographics. Number 2, creative alignment. The concepts play a very important role in the ad creative development by illuminating themes and messagings from the learnings to incorporate into the creatives themselves. If we explore another concept here, like A.P.C.. A.P.C. is a French fashion brand who, as it turns out, has done multiple collaborations with Carhartt. The strength of the A.P.C. concept could strongly influence the traditional Carhartt aesthetic, which again, is more construction workwear to something more high fashion and trendy. This could be reflected in the ad creative to garner interest from the A.P.C. concept audience. Again, these concepts would be inherited into the Carhartt concept. Lastly, partnerships. The learning can highlight an opportunity for a brand to work with a strong concept, in this case, a celebrity like Matthew McConaughey. Katie, I wonder if I could just add a couple of words here, because clearly this is, you know, where the greatest differentiation between the way a language model-based AI like, the IntentKey is from the traditional methods, which have always been based around identity and people. As I said in the opening statements, you know, when you think about marketing, it's not really about the people. We've made it about the people. Those of us that have been a part of designing, you know, the data, that gets used for marketing. We designed all of that around people simply because that was the way the technology allowed it to be designed at the time. It's really never been about that. It's really been about what people are thinking about a brand, like Carhartt in this example. That's what really matters, is like, what is the actual thinking of my audience about my brand or my products or my services? The Interstellar example that Katie gave is a perfect example of that. I mean, what is it saying? It's saying that a bunch of people watched Interstellar and thought Carhartt's clothing, particularly the jackets, if you go look at the movie, were cool. That's a good thing for Carhartt. These people think that their stuff looks really cool. That's the kind of audience you wanna put your products in front of simply because they're predisposed to have an attraction to the brand already. It's really a way more powerful way of looking at the audience-building problem, because it opens you up to the ability to extend audiences in ways that have never been possible before, and to a large degree, have just simply been limited by very structured and limited data sets. There really isn't a lot of information that you can add on to a person's identity. Measures in the thousands, maybe. This particular type of technology opens you up to millions. As Katie pointed out, when you are a client of ours, you get all of the associations. And Carhartt, for example, I know there's an association with them, with fire retardant materials. If you think about it is a workwear. It's for people, you know, who are out in the fields, they would want materials that are fire resistant, fire retardant. As it turns out, that is associated with Carhartt. Again, another perfect example of how our AI would be able to find that audience. You could do thousands of pages talking about fire retardant and fire-resistant materials. None of them, by the way, have anything to do with Carhartt. There's no mention of Carhartt at all in any of those discussions. However, that's exactly where Carhartt might wanna put the products they have that are resistant to fire. It's really a way to extend your thinking about audiences and have the technology capable of reaching micro audiences you never dreamed you could. Katie, I'll turn it back over to you. Thank you, Rich. With all of that as background, let's explore the audience for Carhartt. Our technology goes way beyond the general makeup of a prospect audience by using these concepts, but it does have the ability to generate demographic information. Information that may appear familiar, but I want to stress this difference. Concepts, not demographics, drive audience selection. The demographics shown here are inferred from a collection of these concepts. Let's look at this. What the AI is saying here, which I find kind of interesting, is the split between male and female is basically 50/50. Note the star here. What the star is telling you is an engagement rank. For females, this is a score of 76, with 100 being the highest relative engagement. This means that the audience of females is a strong candidate for Carhartt retail products, as they are very engaged online with this brand and their products. This isn't to say that males aren't engaged, since there is no star, it means that the engagement rank is below 50, and therefore less engaged than female. The same engagement scale applies to all the demographic categories in this view, these engagement ranks create opportunity to evaluate your advertising plans. Age, for example. You could look at the younger age group and see here that they are very engaged online with Carhartt. You could ask, "Does my marketing plan take that into consideration?" Perhaps the less engaged age groups here are an opportunity to action an underserved audience segment, especially since, in this case for Carhartt, a strongly associated concept like A.P.C. ranked very high with the older age segments. The wealth of knowledge ready to be explored through these layers and layers of concept data is truly remarkable. Lastly, backing out to the main page, we also have a section for industry audience trends and as well as an FAQ. Pardon me. If you have a question not shown here, use the multiple contact buttons to reach out and learn more. We've also included some helpful resources in the portal menu, a recorded tutorial similar to today's webinar, case studies highlighting our ability to discover and action audiences others can't, and again, our contact. Please don't hesitate to reach out to us for your customized insights about your own product or brand. With that, I thank you for taking the time to learn more about the Audience Discovery Portal. This concludes our tutorial, and I'll be turning things over to Natalya Rudman for Q&A. Happy discovering. Thank you so much, Katie. As a reminder, if you have a question about Inuvo's Audience Discovery Portal or about Inuvo's AI, please submit your question to the Q&A box. Let's get started. Our 1st question is: How is it possible that you could have AI as powerful as ChatGPT or Bard? T hat's a great question. I guess the answer to the question, Natalya, and whoever asked it was, we've been doing AI for many years already at Inuvo. I think, as I may have indicated in my preamble, our founders and our board members and many of our executives are from notable companies who built most of the methods that are currently used to do marketing and advertising, and the data businesses that support that. We had maybe a jump on others in terms of our thinking about how to solve the privacy problems and how to leverage, you know, the latest and greatest technologies associated with doing that. It was clear to us, even many, many years ago when we first started developing this technology, that a language model-based generative artificial intelligence technology would be the way to do that. We didn't just wake up and think that that was the case, you know. It was our experience that led us to that. I think history is proving us correct in this regard because we do see, you know, these announcements coming out now, you know, from ChatGPT and Google Bard. However, as I've mentioned before, we are the only company that I'm aware of that has applied this to the marketing use case. Thank you for that, Rich. Our 2nd question: How long does it take to get an ad campaign going? That's another great question, and another very huge advantage of technology like this. In traditional advertising, we all know the construct. You know, we take a look at all of our clients, we go buy a bunch of data about them, consumer data, we overlay it, we segment it, we do some analytics on it. We try to figure out, you know, where we think we need to go target, we go purchase, you know, third-party datasets that are aligned with those identities. There's a lot of work, a lot of money that goes into doing that. None of that's required with this technology. This technology effectively eliminates the need to do any of that. It automatically, you know, figures out what the audience is. You saw that today. You can see it at the portal. It automatically figures out where the media should be placed, you know, based on its understanding of the product, service, or brand. The answer to the question is, in most of our clients, implementations is a few days. It really just takes the AI to be focused, you know, on some objectives which we work with our clients on. Within days, the AI is knowledgeable about where the best audiences are located and we can begin, you know, running campaigns for clients. We have another question that came from our audience. As a potential customer, what services do you offer to complement this AI? We offer a full set of services, so we can run the campaigns and use our AI, you know, to be driving that campaign strategy. For our agency clients, we can plug our artificial intelligence into whatever campaign systems that they are actually using so that we can empower them to be successful with their clients. Another question from the audience. What is the difference between what you are doing to gather information about consumer behavior different from others in this space? The first difference is we don't use identity. You know, as I mentioned earlier, everything about marketing for at least 2 generations has centered around the person. You know, if you could look inside the databases that are used, you know, you'd have a picture, Not a picture, but you'd have a number that's associated with Rich Howe, and then there'd be this long list of, you know, attributes that are, you know, that define me, my age, my income, my family, you know, anything else, my DMV records. Anything, you know, that can be found gets added to that, and then that becomes, you know, the targeting, you know, record that gets used to do advertising. I'm sorry, there I went off, Natalya. What was the question again? Just so. I went off explaining how it's actually done now versus what the question was, but remind me. N o worries. The question was, what is the difference between what you're doing to gather information about consumer behavior. Oh, there you go. from what others, are doing in this space? Okay. That's the way it's done now. Our method is different, and it's very much like ChatGPT and Google Bard. You know, the technology that we've developed has read 10's of billions of pages of content on the Internet, and it has interpreted that content and understood the relationships between pieces of that content, the words on the pages, the pages themselves relative to other pages. And the consequence of that is a large If you could look inside, a large model of the language, at the conceptual level, where there's connections, if you will, between all of the concepts. There's actually, you know, 25 or so million of them in our language model. Not that that matters, but more than enough. There's really an unlimited way for the AI to kind of find its path towards these audiences. You know, takes a lot of computing power and processing power and a lot of really smart, you know, AI-based, you know, scientists and engineers to be able to build something like this, let alone actually be able to implement it. That's the fundamental difference, is that there's really not, you know, consumer identity-based data involved in anything we do. It's all public information. Thank you. The next question. Can you apply this technology to market research and product development, and is this something that you offer? Yes. The answer is yes. I'm not aware of any other technology that has the ability to do that. The answer is yes. If you think about it, you know, we've been constrained to some degree, again, with the way the environment was created, where if you're launching a new product, you know, you're at a somewhat disadvantage, you know, in terms of trying to understand what does the audience actually look like for that, and maybe more importantly, how should I design this product, you know, product that doesn't, hasn't existed yet, so that I'm aligning the features of that product with what ultimately the audience is interested in. You know, many of us, you know, would probably do surveying to do that or at least to get some perspective on that. That's not necessary with the IntentKey and the AI we've developed. We can point the AI at any product even, you know, products that are, you know, conceptual and it will, you know, help refine and define not just the audience for that, but what the audience is interested in related to that product, meaning the actual features of it, which should be part of the design. It's actually a really great added benefit. I'm glad that question was asked because it's not just a media technology. Of course, it was designed to be a media technology, but there's so many other areas, creative ideation and content creation and this product research and design. There's so many other capabilities that the tech can facilitate. Moving ahead. Is the AI able to place an ad online? Yes, that's effectively what it does. Go back to the Interstellar example that Katie said. You know, not only would it have figured out that there's an audience of possible purchasers of Carhartt's gear who were watching the Interstellar movie, but it will know all of the pages on the Internet, and there's probably hundreds of them for that one, where Interstellar is being talked about, that become good places for a Carhartt ad, because ultimately, the people in front of that screen are interested in Interstellar, which means they're probably interested in Carhartt gear because they watched the movie and it was in there and they thought it was cool. Absolutely. Next question: Can your tech also generate hyper-personalized creative in real-time based on targeting? The tech has not yet been designed to generate creative, but the concepts that are the result of the AI's definition of the audience for any product, service, or brand absolutely should be used by the creative agencies that support the companies we work with to help them with ideation related to the creative. I would submit that it opens them up to a whole different way of thinking based on a whole new subset of information. A lot of creative ideation, you know, is just that. It's a lot of people sitting in a room trying to come up with some great ideas. The concepts that we associate with the brand, product or service are in fact the stimulus for that ideation. It's a very powerful component of the creative. We don't do creative at Inuvo. We partner with companies that are, you know, that good at that. It's an interesting question. If the AI can read and understand conceptually what the concept is about, can you also target by emotion? Emotion is kind of a strange word. You know, there are concepts that the AI understands that have an emotional component to them. At the highest level, the answer is yes. As a side note, I think, and we mentioned this, you know, at the portal, we're not disclosing all of the information associated with what the AI knows. The Carhartt example was a perfect one. There's thousands of other concepts that are in that Carhartt matrix of concepts. One of the things our AI has the ability to do is actually to attach sentiment to the various concepts that are associated with a brand. Sentiment meaning the AI knows whether or not consumers have a generally positive or negative association with the certain concepts that's attached to the brand, product or service. This can be also very powerful and maybe taking it back to the last question you asked to the creative part. The last thing you wanna be doing is having, you know, creative components that while they include things that are actually good and will stimulate conversions, they're negatively correlated to the consumer. An example of this, you know, in one of the companies we worked with was, you know, checking accounts or the financial services product, and it was a checking account, if I remember right. A number of the concepts that the AI was associating with people opening up checking accounts was tax-related, Uncle Sam, if you will. There was not a particularly positive sentiment towards towards taxation. You know, while it is important and is something people think about, it was not necessarily a positive sentiment. I could imagine. If the AI is focused, less on identity and more on content, how is the demographic information that was shown derived? T hat is a great question, too. I'm glad that one was asked. This is where the paradigm has to change. It's not that big a leap of faith, but it does require that we readjust our brains a little bit, those of us that have been doing it the traditional way based on people's identities for so long. If you think about how that works, you have an identity, like I said, Rich Howe. What you're doing all the time is you're adding information to Rich Howe. There's like little blocks of information you keep adding. You know, my age, my income, my presence of children, et cetera. You just keep adding blocks. Our technology in many respects is similar in that construct. The difference is we use a concept, right? You know, you might have a concept like Porsche, like in the Porsche car, for example. We've trained the AI to be able to understand demographics, if you will, at that conceptual level. That's how it knows that. You know, in the Carhartt example, you saw Katie basically produced, you know, some great demographical information without having to use any consumer data or demographical information. That's because the AI is trained to understand those things and generate them. They don't actually get used, you know, in our technology when we're doing the targeting. It's the concepts that are the backbone of the targeting mechanism, not the demographics. They're a byproduct of it, simply because we know marketers have to know that, because behind every purchase there is a consumer, and we're all wanting to know what they, you know, generally are made up of. It's inferred. Right. How scalable is this product? Do you have any partners that are using your product to offer a service to their customers? The scalability is effectively unlimited. There's no limitations as to scale, which is probably also important relative to the context of what's going on within our industry. We're all well aware of the fact that third-party cookies are fast disappearing. Like, there's really less than 1/3 of all transactions now where you could actually buy a media spot that have a persistent identity left that you can actually target, which is, you know, the way it's done. All the datasets that you purchase to do that targeting are based on cookie IDs. There's only 1/3 of those left. First-party IDs are, you know, significantly less than that. That's the scale problem. We don't have that issue. Maybe the most notable way to think about that is, you know, we all know Apple browsers, you know, block cookie IDs, third-party cookie IDs, and I think they actually delete first-party cookie IDs after 7 days if they're not used. In fact, now they're, you know, they're redirecting IP addresses, which is another way identity gets established. We don't have an issue with, you know, with making sure our ads are, you know, in front of people who use, you know, Apple browsers. This is not a limitation. We don't have a scale issue with our technology in this regard. Thank you. We have a couple of more questions here from the audience. How is Inuvo AI informing creative execution? Are you working with creators and brands on developing the creative work? We have a few companies that we've partnered with who are exceptional at the creative parts of the advertising, you know, value chain. The answer is yes. We partner with people who are really good at that. We empower them, and ultimately their clients, with the, with the, you know, the intelligence that comes from the AI. Our next question is: Can the AI determine a consumer's intent to purchase? You know, just because someone is interested doesn't mean that they are ready to buy. This is another aspect of the technology that is materially ahead of the conventional technologies. We intimated this in the opening, one of the major advantages of our technology, our generative AI technology based on this language model that's a little bit different than the other people have done, is we actually are refreshing that understanding, the language's understanding of what's going on, every 5 minutes. What's the implication of that? I will tell you, it takes a lot of computing power to be able to do that, but we are doing it, and we did it for this very reason, for this the answer to this question is because we've known, because we've been around the ad tech world and the data world for a long time, that just-in-time purchasing is a pretty important component. Identifying when people really are in market, you know, is really, really important. It's probably one of the major reasons why, you know, Google has been so successful, because search is a good way to know that. People type it and say that they wanna buy something right now. Our technology can do the same. We're able to identify based on the concepts that are being associated with the audience, you know, really good indications that ultimately, the consumers that are, you know, made up in that audience are in a purchase mindset. Thank you. Next question: Does Inuvo utilize this technology to market itself? We have used it to market ourselves. Great. It looks like our last and final question. Let's see. You use an e-commerce brand as an example. Can the AI also be pointed towards an industry like finance, for example, consumer banking? The answer is yes. In fact, I would encourage you to visit our website. There's a plethora of case studies that we've, you know, implemented successfully over the many years that this AI's been in, you know, in place. Maybe I'll just make a little statement about that, 'cause You know, in my opening, I did say we've entered the age of artificial intelligence, but the reality is we've been in it for quite some time, but there has to be a date that marks it, and I would say ChatGPT and Google's Bard's announcements kind of signal that, hey, we're into this thing now. We've, though, been doing this for, you know, the better part of the last 5 or 6 years successfully with clients using this technology, and we continue to make the technology, you know, better. Now, sorry, Natalya, I got lost there in my answer again, so just remind me of the question, 'cause I wanna answer it specifically. I mean, I think you pretty much answered it. Basically it was just asking, can the AI be pointed towards an industry like finance? Yes. consumer banking? Okay. Yeah. Thank you. The answer is, because of all the case studies we've had by now, we've had many, many different industries and use cases. They've been, you know, ones that we quite honestly thought maybe wouldn't work or just didn't know any better. The one that comes to mind was a recruiting case study. We had a pretty well-known healthcare organization that was having trouble recruiting nurses. W e pointed the AI at that, and lo and behold, it was able to help them recruit nurses. The adaptability of this technology makes it applicable everywhere, and to some degree, removes the need to have an expertise in a certain vertical area. What do I mean by that? In fact, we had a client recently coming to us, you know, and asking us what our expertise was in a certain vertical in which they have a unique position. Our answer was, in a way, we don't have to be an expert anymore. That's, our AI is the expert. You know, it knows more about your product or service than any of us do. We're not limited by having to have had this experience, you know, purchasing all these, you know, third-party datasets that might actually be applicable to a certain industry. The answer is it works everywhere, and it's already an expert in those areas. Could do it all. We actually have 1 last question that just came in. The visualization showing the connections almost feels like it could be a new way to search the internet. Is Inuvo going to keep evolving that way? I don't know. I don't think we're gonna become a search engine. There are some very powerful companies who own that marketplace. The observation is a good one. To some degree, it's accurate. You know, concepts, you know, are just words. In many respects, our AI is making a prediction, you know, just in time, about whether or not the unknown person who's in front of a screen is likely to be, you know, a good set, a good match for the audience. That's based off of words, we call them concepts. We're not gonna get into search, but we absolutely are gonna continue and do continue to evolve this technology. Frankly, as I said in- a few times here today, if you do become a client, you will see that there's already a bunch of other things that we're not disclosing at the portal. We can, for example, tell you all the television programs that are associated with your audience. Not we, the AI can tell you that. I already mentioned sentiment. We're working on hashtags since we know obviously those are important these days. We're training, in fact, we're in the process of training the AI right now to learn what, you know, what hashtags are and be able to associate those with the audience. Lots and lots of continued innovation occurring here, continuing to add on, you know, value. This is all very exciting, Rich. looks like we have no further questions, and I'll turn it over to you for concluding remarks. Thanks, Natalia. I wanna thank everybody for joining us. We're pretty excited, you know, about this, you know, disclosure, public disclosure. We hope you'll go to the portal and play around with it and try it yourself. Ultimately, we hope you call us and allow us to try to help you know, reach those audiences. It is getting harder to do that. It's always been hard to reach audiences. I've been in this field now for, you know, the better part of 25 years, and this has always been a tough problem. Unfortunately, it's getting harder for y'all. You know, the technical systems that underpin the ways that have been used for 2 generations are now, you know, coming apart, and as a result, that makes it, you know, something that was already hard for you know, even harder. The good news is, you know, these kinds of technologies have been, you know, on the burner now for a while, have been proven to be working. I would encourage you to, you know, to make it part of your strategic discussion within your company because you wanna get a jump on this. Like I said in my opening preamble, the people that do jump on this are the ones that will get the competitive advantage over the others. With that, thank you so much. I hope you enjoyed the webinar.