Inuvo at IAccess Alpha: AI Tech Leads Strategic Growth

On Tuesday, 24 June 2025, Inuvo Inc. (NYSE:INUV) showcased its strategic initiatives at the IAccess Alpha Virtual Best Ideas Summer Investment Conference 2025. CEO Rich Howe highlighted the company’s innovative AI technology and its potential to transform digital advertising amidst evolving privacy regulations. Despite positive growth metrics and strategic positioning, the company faces challenges in achieving cash flow breakeven, with a $100 million revenue target in sight.

Key Takeaways

• Inuvo’s AI technology targets audience interest without using personal data, aligning with privacy trends.
• The company reported a 57% year-over-year revenue growth in Q1 2025, with $26.7 million in revenue.
• Aiming for $100 million in revenue for cash flow breakeven, Inuvo is expanding its sales and marketing teams.
• Inuvo has received acquisition offers but seeks a valuation that reflects its true potential.
• The company is competing in the $300 billion advertising market, leveraging its AI to capture market share.

Financial Results

• Trailing twelve-month revenues reached $93.5 million.
• Q1 2025 revenue stood at $26.7 million, marking a 57% year-over-year increase.
• The company projects a 25% year-over-year growth for Q2 2025.
• Inuvo targets operating cash flow breakeven by 2025, requiring approximately $100 million in revenue.

Operational Updates

• Inuvo’s proprietary AI reads millions of web pages to understand consumer interests, enhancing ad targeting.
• A second AI technology measures advertising effectiveness across channels.
• The company serves hundreds of clients and is expanding its sales and account management teams.
• Inuvo aims to capture market share in the $300 billion search and programmatic advertising market.

Future Outlook

• Inuvo plans to scale through increased sales and marketing efforts, adding qualified personnel.
• The company is capitalizing on the shift in digital advertising due to increased privacy regulations.
• Targeting verticals such as retail and auto, Inuvo is open to acquisition if valuations reflect its value.

Q&A Highlights

• Inuvo has received acquisition offers but believes its current valuation is too low.
• The company collaborates with larger corporations but does not plan to merge.
• Inuvo’s privacy-centric AI technology positions it to compete against larger agencies reliant on traditional data-driven methods.

Readers are encouraged to refer to the full transcript for a comprehensive understanding of Inuvo’s strategic direction and financial performance.

Full transcript - IAccess Alpha Virtual Best Ideas Summer Investment Conference 2025:

Jenny, Host, IAccess Alpha: IAccess Alpha Virtual Best Ideas Summer Investment Conference twenty twenty five. IAccess Alpha hosts virtual investor conferences featuring companies sourced from investors with a track record of generating alpha. Today you will hear presentations from 14 selected companies. IAccess Alpha holds four virtual investor conferences annually, one per quarter. The next event will be the iAccess Alpha Virtual Best Ideas Fall Investment Conference twenty twenty five scheduled for September 2025.

We’d also like to take a moment to thank the many investors who have pitched in with ideas or helped source companies. These conferences wouldn’t be as valuable or high quality without your ongoing support. Now let’s begin with our first presenting company, Inuvo Inc. If you’d like to ask a question during this webcast, you may do so at any point during the presentation by clicking on the ask question button on the left side of your screen. Type your question into the box and hit send to submit.

I’d now like to turn the floor over to today’s host Richard Howe, CEO of Inuvo Incorporated. Richard, the floor is yours.

Rich Howe, CEO, Inuvo Inc.: Thank you, Jenny, and thank you those who have attended this. As Jenny pointed out, my name is Rich Howe and I’m the CEO of Inuvo, and we trade under the ticker symbol INUV. To the best of my knowledge, we are the only company in the world to have successfully developed, commercialized and patented large language generative artificial intelligence, specifically for the solution of audience discovery and targeting online. Like a lot of good technology, our AI actually started its journey in life in a machine learning lab at UCLA and we were fortunate enough to acquire the underlying patents and the original technology from that and then commercialized it specifically for the use case of targeting audiences online. In the last thirty five years there’s really only been two evolutions in ad targeting, And the first one actually started when the internet itself began.

And the second one has been in place probably now for the better part of twenty five or thirty so years. And this most recent evolution, the one that is universally used across digital targeting, depends entirely on the use of your and my and everyone else’s private data, meaning without the ability to identify who a person is and use their data the targeting technologies are for the most part useless. Consumer data privacy legislation and technology changes that are impacting the very plumbing of the internet are making this current method of targeting people based on who they are and their data obsolete. In fact, as of today most people with an iOS device using Safari browsers are for the most part invisible as it relates to targeting because of the privacy changes that Apple has made. And that represents you know some 50 or 55% of mobile traffic.

So this is a significant problem for advertisers and it presents an opportunity for a company like ours who has built what we believe is the third evolution. And we believe we’re positioned well to be able to capitalize on a large market and take market share as a result of having a technology nobody else on the planet possesses. I may say some things during this presentation that are forward looking, please do treat them as such. Our markets are large. It’s one of the reasons why we commercialized this technology specifically for this market.

The ad market has a significant amount of spend. There’s really sort of three high level categories to this market. One of them is you know the search marketing area, the other one is social marketing, and the third is customarily referred to either as the open web, just generally the internet and or programmatic marketing. We have technologies that allow us to play in two of those markets and as you can see from the slide these are significant size marketplaces, 100,000,000,000 for the search marketplace and over $200,000,000,000 for the programmatic marketplace. And so this gives us a lot of confidence that we can actually build a significant sized business here just given the sheer size of the markets we’re playing in.

The challenge of the Internet quite simply stated is for the last thirty years, we’ve been tracking consumers around the Internet. And all of the companies, be they analytic companies, data companies, ad tech companies, measurement companies, all of them depend on the ability to actually track a person throughout their journey. And that journey involves many different paths. You could be on Facebook, you could be on search, you could be just seeing a website, you could be watching a television show online. Unfortunately, that path is now broken.

And with it, so are thousands of companies who have built all of their technologies on the back of actually being able to do this. This is the problem that we set out to solve with this large language generative AI that we have developed and now proven many times in the marketplace. And it gives us a competitive edge in the marketplace and allows us to target consumers in a way that doesn’t violate their privacy while at the same time it’s performing measurably better than the current methods in any and all head to head tests that we have done against competing providers. We actually have two different types of artificial intelligence solving the two biggest problems. If you can’t track people around the internet, then you can’t actually effectively measure the effectiveness of the money you’re spending across channels.

Meaning if I can’t tell when you were at Facebook and then you went to Google and then you saw an ad on a website somewhere, then I have a really hard time attributing the spend that I have against the value created from those various ads. It’s near impossible to do that anymore. So we developed a technology, a machine learning technology that does the following. It basically can take all of the spend for some historical period across any and all of the channels that our clients are using and then deploying some algorithms that we have developed and extended ourselves proprietarily. It has the ability confidently to predict which of the channels are producing the value and which are not.

And of course what this allows our CMO clients to do is to have a dashboard that they can use to basically dial a spend up and down across the various channels they’re using. Hugely beneficial and has been proven to be successful now in many of our client implementations that has had material changes to their business. The second artificial intelligence technology is the one I spoke of at the beginning that nobody else on the planet possesses, and that’s the implementation of large language generative AI. This is technology in many respects comparable to the large language technologies we’re all now accustomed to using the chat GPTs and the Gemini’s and the Grox and the CLODs and whatever are out there. Similar in the sense that to accomplish the goal of building this technology, we had to build a machine that has the ability to read and understand and build a language model for the collective wisdom of humanity represented by all of the content on the internet, hundreds and hundreds and hundreds of billions of pages.

And that’s exactly what we did. And interestingly, we started doing this now maybe seven years ago. So before anyone was even talking about a ChatGPT or a Gemini, we were actually on this as a solution at least to our use case problem. And the technology is out there today and it’s still reading pages every day, millions of them every single night. Fundamentally, it has the ability to determine for any product service or brand the reasons behind why someone’s interested in that product service or brand.

It does that without having to know anything about consumers. So for example, if you look at the left side of the slide here, you see the Wall Street Journal in the middle And the Wall Street Journal in this case would be a subscription. So the Wall Street Journal is looking to basically you know find subscribers for this. And what our technology would be able to do is find out all the reasons why people might be interested in the journal. And the reason it has the ability to do that is because it’s read everything that’s ever been written about The Wall Street Journal by everyone, anyone.

And of course, one of the audiences, a well known one that comes to the forefront for the journal is the Theranos fraud. The journal was the company that broke that fraud. And so if you look at this, our AI would have immediately figured out that Theranos is a catalyst, if you will, probably to people wanting subscribe, I. E. A reason behind why they would want to subscribe.

And so it would lock that into its memory. On the right side of the screen you see the other side, the media placement side. So here you know you have all kinds of You have connected TV ads, you have online videos, you have web pages where you can put ads on. If we just look at the top one you see a movie there called The Dropout.

Now because our technology has read everything about everything, it knows what this television program is about And it would conclude immediately that that television program is about Theranos. And consequently, when a media opportunity comes available to be able to place an ad there, it would associate the fact that this is an audience member who is probably interested in Theranos and ultimately that would make them a good candidate for a Wall Street Journal subscription and it would put the Wall Street Journal subscription there. So the evolution that we have designed and developed with this technology really takes ad targeting from being about people. The way this is done today is it is all around figuring out who people are based on their data to actually doing audience discovery and targeting based on the reasons behind why consumers are interested in the things they do. And we believe this second approach, a paradigm shift in many respects, is a way more powerful way to do this.

And the evidence speaks for itself in the performance that we’ve seen for clients. This technology comes to life when you see it in a demo, so I’m going to play a demo now. It’s a video, so I’ll be quiet here probably for five and the next slide is really just going to show you an example of this related to this Wall Street Journal case.

Unidentified speaker: That’s it. So now that we’ve explored denial of home business deal, which upheld her Yes. Thank for your help. Audience dynamic narrative, surfacing relevant themes as they unfold in real time. Sentiment and demographic insights like age, gender, income, and education.

The geographical view. Visual lines across The United States.

Rich Howe, CEO, Inuvo Inc.: So what you’ve just seen has never existed before, and it is amazing. The ability to be able to prompt a system and have it generate an audience for you in minutes, and maybe more importantly to be able to generate an audience about anything is amazing. It’s transformational, it’s never been done before, nobody else is capable of doing it, And it really is what I like to say democratizing the challenges associated with marketing. The analytics and the data and the discovery, done by an AI without violating any consumer privacy and being designed for the future, not the past insofar as the way the internet is developed. We think it positions our company quite well over the next few years to capture market share.

At this point in our journey with Inuvo, we’re roughly $93,500,000 in trailing twelve month revenues, and we’ve served hundreds of clients. And so we’ve had plenty of opportunity to prove out the value proposition of the technology you’ve just seen directly in market with clients. But here’s one out of many. It’s a recent one that we’ve been working with. This company is called James and James and they’re a higher end furniture manufacturer.

Prior Inuvo engaging with James and James, they were, like a lot of companies, using an agency to help them with their marketing activity. They were spending twice as much money as they’re spending now and they were losing a lot of money. And in fact, the company itself was getting close to being on the verge of going under. Maneuva came in, we deployed both our AI technologies, the one that allows the CMO to measure the success of the money they’re spending, second, the technology to help them find the right audiences and then target those right audiences. And within three months the entire picture was turned around for this retailer.

Now had a return on ad spend that was an increase over the prior spend they had of near 100%. They were able to open up and understand which channels were working and which were not working, turn off the ones that weren’t, turn on the ones that were. And now they’re profitable and they’re on a growth curve and leveraging our technology and the great products they have, there’s going to be a bright future for this company. There are literally tens of thousands of these kinds of James and James companies in The United States alone. And so we think we’re in a great position to steal market share.

The growth profile for the company has been attractive. We’ve had a compounded growth rate over the last five years of about 6.5%. We grew 13.5% year over year in 2024 and we’ve had a growth rate in Q4 twenty twenty four which was 25%. We had a 57% growth rate in the first quarter of twenty five and we’ve already guided the second quarter of twenty five to be up 25% year over year. As a technology company, as you can tell from this presentation, a highly technologically oriented company.

AI costs a lot of money to build with the computer systems and whatnot. It takes about $100,000,000 for our company to be generating cash at the operating level. And we’ve broken through that barrier a few times now. We did $26,700,000 I think in revenue in the first quarter of twenty twenty five. And so we believe this year we should be able to have at least an operating cash flow breakeven on the business.

And we do expect to see continued growth in the company going forward. We’ve had the good fortune to be able to serve a lot of clients. Here’s a sampling of them. As I said and continue to say every time we serve these clients we see a measurable increase over what they were doing before we showed up. So performance is not the barrier to our technology.

The real hard part of gaining market share is the aversion to change in the buyers and the sheer number of competitors whose business models are so dependent on the old methods that they create complications for us in sales cycles. But we are fast overcoming that as the legislation changes and the technology changes that are changing the internet are having an impact on forcing effectively people to change. Just maybe to sum up and then probably turn it over to Q and A. But as I said, we are really the only company on the planet to have created this next evolution in digital audience discovery and targeting. We have a catalyst, if you will, in that there are some large changes in privacy that are ongoing that are helping us.

If you can’t target people online, we become a good choice given we don’t have the limitations of the existing technologies. We have disruptive technologies that are being applied in both the search and the programmatic markets, roughly a $300,000,000,000 market between the two of them. We have proven growth now for at least five years, know, steady proven growth with accelerating growth actually starting in Q4 of twenty twenty four. So we think that that’ll help us scale and as I said earlier, now having served hundreds of clients, we don’t worry about whether or not we’re going to prove our value proposition. We go into a client, We spend most of the time in our sales cycle trying to convince them to change and take the risk associated with changing off of something else.

And with that, I guess I will turn it over to any Q and A. Okay, so I see that some of the questions here, so I’ll see what I can do to manage this. One question that’s asked here is anyone interested in acquiring the company? I would say we’ve been approached a number of times over the years to be acquired. And the only thing I can say is I don’t think we’re right now at least at the valuation that we have, which we believe is significantly less than the inherent value of the company we have in a position to be able to sell to somebody and reward our shareholders you know for all the hard work that we’ve put into this company.

So the answer is yes, but you know we need I think some more growth in the company and perhaps get ourselves to this cash flow positive, which we will this year before maybe an acquisition becomes serious. And there’s a second question there associated with this, which is why not merge or something with a larger company? We work with some larger companies, but we’re not really merging with companies, we do work with a large company. I should point out that we have our three largest clients are three of the largest companies in the world, one of the largest retail companies, one of the largest tech companies, another one largest auto company. So now the question becomes what are the larger agencies doing?

The answer is they’re all doubling down on the existing identity mechanisms, the consumer data methods. And this is exactly what happens when an industry disrupts and you have thousands of companies who are dependent on the old ways. Instead of reinventing themselves and doing it the way they need to do it to win in the future, they basically try to figure out how to take their round peg and put it in a square hole, and that’s the best way I can describe what’s going on, and it’s happening almost universally. So we can help those companies, but in many cases we’re competing with them and we see actually an opportunity to steal market share. The third question I see here was how do you plan to scale in 10 ks across verticals?

We serve a number of verticals now. We have some dominance in the client base and retail and auto. Key to scaling this is boots on the ground. And we have a sales team that’s out on the street and we have an account management team trying to grow within the accounts we have. The answer to the question is we just keep adding more qualified people to do that and get out in front of people and spend some money on marketing so that people know that we’re out here despite the fact that we’re now almost $100,000,000 in revenue.

We’re still a small player relative to the billion dollar Goliaths who are in our industry. And so that’s what I have. So with that I will will thank you for attending today and I’ll turn it back over to Jenny.

Jenny, Host, IAccess Alpha: Thank you very much Rich. That does conclude Innuvo’s presentation. You may now disconnect. Please consult the conference agenda for the next presenting company.

This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.