AIAI Holdings Corporation Class A Common Stock LD Micro 20th Annual Main Event Conference

Welcome. Thank you. That's the warmest response I've gotten in years.

I have only done about 250 of these presentations, and it's very abnormal for me to actually use a deck. Unless you guys want to use the deck and go through every single slide, I'll avoid doing that. One of the things that I have been charged with is having an extremely complicated business model. I don't think it's complicated. I'm going to start with the end, and then we'll go backwards, and I'll fill in the color in between. The question is, what does AIAI Holdings Corporation do? And the simple answer is, we buy companies, we retain the management teams, and then we use our newly acquired retained management teams to deploy our technology in our newly acquired companies. That's it. We're finished. The difference in our model is we don't sell any services or license any software to any third parties.

What we do is we use our technology exclusively for our own companies. And we have proprietary technologies that's fantastic. Of course, everybody would say that. But our provenance, I think, is pretty unique in that we have one of our architects is a guy named John Rochon, who's our Chairman, who happens to be the guy who worked with Geoffrey Hinton and started work on things like value laddering, which are now called neural networks, and how people actually make decisions, the psychology of making decisions. And on the other hand, we have Michael Sandoval, who's a former Nobel nominee for AI and happens to have run AI for Microsoft back in the day.

He has developed about 180 different branches of mathematics and science in order to augment the work that John did. We look at things a little bit differently. We call it non-monotonic reasoning. I would love to say that I came up with that very large word, but I did not. Non-monotonic reasoning means you can take a dynamic set of data and a dynamic set of rules and still come up with an answer. Most agentic AI or generative AI is called monotonic reasoning, which means you have to have a fixed set of rules and a fixed set of data in order to come up with an answer. And if the data changes or the rules change, then the agent has trouble. And then machine learning, which is kind of where everything started, is simply seeing patterns in data.

If you think about it, patterns in data is machine learning, patterns in data in context is generative AI, and then we do something different. A lot of our work actually started with finding bad guys. What do I mean by that? Literally, we hired a bunch of people into a nonprofit, and we find people who are engaged in human sex trafficking. So we have a nonprofit that does that work. We found that there are a lot of veterans who come in after serving overseas, and they do not really have a purpose anymore. So what we did is we said, "Well, your purpose is to be a hunter, and we are going to equip you with the technology to go hunt bad guys." So now they hunt bad guys in that organization.

I am pleased to report that we found 50 bad guys that are now in jail, and we put 150 into the good folks who are the authorities who are helping them find their way to jail. So this is very meaningful work to us. But in addition to that, we use it for other purposes when it comes to making companies capable of doing something they never conceived of before. What do I mean by that? So we take a company like our second opinion company. It is called MediGuide. Most people do not think about this because most people do not have these problems hardly ever, if at all. But let us imagine you are living in Costa Rica and you say, "Well, I have just been diagnosed with cancer." Well, that is a bad thing, obviously.

But Costa Rica, like most countries outside of the U.S., are what are called single-payer nationalized health organizations. If you want a second opinion, what is going to happen? You are going to take your data to another nationalized governmental doctor, and they are going to give you the same protocol and the same answer that your first doctor gave you. In the U.S., if you get a second opinion, which you are most likely not to do for odd reason, which is you do not want to piss off your doctor. You got oncology and you are worried about angering your doctor. That does not make a lot of sense, but nonetheless, it happens. So that company has relationships with 120 or so multinational insurance companies, and then we deliver this service into roughly 150 countries in 47 languages.

You might say, "Well, okay, interesting." We have changed that by virtue of our technology into a global delivery platform for healthcare services. So now we are doing things like longevity services, telehealth. We were approached by one of the largest mall developers in Saudi Arabia to do kiosks for healthcare delivery in the malls in Saudi Arabia. We are working with another one of our portfolio companies. They have a cryptocurrency called DAG, D-A-G, and we are using DAG to do cross-border payments where, particularly in high inflation environments, we can help stabilize the value exchange with the cryptocurrency. The list goes on and on. Then I guess to go one screen further, we also are working with one of the largest credit card processing companies in the world to help with preventing fraud, waste, and abuse in healthcare savings accounts payments.

What we are doing when we use our technology, again, using our newly acquired retained management teams, is we are identifying where the opportunities exist in terms of creating value inside of the company and then developing projects and then organizing them sequentially for delivery into that company. What happens is we are focused on revenue generation and innovation, which then leads to corporate growth. That is a much better message for people to hear as opposed to cost reduction, which means job loss. If I said to you, "Hey, I would like to have your help in training this agent to do your job, and by the way, when we are finished, you are not going to have a job. We do not know where you will have a job, but it is not going to be here." That is going to dissuade assistance.

Whereas by contrast, if we can say, "Hey, we are going to go grow the business, we are going to go innovate and create new service offerings, and here are five opportunities where you can professionally develop into," that is something that excites the population inside of the company. People get excited about that. They want to be a part of it. It ends up changing the friction levels inside the company, and the adoption rate is much higher and much faster. Part of our message is around speed to market. If you think about how we buy companies, you would say, first of all, or we have said publicly, we think we want to acquire companies on average 120 days after we sign the letter of intent. Well, okay, that sounds interesting. Then we want to implement our technology 120 days after we buy the company.

240 days later, after we sign the letter of intent, we are already deploying our technology. By contrast, 95% of all successful AI pilot projects are never implemented. What are they doing? They have spent all this money, perhaps wasted all this money, and the management does not put the technology into place, or it is rejected out of hand. Our model is we encourage everybody to participate. We align economic incentives. We have everybody excited about the growth and the innovation of the company. As a result, our adoption rate is far faster. By contrast, if you want to take a look at the problem from a different dimension, you say, "Well, why would not you just sell your software?" I probably had that question several times today alone. The question is, if I am doing an enterprise sale, somebody wants a CRM or an ERP, then what happens?

Somebody in middle management says to somebody in senior management, "Hey, you know what? We ought to have a new CRM." Somebody in senior management says back to that person, "That is a good idea. Write me a memo on that." Then the junior person writes the memo, and then the senior person says, "This is a really good memo. You know what we need to do? We need to get McKinsey to do a study." Then six months later and $1 million later, the study is completed, and McKinsey comes out with a conclusion that not only can you create a lot of value, but the marketplace is filled with competitors. We should do a competitive procurement. It takes two months to write the RFP. It takes two months for the responses to come back.

Sooner or later, the BAFO, best and final offer, is received. The business is awarded. Then what happens? You start negotiating the contract. That takes another 60 days from the day of the first draft. Okay. Then what happens after you sign the contract? You either start developing the implementation plan, or you have to go back through a process of reaffirming the implementation plan. This process can take two to five years. We bought the company in 120 days. Speed to market. Let's get this thing done. Now, the next question was, well, we're at the beginning, and some people in this room may say, "No, no, we're at the end. AI, everybody knows about AI. That ship has sailed." No. 50% of all businesses that are privately held today are owned by old guys like me, over 55.