Ep 366: AI Is Rewriting Due Diligence  & How We Acquire Businesses – Here’s How Buyers Win or Lose with Haytham Allos

Due diligence, buying businesses at any level, at a very fast majority, is still being done in a very traditional way. I don't have numbers on it, but from my judgment of how society is accepting AI, they're a little bit behind.

So I would say that a good majority of the work that's happening in this area is still done in a legacy way. I mean, you have to understand, the majority of people don't even understand what a large language model is, okay?

World don't understand how to use them. Business organizations, they don't know. They may not have the people to actually be like you. They don't have the people to, there's no workforce. There's not enough workforce right now to lead these organizations on how to do it.

I'm Jaryd Krause, and welcome to the Buying Online Businesses podcast. Today I'm speaking with Haytham Alos. He is an &A and AI strategist focused on how artificial intelligence is transforming the buy-side deal process in M&A.

He works at the intersection of technology, data, and acquisitions, helping investors and acquirers use AI to enhance due diligence, identify hidden risks,s and make better capital allocations. Haytham specialized in applying AI tools across deal sourcing, potential analysis, rational review, and post acquisition decision-making.

One of the first AI law firms, which is so fascinating, which we talk about at the end of the pod. At the start of the pod, we talk about how AI is changing &A? How is it changing how we buy businesses? How is it changing how we do? What are the risks of using AI without the correct prompting and understanding how to use it, and the industry knowledge?

We also talk about where we're going to go, and how we start to acquire businesses and sell businesses. We move into the depths of joining the blockchain, crypto, smart contracts, fractalization of acquiring businesses, and using AI agents to run these businesses. And we dive deep, deep, deep, deep into the field of AI and acquiring businesses, investing, and I'm excited.

I'm really excited for where this is going to go and the opportunity for people, myself, you, and everybody in the space. This is really cool. I think you will love it as well. Lean into this. It can be scary. It is a change. Change can be scary, but the more we move into change, the more we can evolve and grow. So enjoy this pod. I really did. I'll speak to you inside.

Aetherm, welcome. Welcome to the pod. Thanks for your time. Thank you.

Thank you for having me here.

Absolutely. It's necessary to have you on, really. What's happening now in &A, buying businesses, selling businesses, structures, negotiations, due diligence, using AI as a tool, it is, yeah, it's changing.

It's helping advisors a lot and even clients. I guess we start now at a high level. How has AI fundamentally changed the way &A is done? And let's maybe stick to the buy side for now, if we can.

Yeah. So I think in terms of what the implications of AI are when it comes to buying organizations that are in AI or could be in non-AI businesses. The point is, when you buy a business, what are you really doing?

What you're doing is you're reasoning behind the business model. And what that means is you're collecting a bunch of data from the business, their financials, their technology infrastructure. You are receiving a bunch of data, and we can call that data unstructured information.

And in the traditional sense, what you would do, what we did in due diligence in buying an organization, is you would essentially take that unstructured data, you put it into different templates, you present it to your business execs, and then you make decisions, a data-driven decision of that particular organization.

AI has come in and said, well, we can do that and better and much better because it can take unstructured data. It could actually model this data in such a waythate it knows all the relationships. It can relate all the relationships that are there, a nd it can actually reason and provide a very non-biased, that's very key, a non-biased view of what the business actually is.

And then on top of that, you can actually do predictive analytics on that based on other data that you can compare. For example, you can compare industries that this company is in, and you can start to do a lot of things once you have that foundational reasoning.

Yeah, there's on the buy side, I've been using due diligence, I've been using AFR due diligence to just get all the data, and just, it's really good at just plugging data into it and just having that unbiased view, as you said. And what I know is that when I read a listing of a business for sale, it's being sold.

It's being sold to me and all my clients. And it's highly attractive to see these businesses that are making this amount of money for this little amount of work per week, 10 hours per week or whatever it is. And then you get, then I go and get the data package, access to the data room, check everything out.

And before AI, this is where my skill set is. like finding the hidden pieces where the risks are, and AI can do that now. But there's also like, it also wants to be very conscious of how I share this. It's like AI is not a, should not be a replacement in the sense of like, yeah, okay.

Like, if you wanted to go away and use AI to help you buy a business without my help, fine, do it. But I would say that's incredibly risky. It's kind of like you finding this, like your goal is to say, like I mentioned before, we jumped on the pod, if your goal is to chop down a tree and you find this tool that can chop down trees, but you've never chopped a tree down before.

And then you take this tool, try and try and do it, like a chainsaw. It's very risky, like your house, if you chop it down the wrong way, or your life, maybe it's the same with buying a business as well. Like it's a tool, you need like it's tool is best used by some trades person skill to use it.

So it was a very good point what you just mentioned, and I think it's a very something really to talk about. That is, AI is not here to replace humans. This is what I tell everybody. I agree. AI is here to augment humans. Enhance and augment humans. So before, there was a lot of, call it kind of like a low-level work that had to be done.

When you're out there, you have to kind of make the arrangements with the people to get the data, actually get the raw data, the data may be in different formats, and all this stuff. So there was a lot of legwork that had to be done. Human error. And also one more thing, and that is, especially when you buy a company, it depends on the complexity of the business model.

You needed a bunch of experts. I mean, for example, when I did my due diligence on some of these companies, I mostly did it at the application layer and cybersecurity layer. You know, even those, I would go to a database, my God.

What kind of database is this? Mean, what's going on here? Do we need an expert here? So you needed kind of various experts to really put a picture together. And what would happen is because of time constraints, and you, for example, did your due diligence, not to say that you were taking shortcuts, but you were under a time constraint, and you had to come in and make some compromises and say, well, you know what, I'm just going to, I'm just pick my battles. Sometimes you don't.

Maybe you don't go after some of the small things because you don't have time, or they might not be worth it. But I think AI offers us a different perspective. It says, you know, let me handle a lot of that paperwork.

Let me get all the details, small and large. I can be different experts very quickly, and I don't have to cost that much. And I could actually give a more accurate picture of what you're buying. So I think that's the way it's changed. Now, in terms of what you do, you still have to architect the way this happens, right? And that's the thing.

You're going to spend your time now looking at the big picture and coordinating the big picture that AI can go after still have to interpret it and understand it. Sure, of course. Sometimes when I plug in all this data to an LLM for a business, and basically it's just like, buy this business because this reason, this reason, this reason.

But without the knowledge of understanding that all of those risks are opportunities, as to which one is too much of a risk and which one is too much of an opportunity to have that independent thinking of somebody that's been in the space for over a decade to know, that's too much of a risk for my buyer's profile.

And this is actually probably suits that risk suits my buyer's profile, right? You know, and what could we do to mitigate that risk and turn it into an opportunity? And it's like, some people could be missing out on tremendous deals by not understanding and interpreting the data and how it's relayed to them, or by something that is a tremendous value.

Right. So it's a very tricky thing. mean, so when we talk about buying a business, you're talking, depending on the size of the business and how much money you're putting on the line, it's still a risk, levels of risk. Now, one thing that I mean, we're talking about how great AI is, but one thing that cannot be underestimated, and that is the hallucination factor of AI.

And we all know that AI is as good as its foundational knowledge base, right? Essentially, what data has been trained on. So you can think of it as the reasoning, you can think of it as different layers of abstraction, right?

And I think when you're assessing a business using AI, you have to understand that large language models out of the box, they're designed to be sort of creative, let's just call it. Okay. They like to embellish a little bit, and there are actual levers that sometimes are visible, but not visible to the user.

Like OpenAI, JetGBD does not make those visible right there, like the temperature on top and things like that, that allow us to control those levers. So I think it's important to know that, if you're going to assess a business and if you want it to be as factual as possible, it's important to understand there are hallucinations.

So you may be geared towards something that may or may not be accurate. And then there are ways to configure the large language models where you could make it more fact-based versus more embellishment, less hallucinations. So that's very important.

Yeah, it's, I'm so glad you mentioned that. This must be such a valuable tool at the same time. It has flaws, and it's not a complete answer to everything in the acquisition process. Where do you, where do you see most buyers still rely on outdated sorts of due diligence methods, and what sort of risks are created with that versus what we can do now?

I mean, if you look at the evolution of AI, it really was November of 2022 that we started this revolution, JatchiPT 3.5 had just come along,g and followed by 4.0. But for all intents and purposes, it's only been three years.

Yeah, and it is. And so what that tells us is that due diligence, buying businesses at any level, at a very fast majority is still being done in a very traditional way.

I mean, I don't have numbers on it, but from my judgment of how society is accepting AI, they're a little bit behind. So I would say that a good majority of the work that's happening in this area is still done ina legacy way. I mean, you have to understand, the majority of people don't even understand what a large language model is.

Agree. Like most of the world, don't understand how to use them.

Business organizations, they don't. And even if they do know, they may not have the people to actually be like you. They don't have the people to, there's no workforce. There's not enough workforce right now to lead these organizations on how to do it.

What, what, okay, I want to use AI for due diligence. Well, there's a lot of that going into it. Where are you going to deposit the data? How do you know which language models to use? Are you going to use any agentic AI? I mean, are you going to have any actions associated with your due diligence? How's that going to be configured?

There's a lot that goes into it, right? You do it, and there's a lot that goes into it. So I think it's still done traditionally, but they compromise something. They compromise time, and most likely, they won't get the picture.

But if you're using AI most optimally during due diligence in an M&A, then you are going to be, first of all, you might get the picture very quickly and might be able to bid on the business very quickly. And you might be able to actually find opportunities, like you said, where others may miss that in a traditional sense.

Yeah, like, it's a very good point, is that people don't have the workforce or the team and the time required to do this in a successful way. For example, when I use it, the results change significantly depending on how I prompt it.

For example, when I ask it questions around risks and the reality of them and how I prompt it, it may be very different from somebody who just puts in the data and says, should I buy this business? And not yet, and not coming from a space of being able to do it in the traditional sense.

So, where would you say in a process AI has the most value for acquisitions at the moment? Like we're talking about sourcing, diligence, valuations, integrations, growth strategies, like what? I mean, it could be all of the above.

Where does it correct? That's the question. Where does itplace the most value in the process of an acquisition?

I think today, where we are now, so before I answer that question, you have to look at where we are with AI today. Where we are with AI today is that we have established that we can have conversations using prompts for the AI.

And then what's happening now and what's happening the next six months to a year or whatever it is, is what we call agentic AI, where from our conversations, now we can determine intent, and from that intent, we're able to take actions. And so those tools, the conversational piece has been established.

So we know we can do that. We can put a bunch of data, and we can ask questions prompted. That's no problem. The tools for intent and agency are actually maturing very quickly. So those are available. Okay. So I think the best way to kind of where the, I think where AI fits in the best way is to really just dump a bunch of data associated with the business and really just get a first look at what we are looking at.

Bound the business opportunity at a very abstract level and say, okay, based on all this data that we have right now, so what is this business? What is it doing? What industry is it? How are those industries? Are they growing or are they not growing? So, I think to myself, the best opportunity is to get a very quick first glance at what the business opportunity is.

Now, after that, you can go to the market and start using specialized tools like predictive analytics tools, things that are very specific. And you can start to kind of, for example, if you're buying a hedge fund or if you're buying a subservient.

Yeah, exactly. Then what you do is you would have specialized agents that are available right now that are personified for that purpose. And they would be able to crunch that data and provide you with very different analytics, things like that, things that you want.

So I think it's just, I think it's a top-down approach. It's really what it is with AI. Just slap a bunch of data for you from your opportunity, and just let it go. Okay.

I agree.

That's basically how I started with it is, and it's become a bit more, as you said, once you get the data and you can do different things with different agents and lead it in different ways based on the data you have, based on me having the understanding of how to lead it in the space without thinking about a deal structure or a price or evaluation, I should say, that is going to be laughed at from the seller and the buyer.

An AI agent can be biased, like it's got all of your data, it can be biased towards what it thinks you want, and it might not be; it might provide some data or answers that may not be what's possible in the real world or in the market.

Yeah, I mean, that's exactly, I mean, that's why you have to, that's why prompt engineering is so important. know, prompt engineering is a science and an art. And like you said, you know, just some Joe Blow doing some prompts, that's, you know, may not know how to do prompt engineering. I mean, what is a prompt engineer, right? Prompt engineer engineering is the ability for us to dig into the brain at different, different, different depth of the model.

Okay, that's really what prompting here is. You could do a just a rig, just a no-jo kind of a prompt. What you're doing here is just grazing the whole upper layer of the knowledge. What we saw to use a prompt engineer, what you're doing is you're digging deep. And there's a lot of depth to that knowledge, and you're trying to harness that data.

So in essence, you've got to understand how prompt engineering works and be able to harness that and be able to also balance the bias. So, for example, if you do an &A and you have buyers and sellers, like what I would do, and I think maybe you may be doing this already, is that I would come in and say, well, I've got this company.

I know that from my point of view, I see all the metrics and the analytics and all the data. Well, what do my buyers like? What are they into? What industries do they actually invest in? And can I somehow make this look very attractive to them? And how you do that, it's just a balancing act, right?

Instead of just saying, you know, these guys may be interested in investing in certain industries and have a certain way of investing, but you want to kind of map it to that idea. So you can maybe help, maybe they can invest.

Yeah, absolutely. Like, show them the path towards the acquisition and then the growth plan based on the data and all that sort of stuff. The way I see it, yeah, yeah. How can you merge it into their?

If they've got a hold code, how can you run it in parallel or merge? It'slike in M &A, the toughest thing is acquiring and not just the acquisition, but the merger, like making sure it's.

And how it fits into their portfolio because you typically want a very specific type of business that you can merge,e and AI can help you understand how to do the best merge without creating too much friction and loss, I guess.

Well, I mean, you're absolutely right. Mean, think about what is happening here. The biggest challenge, to me, the biggest challenge of an A in the merger is really people. It's culture, it's people. It's people protecting their turf. It's people playing politics. It's people doing this.

To me, that's the number one reason why mergers fail, or acquisition is fail, and all this stuff. It's because you got a bunch of biased people who are involved in all this, and their muscles are playing politics. I mean, what's happening in the world right now, we're starting to reduce that workforce quite a bit.

Little management is going away. We're starting to hire agents, agents. And there are companies right now that are strictly run on AI agents. The point is, we're going to get to a point where the companies that we are buying are actually AI agent-driven. There'll be more AI agents than people.

Which is like, as an investor, it's pretty attractive because actually, for people that are listening to my pod, they want to be able to replace their income and work less and not have to have a large team and HR and all of these things that come along with managing humans. Obviously, you're going to miss out on some, like it's not all positive.

We're going to miss out on the human, like the humanness of being in business and running a business as well. But there's definitely some, some positives there, which, which is a question that I had is like, how do you see AI changing the portfolios of business owners, or how do you see the AI changing and managing growing businesses post acquisition? it just like, those are the same answers as AI agents, or can we get more granular, or what are your thoughts on that?

To me, I think starting the last couple of years or last year, and now it's agent first and human first developing company. I mean, you're already starting to see it. You look at companies, mean, Cursor, like Cursor AI. Cursor AI started literally, I think, two and a half years ago, okay, three or two years ago. It's a 30-person company, 30 people, okay?

They're worth $2 billion. They're valued at $2 billion. Think about that. I mean, before AI, to build a company like that, to build an IDE development environment against the giants like Microsoft, right? I mean, they started. What they did is they were just AI-driven.

They built a small team, a very lean team, and they just said, we're just going to have, they built their own agents, they built their own environment, they built their own product.

So, I also think about the cultural aspect of growing a business. If I'm an owner, most employees don't like their jobs. They come in the morning, and they're not happy. Mean, data says that the majority of people who go to work are not happy. They're just wasting their life because they're not doing the thing that they want to do.

They're doing a lot of legwork, this and that. So I think that it's going to be a balancing act. I think that for every one human, there's going to be a proportion. For every one human involved, there's probably going to be some X number of ages that they're going to manage. And they're going to be, they're going to use their brain to coordinate how things are happening.

Yeah, which comes back to the prompt engineering is like you need the right mindset and the right mind or experience to be able to prompt a, you know, AI agent in a way that's going to produce phenomenal results.

I wanted to ask around that, like what sort of mindset shifts do you feel that business owners or acquisition entrepreneurs need to make when moving to, you know, AI-assisted decision-making and working with AI agents?

I think the first thing that they have to do is they really have to, it's going to be hard, but they really have to start fresh with an open mind about the capabilities of what we have today and question their assumptions.

So they have to question their assumptions. I talk to people, and they say, well, I didn't know that AI can do this. I didn't know that AIcouldn do that. In fact, just yesterday, a friend of mine called me up. He goes, my God, I have this great business opportunity.

Hey, Tham, I want you to be the CTO of this company, blah, blah, blah, in the future. And I'm like, we need to develop this prototype and do this. And I just held on a second and said, that's a great case where there's no understanding of what we can do today. Any business owner who is starting needs to understand the full capabilities.

You can do way more than what you think you can. You can start building, if you're in technology, but you can start building prototypes with something like lovable and things like that. Like, within minutes, you give it a hundred-page spec, and this thing just builds it for you. Okay. Now you can go out there and pitch, right?

So the first thing is get educated, question your assumptions, and forget about your old stuff. Just let it go. Forget about your old stuff? The old legacy. Mean, that's what I did in 2022. I was doing a lot of work in the industry. I said, you know what?

I'm just going to forget about everything. I'm all in on this. And then just started learning about our tools and doing everything. So I think that's really the mind shift that has to happen, that I am no longer going to be dealing with as many humans.

I need to know how to deal at an unbiased level, learn what prompt engineering is, and you don't have to be a technical guy to learn prompt engineering. You can actually use AI to do prompt engineering. So it's kind of weird, right?

I would like to say, it's a prompt, engineering is an art and a science, and you can use AI for the science of it. What I like about the art form is being an independent thinker, challenging ideologies, and being a bit outside the box to be able to get different results or better results because you keep doing what you've always done can get what you always got, especially as a high-level executive who's using an AI agent to just run the same things over and over again, when you could be doing something at a better capacity.

And I think that's where it really comes into is like you said, how do you get better at prompt engineering and having more space and capacity, capacity to think about the art form of how do I move this in a way that's going to grow my business or grow the business or have more influence or more of an impact.

I was just speaking to a friend in the sauna yesterday who is creating an app through Claude and a bunch of different LLMs that is specifically because he used to work for a tech company coding, and his old CEO reached out to me, who he used to work with five years ag, ando said, can like, I need, I need your help.

We need to build an app that CEOs use to help them just take their visualizations and their thoughts and just voice them into an AI agent that creates what they need, instead of them having to manage a whole team to do that.

And that's kind of where it's going. It's like, then if you've got this app that he's creating, which is fascinating, absolutely game-changing for CEOs. And then how do people become high-level executives themselves with understanding prompt engineering and being very creative, understanding the science of it, but then also understanding the art form.

Yeah. It's very important, prompt engineering, and it's an art form. And you mentioned this idea of like a great CEO too,l and these CEOs, I mean, what they're doing is they're bombarded by information, and they have what their skill is. They actually think of them as a creative CEO's job or an executive job in an AI context is being creative with their prompts.

You think about that's really what it is, right? I mean, that's what they do. They're like, they can see things, and they can formulate some speaking, but in this case, they can, with prompt engineering, like be very creative and say, well, what if we were able to add this to the business,s and how would this affect the financial lines, blah, blah, blah.

So they're very, essentially, they're prompting, okay? And a tool like that, that can help a lot of their data come in unstructured and then help them maybe suggest some things that they can do, and they can start to think, get their brains going, then they can prompt.

This is the creative part. This is what they're good at because they understand the world of business. They're too prompt; be creative in their prompt. So it's great to have these tools for these executives because it's going to help them kind of train their brain to do these prompts.

And you're right, in terms of becoming an executive, I think people just have to step up. What's going to happen is that if you step up and say, I know how to use these agents as tools, that you can you can rise to the ranks because you can manipulate the game. You can manipulate the system. You can be part of the game.

You have to be a player in a game to be the game winner.

Absolutely. And the more you play, the better you get. Yet it's like you said, you know, a couple of years ago, just, you just went all in. And I think that's what people really need to do now is that most of my audience are looking at acquiring a business and growing it and using AI to just go like in the due diligence process, go like use it, go all in with it, get better at it. Obviously, have people alongside you to guide you along the way.

And then once you've acquired the business,s and you've already got all this massive amount of data in your LLM that you can use,se and you can do that high-level executive visionary thinking and talking to it and consulting with the LLM to see how it would change the finances of the business. Keep updating the P&L there every month. Whatever the CFO is giving you, plug that in and see where, ask it for CFO advice as well.

I mean, think about how crazy these things are gonna get. I mean, think about how crazy things are gonna get. Right now, you're like M&A, you're doing your due diligence, and you present some opportunities to investors. In the future, not too far in the future, these investors are actually gonna be separate agent entities.

There's gonna be entities out there that will have their own wealth and their own portfolio. And there's gonna be people that are gonna empower these agents to make decisions, a certain level of decisions, with a certain level of money.

And so it's not too far in the future that there's going to be agents that are going to be evaluating agent-driven companies. And those agents are going to be presenting this to agent investors, AI agent investors, who are going to be crunching things.

And at some point, I'm sure there's going to be a guy who owns the bank account that says, okay, the agent says, I really recommend we should buy this company. I really recommend that we invest in this company. And I think we should invest this much because we get an ROI of this much and this stuff.

And the guy goes, I trust your agent, transfer the money. Right? It could be in a blockchain, it could be a wallet, or it could be a crypto wallet. Right? So there are a lot of exciting things happening.

What we see today as the flow of due diligence during an M&A could completely change in the next three or five years, especially as different protocols are being developed. And you mentioned Claude, Anthropic.

So Anthropic is actually doing an amazing job. I love the company, and they're really leading the space and building the foundational protocols for the industry, like MCP protocols, agentic AI protocols. So I think they're doing an excellent job.

Yeah, I use Claud,e and it's just like in the last few weeks have made some massive changes from what my friend has been sharing with me. That's just made it so much more powerful. Yeah. It's, it's a fascinating to think about how the M&A space will change.

I'm considering, like, what does that look like for people that are wanting to just start and buy a business? And it might look like they are able to invest in an AI agent. That's like my AI agent that I've built that can go out and find those businesses, plug in there, they fill out a form, have an interview, plug in there, a profile, financials, and then have an agent that go out and search that for them, run through the due diligence, present the opportunity and then get them to a decision.

Do you want to proceed to have my agent liaise and do due diligence with their agent and then present the, you know, it'll cost X amount of money to do the DD and this process to do it, and then they decide to either purchase or not.

And you know, the AI agent can do the law as well. You know, the contracts, LOI, asset purchase agreements, contract of sale, whatever it is, it's, it's pretty, pretty fascinating that it can get to that level. Don't you think? Does that make sense to you? Like, am I sounding crazy in.

Crazy at all. I happen to have a bit of background in blockchain as well. So I've done a lot of blockchain technology. And you are completely correct. think what's going to happen is to think about, here's the thing about business. Business needs a high level of integrity when it comes to business. So you're able to go out there, your agent can gather this and do that.

But if you think about it, you're just presenting an opportunity, and then there's a bunch of humans on top of this that are evaluating things, and there are banks involved. There's this and that. There are all kinds of stuff, right? So a lot of manual work.

And what I'm saying here is that if you marry AI with blockchain technology and crypto wallets and tokens and this and that, your vision becomes a reality, in my opinion. And I think this is where it's heading. Right now, AI is overshadowing blockchain technology.

There's going to be a time; it's creeping in, the foundation is there. There's going to be a time when you're going to have investors who have crypto wallets. Your agent is going to go out there, evaluate things, and present opportunities. Their AI agent is going to look at those opportunities, is going to present, and there's going to be a button with their crypto wallet that says, I'm in, and there's going to be a smart contract.

This is where I was going to get to you with a smart contract. How awesome that's going to be when you structure a deal with seller financing, earn-outs, notes, holdbacks, even bank financing, and it's all through.

It's all on the blockchain. It's because I think about, like, why do we buy something? We only buy something if we trust we have some trust in the transaction. Yeah, which is what you're talking about is blockchain and it's yeah, it's really cool to think that you've got a smart contract where conditions are set that and for both sides for a seller and and a buyer that the buyer is 100% the money is put aside into an escrow the money is going to taken through the seller financing and also like the seller, know, like it's so nice for both parties to know that the transaction is going to be complete.

Absolutely. And the thing is, already proved. There are over a trillion dollars of transactions that have happened in Bitcoin, and close to hundreds of billions of dollars on Ethereum that have happened.

It's an escort that happens within seconds. It's the best escort,t and it's guaranteed. It's guaranteed. It's not hackable. mean, just the nature of the way that consensus algorithms work. It's just not thereMeanan, it's impossible.

Yeah, really, isn't it?

It's like so, I'm just thinking about how we even structure offers in the future in this way, where it can, know, some sellers might take on more seller financing because of this, which may mean there's less maybe institutional money needing to be put in.

You know, it might change how we submit our offers and structure deals. Well, I'm sure it was because the trust is there, it will change how we structure deals, right?

Absolutely. Well, I mean, if you're talking about marrying AI with blockchain, you now have leverage. Now we can leverage, we can use leverage on these different pools that we can put our money in and gain interest.

In essence, what's happening here at the high level is that it's going to become a peer-to-peer way of doing business. Instead of the giants, the banks, all these giant companies that are kind of overshadowing, they have this control, and you have to go through their bureaucracy. We're breaking all that.

I mean, if we do have a marriage of blockchain and AI, that's all gonna break down. Okay, and you're gonna have all the instruments of today, the ability to loan, the ability to actually give money to be loaned. So hard money. All that stuff can be done on the blockchain in a high-integrity way.

And yes, the whole offering will be different because now you're saying, okay, well, if I get investment money for this, and if I put some of that in this pool, and people are borrowing against this pool, and I get some interest, then this may change my offer. All this stuff happens.

The whole diffractionalization of acquiring, as well as not just you as one person or one AI agent acquiring, where you can have multiple investors as well, and have agreements set that AI agents connected with the blockchain will carry out certain tasks and performance levels. And if this, then that, in terms of performance levels, and wow, my mind is going crazy right now. thinking about how.

I mean, I'll give you an example. I mean, I'm part of Vic AI. We are a startup, and we're leading in the market of legal AI. We just closed our seed round two weeks ago. We were oversubscribed. Thank you. And we'll go for our Series A.

But if you think about what a seed round is or any kind of funding round, it's really an M&A. It's really M &A, right? You're not buying the business. You're getting an interest in the business. You're still doing the due diligence. You're still doing this and that, and people are still putting money.

Congrats.

So in a way, there's a lot of relationship between fundraising and what an &A is. Of course, &A is the actual, you have the merger part and kind of this stuff, but that comes after. But during the investment time, it looks very much like a fundraiser.

And so I look at what we did for four months, we ended up raising a few million bucks,s and I'll just look at the whole four months. I'm like, well, in the future, if there's a company like us starting, and let's say AI is more advanced and there's blockchain technology is more advanced, this whole four months could have actually be done in a few days because we could have had your bot assessing our company, your bot structuring would have some structured smart contracts and offerings for investment.

We would have, you know, certain kinds of shares already built in the smart contract, preferred, common, this and that. People have crypto wallets. They get an investment opportunity to them. They click the investment amount,t and suddenly we've got all that money in our wallet.

Yeah. And we have our investors, and we communicate because,e like you could take smaller investment dollars from, maybe you have just to agree, but once you've got like smart contracts that you're not having to talk about.

Absolutely, yeah, you're right. What I'm saying is that, even not just M &A's, I'm just saying, even going through funding rounds, it's going to change. Like, even if we go for Series A, we're going have to deal with institutional vendors, then we have to deal with banks, then we have to deal with those. So it's just this whole manual bureaucracy that you've got technology out there that's going to, in my opinion, is going to replace it.

Yeah, there's a lot in there. People's minds are going to be, I mean, we're talking about what's to come in the future. We don't know when it's going to come, and there are certain regulations and humans that are going to slow down the process of it for sure.

Maybe, maybe, who knows? But yeah, it's really cool to see where this can go. And what I'm excited about is it allowing people that don't have a hundred grand or 200 grand to go away and buy a couple million dollar business. It's people who can have five grand to fractionalise invest in a business, which is really, really exciting.

That's what my previous role was, I was the CTO of Realty.co, and that's exactly what we did. We offered fractionalized ownership of real estate for $50 a share. You could become a landlord for $50. It was straight up.

We presented real estate, added up the shares, and these were crypto tokens. We'd represent that as a crypto token, the share. And you could be saying, want, let's say this house has 100,000 tokens. Give me 250,000.

So they become a landlord, and we actually distribute the rent. We collected rent, and we distributed rent in crypto. So they were landlords for 250 bucks a share.

So cool, isn't it? Yeah. Yeah. That's really cool. Yeah. Ithink that's what's happening in M&A for sure. Yeah.

Yeah, I'm really glad to hear about your bot. think your bot is really great, and hopefully I can bring it into use in the future.

Yeah, absolutely. Yeah. Well, as this evolves in the future, building our own AI agent for acquisitions, it's inevitable. So I'm excited. I'm really excited. I think we're going to have more chats in the future. Hey, I really appreciate your time and coming on and sharing. Where can I send people to find out more about what you're up to?

Yeah, well, currently I'm doing a Vic vik.ai. So you can just go to, and we have our app, a legal AI assistant. We're the number one legal AI assistant in the market today. Meaning that if you have any kind of legal issue, it doesn't matter what it is. We have a very empathetic and passionate. It's like having a lawyer in your pocket for four hours.

It's free, you get a first case for free, and it's a wonderful app. have 1,400 reviews in the App Store, 4.8 rating. So just download Vic, V-I-K-K-A-, I, and just chat about your legal issue, and then Vic will walk you through it, and you don't have to pay the $5,000 for a consultation with an attorney.

That is beautiful. That is amazing. And congrats on what you built. It's really, really cool. I'm excited.

Thank you, Jaryd. I appreciate the opportunity to speak with you today.

Looking forward to chatting more. Everybody is listening. Thank you for listening. If you've got further questions, I'm sure you do around &A and where AI is taking it, then maybe we can bring those questions to Hatham on another pod. Thanks, guys.

Thank you.