Episode 3 of The Applied AI Podcast

About the episode

Bill McCalpin, founder and CEO of Capitalize Network and chair of the Alliance of Merger and Acquisition Advisors (AM&AA), brings a powerful perspective to the intersection of digital transformation and M&A success. His investment banking firm maintains a perfect track record, never failing to close a deal for any client they've taken on in 13 years. The secret lies in thorough preparation, particularly around technology strategy.

The six-fold difference in sale price

Data from Capitalize's biannual national M&A survey reveals a striking pattern: companies with similar financial performance can sell for wildly different valuations. A company with $1 million in EBITDA might sell for $2 million or $12 million. Another with $5 million EBITDA could fetch anywhere from $10 million to $60 million.

The difference comes down to how well companies compete on price, speed, and quality, all areas where digital transformation plays a decisive role. McCalpin illustrates this with a Silicon Valley taco shop that moves 150 customers through its line in under five minutes using digital ordering systems and streamlined kitchen operations. The technology creates such operational excellence that customers forget about price entirely.

Why buyers pay premium multiples

The M&A survey identifies three categories of value drivers that motivate buyers:

Existing assets: Current profit, cash flow, sales channels, customer base, brand, and team capabilities

Growth potential: Strategic alignment with buyer operations, annual growth rate, and expansion opportunities

Risk reduction: Low customer concentration, revenue consistency, repeat business percentage, strong management, and minimal owner dependence

Digital transformation strengthens all three categories. It creates operational assets through automated systems. It accelerates growth through enhanced customer experiences and market expansion. It reduces risk by decreasing owner dependence and creating systematic processes.

The digital transformation hierarchy

Companies must progress through clear stages to capture M&A value through technology:

1. Digitize data: Convert manual processes to digital records
2. Digitalize processes: Automate workflows that produce and consume data
3. Integrate systems: Connect data streams across the organization
4. Create competitive advantage: Use integrated data to identify and capture incremental improvements
5. Enable continuous improvement: Build systems that measure outcomes and refine performance

Companies that skip foundational steps cannot implement advanced technologies effectively. Alpen refuses to take companies to market without a clear technology roadmap because buyers demand it.

Different buyers, different premiums

Private equity firms often target companies with weak digital infrastructure, seeing opportunity to capture value through post-acquisition improvements. These buyers typically pay lower multiples, looking for bargain prices on companies they can transform.

Strategic corporate acquirers take the opposite approach. They pay premium prices for digitally sophisticated companies that can serve as platforms for rolling up competitors or transforming their own operations. Many large corporations lack internal expertise to drive digital transformation and acquire smaller, more nimble companies specifically for their technology capabilities.

The highest premiums—those 60x valuations—go to companies positioned as technology solutions rather than traditional service providers. These businesses become the acquirer's digital transformation roadmap.

The AI advisory gap

Despite AI's potential to transform M&A advisory services, the sector barely scratches the surface. Investment bankers spend only 4-6% of their time using AI tools, primarily for basic tasks like email composition and buyer research. Most shocking: zero respondents in Capitalize's survey reported their firms had any technology roadmap or AI strategy.

This creates massive inefficiency. Investment bankers spend more time finding clients than serving them, with business development consuming the single largest portion of their work year. Some business development-focused bankers spend over half their time hunting for deals rather than executing them.

BizForesight: scaling preparation through AI

Recognizing these inefficiencies, McCalpin partnered with Talbot West to launch BizForesight, an AI-powered platform that transforms both sides of the M&A equation. For business owners, it compresses months of preparation work into days through intelligent data collection, analysis, and advisory services. For M&A professionals, it solves the business development crisis by creating a steady flow of qualified, prepared clients.

The platform leverages Talbot West's Cognitive Hive AI (CHAI) architecture to orchestrate multiple specialized AI modules. Rather than relying on monolithic language models, CHAI combines targeted capabilities for data analysis, document processing, strategic planning, and advisory interactions. This modular approach allows the system to handle complex, multi-dimensional business challenges that single AI models cannot address (see our article on neurosymbolic AI for more on this).

BizForesight creates deals that wouldn't otherwise exist by identifying and preparing companies that aren't yet ready for market. Unlike traditional lead generation platforms, it educates business owners on the value of professional advisory services while simultaneously preparing them for successful transactions.

The competitive imperative

The gap between digitally transformed companies and their traditional counterparts will only widen. Companies that invest in comprehensive digital transformation position themselves as platforms for industry consolidation. Those that don't risk being acquired for parts at discount valuations, or becoming irrelevant entirely.

For professional services firms in the M&A ecosystem, the message is equally clear. With AI poised to compress 20-hour processes into four-hour workflows, firms without technology roadmaps face the same disruption they're advising clients to avoid. The shoemaker's children need shoes, and they need them now.

Digital transformation no longer represents an optional enhancement to business operations. It determines whether companies sell for 2x or 12x multiples, whether they become platforms or parts, and whether M&A advisors thrive or merely survive in an AI-enabled future.

Episode transcript

Jacob Andra: Welcome. I'm here with Bill McCalpin. He is the chair of the AM&AA and an investment banker. He's also my business partner. He and I are doing a project called BizForesight. We'll talk about that in a little while, but first, we're just gonna talk about the role of AI in the mergers and acquisitions sphere and ecosystem.

Before we dive into all that, Bill, why don't you just introduce yourself, tell a little bit more about yourself and what you've been up to the last while.

Bill McCalpin: So my name is Bill McCalpin. I'm the founder and CEO of Capitalize Network. And we're first and foremost a sell side investment bank. So we sell companies, we help business owners sell their companies. These are typically companies between 5 and 150 million in sale value. But what makes Capitalize unique is that we've bothered to put a consulting company on the front end of that to help them get ready. And so, significant preparation for sale turned out to really be the key, not only in getting the best sale price and so forth, it drastically improves the likelihood of close. So much so that the past 13 years in business, we basically have never taken on a client we haven't transacted with. Now when you back up early, it might not be an m and a sale for everybody because the further you back up, the more flexible you need to be. So we've made our business model flexible in that way, but that's Capitalize. Basically lower middle market sell side only investment banking and transaction preparation services.

Jacob Andra: That 100% batting average is really impressive, and it's even more impressive when you throw in the statistic that one third of your deals come from other investment banks. I've heard you cite that fact as well.

Bill McCalpin: It doesn't come from the investment bank. It comes from the failed transaction and the owners licking their wounds, saying, what the hell happened? Why did my deal fall apart? And I put a year into this and I have nothing and I'm back at square one. So what happens is they reach out to their trusted advisors and they say, what should I do? And if they know about Capitalize, they'll say, well, why don't you talk to Bill. He's probably gonna work with you for a while to get you ready. You probably didn't close 'cause you weren't ready. So yeah, about a third are from failed transactions from other people's m and a process.

Jacob Andra: Very, very impressive statistics, and that really speaks to your methodology, which we'll get into a little bit later. But on the topic of digital transformation, as you know, I'm the CEO of Talbot West, and that is what we do, digital transformation. And so obviously there's a huge overlap between what you do in helping these companies prepare for sale and what we do at Talbot West.

And we've even shared some referrals back and forth and that sort of thing, working together on some projects. But the thing I wanted to get into, so obviously in what you do, there are so many aspects, from the finances to the technology to all of these things. But I'd like to dive into specifically the technology aspect where we come in and what this podcast is really about.

How AI and machine learning technologies play in as well as other types of transformational technologies, modernization, digitization, and that sort of thing. So, yeah, would just love to hear you talk about how that factors into this whole sale price, getting ready for sale, all of that.

Bill McCalpin: So first of all, you and I met originally because in getting companies ready for sale, digital transformation and their tech roadmap and strategy become so important that I honestly, I really won't take somebody to market unless they have a pretty good idea about that because the buyers are gonna demand it.

Right. So I was looking for a firm that could assess that. And Talbot West is perfect for that. And we'll get to our collaboration later with Biz Foresight. But obviously when you apply AI and scale and digital technology to the process of getting somebody ready for sale, then the sky's the limit, right?

So basically your question about how does this affect m and a and why do we care about this? I thought that was a great question. So that's kind of where I started. Why do we care about how well we can describe our company's value? Or how well it runs inherently, including digitalization and AI and so forth. And is the company prepared for sale? Well, the reason why the owners should care about this is because when we looked at the national survey that Capitalize runs for m and a, we saw about a six x difference in sale price for very similar companies. A 1 million EBITDA company or operating profit company might sell for some kind of multiple.

Jacob Andra: So is the main difference in that six x difference due to the difference in multiple?

Bill McCalpin: The multiple just describes the difference in price. So effectively for very similar size companies, we saw one sell for 2 million and the other sell for 12. And the question is why? Same EBITDA, right? How well the company runs, how well you can define its value, and how ready it is for sale all play into that.

So along in the national m and a survey where we were capturing these prices, and by the way, this multiple held in for a wide range of sale values. So there was one that sold for two and another for 12. There was another one that sold for five and the other for 60. So for smaller companies...

Jacob Andra: That's remarkable. And for our listeners, let me just clarify. So you're talking about an m and a survey. You're the chair of the Alliance of Merger and Acquisition Advisors, and you administer a survey twice per year, I believe. So that's the survey you're referring to.

Bill McCalpin: Capitalize is very data intensive, as you might guess, because we get people ready for sale, so we're taking in a lot of data and analyzing it and preparing it for others to consume. So being very, very data savvy, we basically volunteered to run this national m and a survey. It's every six months, they send it out to over 50,000 m and a professionals, and we get back really good granular data and m and a market sentiment from hundreds and hundreds of respondents. So we have basically a private database that is really world class. So there's some quantitative questions we ask about prices and stuff like that. That's where we get one company selling for five and the other for 60. But we asked some qualitative parts too.

And so one of the questions, this is directly from the m and a survey data. The question was why do buyers buy, like what actually got them to make an offer and buy a company? And there were a bunch of factors that we allowed them to select all that applied. And I noticed they kind of fell into three major buckets here.

An existing aspect of the company, an upside growth potential or something that just made the company consistent, robust, reduced risk, et cetera. So of all these factors that we allowed respondents in this survey, who were advisors on deals that closed, thousands and thousands of deals that closed, you might say the profit or cash flow of a company. That's an existing thing that the company has as an asset. But its sales channel, customer base, brand, its team. Those are basically sources of value. Right.

Some of them fell into just pure upside growth potential. Like how well did they line up with the buyer? Maybe the buyer could double their business if they bought the company. Upside growth potential, their existing annual growth rate. So when it got to other factors we would see sometimes there were two companies that sold for different prices that had the same cash flow, right? That's like the two and the 12. So that's where you get into other elements that reduce the risk, like low customer concentration or revenue consistency, or the business percentage that is from repeat business, strength of management team, low owner dependence, et cetera. So you could say all of these things contribute to maybe one getting an offer for 5 million and another one for 60. Right. But there was one big aspect that I just thought was missing from this whole discussion here, which is the competitiveness of the company itself, right? How well does the company run? So I thought, how do companies compete well? Pretty much they compete on price, speed, and quality, right? So I had a few landscapers that I wanted to bid out a job to, and the one that responded first, and they had their act together, they almost just won the bid, right? Because their system was so sharp that they responded as soon as I left a message, boom, they were right on it. So speed becomes a factor. Price obviously is a common factor and the quality of the product or service.

So there's one anecdote I was gonna tell you. There's a taco shop that my friend took me to in Silicon Valley, and when we drove up, there was no joke, a line of over 150 people, and I thought, oh, let's keep going. Go somewhere else. And he parked and said, oh, no, no, no, no. We'll be outta here in under five minutes, probably three, four minutes. And I just couldn't understand how a small business could pull that off. But it actually happened and it worked. And it was because people were walking out onto the line taking our digital order, which was being wired back to the kitchen and somebody was reporting to the order, the total number of people in line, any customization they allowed you to do after you picked up your food. So it didn't slow down the orders, it was just a masterclass in how to move people through and the food was good.

Right. So the funny thing was, I couldn't even remember what they charged me. I was so impressed. They probably charged double. So we compete on these planes, when you start to talk about digital transformation, start to step back and say, wait a minute. It could improve all of those things, right?

I mean, it's kind of an overarching subject.

Jacob Andra: It is. And I wanted to just say that back on that slide where you were saying kind of the three buckets, digital transformation kind of plays into all of those in different areas like the price, the low owner dependency, right? There's an aspect of digital transformation that removes owner dependency.

And so there are just so many places it sort of underweaves everything. And I think that's what you're leading to here.

Bill McCalpin: With all the ways that they compete here, but also all those sources of value on the previous slide, right. It could improve any one of 'em and all of 'em, right? So that was the kind of missing element that I think also comes into play and like, why does somebody get 5 million and somebody else get 60? Right. You have to be able to describe that.

So basically, I just wanted to also kinda lay down a little bit of bedrock here that you can't do digital transformation unless your data is digitized, right? I mean, that little taco shop could not pull that off if they had somebody handwriting orders, right?

Or trying to seat everybody and then handwriting orders and running them into a kitchen, it just wouldn't work at all. Right? So first off, you need to digitize your data. This is like the bottom of the food chain, right? But then you need to digitalize the process that produces that data and only then could you even have a hope of transforming your business? So you asked me to join the podcast, I thought, well, what does digital transformation mean to me if I'm helping prepare companies for sale? And really it's kind of, are they able to follow some kind of process like this? Like if all of those data streams and processes are producing data, do they talk to each other first off, right? I mean, do they just integrate? And could the business ask a question of, if there was some kind of key data that we could have and monitor, could we create an incremental competitive advantage? Like reduce the wait time at this taco shop from five minutes average to three minutes, right? You have to be able to identify the data that would produce some kind of competitive benefit and then be able to measure both the data and the outcome, some kind of incremental improvement, remeasure the data and the outcome review and repeat. And that is kind of the highest level of, does a company have the ability to improve itself, right. That's really what we're talking about. And it segues kind of beautifully into AI because right now there wouldn't be a lot that AI could do if they were handwriting receipts and walking 'em back to a kitchen.

Right. But somebody who's bothered to do the digitalization be able to capture those key parameters and so forth might be able to improve their company. And so that's kind of walking the whole process up to the doorstep of Talbot basically.

Jacob Andra: Yeah, and I really like how you framed that because Talbot West, we position ourselves as a digital transformation company that is AI native. So we are an AI enablement company, but there are so many precursors and dependencies, like you say, where the data has to be collected and stored properly.

It has to be cleaned up. It has to, you have to have a larger holistic strategy that underpins the implementation of the AI. And then once you have all of those precursors and dependencies handled, you can deploy AI successfully. And so I think that's a really important point there.

Bill McCalpin: So important. Honestly, I will barely take somebody to market unless they've really thought about this stuff. And so we've worked together on some projects where I've brought a live MO client to you who's dabbling in AI. And it actually invokes much larger questions about, okay, if they were going to have a significant number of employees employing AI, what data is available to them?

Right? That's where you basically started. So that's where digital transformation and AI go hand in hand. But take a look at, there's a prospect I have, they're a high value staffing company, so they staff professionals, engineers, architects, so forth, right? It's all online. What are they in five years? Honestly, I don't think anybody knows. If you're a plumber or an HVAC company or an electrician or something like that, you're gonna be an HVAC company in five years and AI's not really going to change anything substantial.

Jacob Andra: Well, it'll make some of your processes more efficient, but you're still gonna be around. You're right.

Bill McCalpin: The ones that are gonna win are the ones that lean into those improvements, right? They're, I mean, roll the clock back by 25 years. And if a company said, ah, we just don't like these computer things and we don't like the internet, well, are they still relevant? Right? I think it's inevitable.

Right? So, but that factor is even stronger for a highly online company or a technical company or a services company. I mean, if you aren't creating your own future and actually being the winner with a technology roadmap, then you can probably expect to be disrupted by it.

Jacob Andra: Yeah, and you and I have talked about how these companies, especially these white collar, in white collar industries, how they can either be bought for parts or they can be the platform that an acquirer wants to buy to bolt other companies onto if they invest in the right digital transformation strategy.

If they create a technology platform around their core offering that is AI enabled, they can sell for many, many multiples higher.

Bill McCalpin: If I told you that two companies with identical performance, one would sell for five, and I said, what does the high one sell for? You probably wouldn't guess 60, right?

Jacob Andra: Yeah, I maybe get double or triple.

Bill McCalpin: They had the same revenue and profit margin. Right. So you're exactly right that you might be the technology solution that the buyer is looking for, right? There's a whole spectrum of buyers, right? Like private equity, some, they're very much into professionalization. That's their playbook, right? So they get in there operationally and they improve all this stuff.

So they're almost looking for the company that's not very sophisticated because they want to capture the upside of implementing systems and processes post acquisition.

They don't pay premiums either. They're part of the ecosystem, right. But they're probably buying on the lower end of those prices. And you're exactly right. Maybe that's perfectly professionalized and digitally transformed. There's not much for them to do. If someone does invest in all of that, then the private equity playbook is essentially to buy a platform, a foundation, and then buy 5 to 10 additional companies, brand them all together, increase their geographic radius, and sell a big company.

So if you had invested in digital transformation, you might be a target of private equity if they saw you as the platform that they wanted to roll up all of your competitors into. But otherwise, they're gonna be looking to pay bargain prices, right?

Your prices are just higher, right? I mean, because it's just more sought after.

Jacob Andra: Yeah. But then there are other types of buyers that are willing to pay more premium for digital transformation enabled companies, right.

Bill McCalpin: That's what I was just gonna say too, is that maybe they don't really know what to do for digital transformation. You're almost their solution. Right. So I always think about synergy between the buyer and the seller for every opportunity. The seller has their salespeople. Is it an opportunity to sell some of the stuff that the buyer sells as well? Right? And but if your systems are, data streams are integrated, it moves quickly, it's efficient, it's highly profitable, it's growing fast. The buyer might look at this and say, you are our tech roadmap, right? And then they're gonna pay a nice premium.

That's probably where they pay the 60.

Jacob Andra: Yeah. And especially a lot of these buyers, I mean, people would be surprised 'cause they think these larger companies, these corporate strategic acquirers must be very sophisticated themselves. But that's not always the case. And they may be excited to buy a smaller company that's much more technologically sophisticated than they are to inform their overall company strategy.

Bill McCalpin: There's that book called Crossing the Chasm where you can have some pretty impressive efficiencies and nimbleness with small companies. And then they grow into a size where they kind of slow down. And then the big, big guys have big budgets and whole teams to kind of bring it back up to nimbleness and efficiency. But that middle range there is sometimes shocking how little they've done and really they don't have the expertise in house. They don't know how to think about it. And so that's where the value of this for the seller can really, really pay off in the price.

Jacob Andra: Absolutely. So we've covered kind of from the seller perspective and a little from the buyer perspective, which obviously represents the two ends of the m and a transaction. But within the m and a ecosystem, there are a lot of other players, namely all the advisory services that help facilitate these transactions.

And so we could talk a little bit about how AI plays into all of these different advisory services. And obviously all these are all white collar services highly ripe for disruption by AI technologies, most of what they do, AI to some degree or another can automate significant portions.

And at Talbot West we always say, we're not advocating for AI to completely replace humans in any of these, but it can certainly cut a, let's say, 20 hour process down to four in many cases with humans still being in the loop to review, et cetera. So I know you've done a little bit of research on AI usage in the m and a ecosystem on the advisory side, and wondered if you want to talk a little bit about that.

Bill McCalpin: It's kind of an unfair advantage that I get to ask 50,000 people every six months these questions. Right. So this is pretty hot off the press from the Alliance of Merger and Acquisition Advisors summer conference. Both you and I were invited speakers on an AI panel there.

Jacob Andra: That was a great panel, by the way, I liked being on that panel with you.

Bill McCalpin: Everyone on the six person panel had a lot to bring to the party to inform the audience. So I was there really to represent one of those professional services that you just mentioned, right. The investment banking part. So luckily right immediately before the summer conference, I slipped in a couple questions on this national m and a survey for how much do you work on different things, Mr. and Miss investment banker. So I'll share my screen real quick. Again, this'll be the last one.

Jacob Andra: And while you're doing that, I'll just say, obviously this is a focus on investment banking, but I think it's quite representative of all the other professional advisory services as well.

Bill McCalpin: I think so too. It's a white collar service, right. But anyway, the banker works about two thirds of their time on deals, and then the other third, lion's share of it is in business development and winning the next client, and then other factors inside of the firm. But all this here in blue, representing about two thirds of their labor year, is broken up in the different stages of investment banking, of selling a company. And this is sell side, so preparing the materials to take 'em to market, to describe the company, to build a buyer list, negotiations supporting the financial aspects like quality of earnings, doing due diligence, legal work, et cetera.

Right? So all of the aspects broken down here by percentage. We got some really good data out of all this, a bunch of investment bankers answering the question. One thing that kind of stood out for me, even for a typical investment banker was that the single largest component, bigger than any one of these components was business development.

They actually spent more time finding the next client than they did on any one aspect of investment banking.

Jacob Andra: Really remarkable.

Bill McCalpin: There really are two populations. These are kind of the normal investment bankers. They're doing a lot of deal work. And then there are business development focused investment bankers.

And the population kind of fell into these two buckets. And for them it was ridiculous. It was like 50% of their time was finding the next client. And now it's not only their next client, but it's the firm's next client. Like they're feeding a whole group. Right. And so they actually work a little bit under half of their time, about 45% actually doing work, so they spend more time finding the next client. So that's really the unspoken elephant in the room here is that for the footprint of all of these areas that AI had anything to do, anything to touch, what was reported back was essentially tasks within the company, like emails and composing things, getting the information for a company ready for sale, like the SIM or the anonymous teaser that they send out before a non-disclosure agreement is signed, doing buyer research. The vast, vast majority of people said these were the only things that really AI touched currently at all.

Jacob Andra: I think that, and I think the reason for that Bill is probably because those are the types of tasks that an out of the box tool, like ChatGPT, a commercially available tool does quite well. 'Cause I remember seeing in some other research that's been published that most usage within m and a of AI is pretty much confined to these easy to access tools. Not so much the custom systems or custom solutions or the more complex ones. And so I think that is the lowest hanging fruit. And I think the m and a sector, correct me if you think if you see it differently, but the m and a sector is sort of dabbling with some of these very low hanging fruit that you can get with like a ChatGPT type of solution.

And there's a lot of other fruit that is slightly higher up that has yet to really get much usage.

Bill McCalpin: Like for instance, the buyer research and the buyer list preparation, there were a couple of out of the box providers that provide that as a service, right? So that's not really ChatGPT, that's a subscription to an AI company that's doing that for these folks. You're right that financial analysis, diligence work, legal doc, it's all coming I think. But when you actually look at 15% of this number of hours and 13% of this number of hours, it adds up to maybe a hundred hours out of a labor year, so 4% footprint so far for the typical investment bankers and the biz dev ones was actually a little higher. They were using it more for this probably 'cause they're out hunting so much, they need to have efficiencies. But still it was about a 6% footprint overall. So for m and a in general, we barely dipped our toe in the water. Yeah.

Jacob Andra: Yeah, there's a lot of efficiency there. Left to be had with AI being integrated more into all of these professional advisory workflows. So I guess the long and the short is, it's just beginning. We're at the very early stages there.

Bill McCalpin: Well, I think that if you extend it out to those other white collar professional disciplines, right? The financial analysis, the legal analysis, wealth management, investment strategy and so forth, AI is coming and it will undoubtedly have an impact. But one of the most shocking things that I found from this survey was zero of the respondents said their firm had a technology roadmap. Or any overarching strategy. It was a topic of discussion in a few, but that really shows you that this light that we're trying to shine on these poor sellers that are going under scrutiny, we might wanna take that spotlight and turn it back around on our own firms.

Jacob Andra: A case of the shoemaker's children not having any shoes.

Bill McCalpin: So.

Jacob Andra: Yeah. I wanna turn it to this business development aspect because we sort of teased the audience early on that you and I are partners in Biz Foresight and we intentionally designed it to, it's many things, in part solve this business development issue for the m and a ecosystem, as well as provide some other things surrounding your systems and processes that you provide at Capitalize. So why don't you give a quick overview of what Biz Foresight is, how it's playing in the m and a ecosystem and sort of the two sides of it, right? The advisory facing and the business owner facing aspects of it.

Bill McCalpin: Capitalize's normal process is to come in early and get them ready for market. We've just found that that gets 'em the higher prices, but almost as important, probably, well, I don't, I'm gonna say maybe more important, the likelihood of close is just astronomically improved, right? If there's one challenge with that business model is that it is labor intensive, it really caps our pipeline of clients. We can have a handful of clients in the market. We can have a handful of clients intentionally getting ready we can have a handful of clients early stage figuring out what they want to do.

And for a dozen subject matter experts that we deploy to this, that's all we can handle. So the holy grail is, for say, I'll say for three labor months, spread out over six calendar months, maybe four labor months, over six calendar months. Could AI do the vast lion's share of that? Could we actually put Capitalize's process into a multimodal agent? Because it's complex, right? There's a lot of interviewing that needs to be done. There's data upload, there's analysis. There's financials. There's a whole personal side to this. If the owner has cold feet or has a dozen aspects that are nagging at him or her, and nobody's actually unraveled all that and straightened it out and given them good answers, they might get close to close and get cold feet and pull out, right?

So that's Capitalize's process. So what Biz Foresight is, is essentially could we take those three to four labor months and turn it into one week of very critical human interface, right? It would just be a highly skilled analyst looking at the results captured by hours of interviews, data upload, data processing.

Jacob Andra: So essentially taking AI train and AI to do the majority of that, but still have a human for some of the critical portions a human needs to do. It's just that they're having to do a week's worth of work instead of four months.

Bill McCalpin: I find a helpful question for this, for almost anything AI is what is the highest best use of a Jacob hour or a Bill hour? Right. What is the highest best use of a Bill hour. The founder of this company and the inventor of the process to ask for a bunch of data and then follow up and ask for it again, and then you know what I mean?

It's, that's a waste of my time, right? If that could be done in advance, and not only uploaded, but pre-processed and put into a form where an expert could take just a few minutes of their time. And look at a high level summary of the company and say, wow, they're pretty close to achieving their goals.

I think this is one that could go to market relatively soon, or they're not close to their goals at all. We should advise them that they should go to market a quarter or two from now after doing some work. So.

Jacob Andra: Yeah, and so, so everything you're describing, this is the business owner facing side of the business. There's the whole business development aspect to which, which we'll talk about in a minute. But if I can summarize everything you're saying for the business owner Biz Foresight is an AI advisor that is collecting data, advising them, helping them kind of benchmark where they're at, where they're going, helping them clarify their goals, right? So a lot of this stuff that you're usually doing with them manually, it's doing a lot of that heavy lifting again, leaving that opportunity for the human expert to still be involved, but just much less of a heavy lift.

Bill McCalpin: Exactly. So Biz Foresight in a nutshell is taking Capitalize Network's process plus Talbot's digital transformation assessment process and taking that to scale, and having the bulk of it implemented by AI. And then having really qualified human advisors at key aspects.

And the second thing that you'll learn if you ever start a company to prepare business owners for sale, is it's a team effort. We don't have any lawyers on staff. We don't have any wealth managers on staff. It's an advisory team. Part of our normal process is to build an advisor team to help us get them across the goal line.

I don't do any personal planning. There's a whole industry of wealth managers that do an awesome job at that. Why would I reinvent the wheel? So let's get them on board. So if you could 10x 100x 1000x the pipe, then really Biz Foresight starts to become a referral engine, right? Because there's no way a small even highly skilled group would be able to process thousand x, right? So very quickly you realize Biz Foresight has two huge fundamental value propositions. One is to the business owner. It just gets 'em ready and increases their value and increases the likelihood of close, helps 'em figure out what they want to do. And the second is then it's a massive funnel of referral opportunities to these white collar professionals of all these disciplines that you mentioned before.

Jacob Andra: Yeah, so all the m and a advisory services, and that's where we come in. So we're solving one problem for the business owner, as you stated. And for the community of m and a professionals that we curate as part of this ecosystem, which of course we carefully curate them based on reputation and capability and all that.

It is a source of deal flow to them, which is solving the fundamental business development challenge. And again, it's just remarkable that they're spending so much of their calendar year on business development activities. And this is going to drop deals in their lap, not in a, I mean, there are a lot of like Angie's list type ecosystems out there that are sort of lead generation.

This isn't that at all. This is, these clients actually need the services and we're connecting them right when they need them.

Bill McCalpin: What's interesting is with Capitalize's normal process and with the AI agent as well, we're actually educating them on why they want these services. It's actually their natural next step to have an advisor do X, Y, Z for them. With Biz Foresight, it's not actually brokering leads.

It's really brokering engagements because they're essentially super, super high likelihood of engagement.

Jacob Andra: That reminds me of your own experience that I've heard you tell where you did your, you sold your first business and you tried to DIY it, and then you realized it cost you way more to DIY it. And so that's a perfect example of why getting the right professional help and so we're actually doing these business owners a valuable service by educating them on why they don't want to DIY these transactions.

Why they want to be connected to the right ecosystem of partners and get the right deal team in place. Right.

Bill McCalpin: The multiple is two to 12 and we do a good job and we get 'em a multiple up towards the top of nine or 10.

Well, if the owner wants to save a dollar and not hire an advisor, they're going to remove some time from their ability to grow their company, to grow another dollar of EBITDA or profit.

Right. They get $12 for every dollar that they create, right? So it would be very pennywise and pound foolish for them to save $1 and lose 12. That's the first thing that I tell owners. And the second thing is, it's not just DIY doing the work you have to. They're not an expert in all of these m and a disciplines.

They actually have to, there's many, many more hours of figuring out what they're supposed to do in the first place. That's the real big loss. So it's like save a dollar and lose a hundred. Right? So with Biz Foresight, you could kind of imagine that the challenge is getting a bunch of folks into the process.

Right, just into the funnel. Right. We just want tons and tons of business owners doing this. Right. One thing we learned is that it is very hard to market to business owners. They're insulated. They're solicited all the time. They're just highly skeptical. They're busy. They have a whole staff of people, executive assistants, basically protecting them from people soliciting them, right? So it is just not successful to try and get them to get that. But you have a whole generation of boomers who are already in retirement age, we're talking 60 plus already, and a lot of 'em, much higher than that. And they're starting to think about, man, I really need to, I'm burnt out. I gotta figure out something.

Right? What do they do? They're not gonna go look at ads for people soliciting them. They're gonna go talk to their most trusted advisor, right? The m and a advisor, like their lawyer or their accountant, or their wealth manager, commercial banker, who's been by their side for 20 years plus, right? Well just so happens those are the same people that are in our ecosystem. So they are the feed to the funnel. So now the challenge is we need to get those advisors to understand how much this benefits their clients. I think they're gonna immediately understand hey, if I put folks into the funnel, I might get other clients out. Like if I'm a wealth manager, I might get the wealth management work from a client who was put in by a lawyer, for example, then it starts to become a flywheel.

Jacob Andra: Yeah. And you and I, we've talked to hundreds, maybe even thousands of these professional services, and every single one of them instantly gets the vision and says, yeah, where do I sign? I mean, it's, the business model is so aligned. The way it aligns the best interest of the business owner, client, the advisory service, and everyone involved.

Bill McCalpin: I don't think you or I have talked to a single advisor who said I'm not interested in that. 'Cause basically what we're proposing to them is a constant supply of referrals to them out of the blue in exchange for them looking at their existing client base and saying, Hey, these three are probably pretty good candidates for this.

They're the right age. They're, they could benefit from this a lot. And so.

Jacob Andra: Or another way of rephrasing it is we're offering them a steady supply of new clients. And in exchange, we want them to do something that's going to be good for their clients and nurture their relationship with their clients and actually have them seen by their clients as providing even more value.

Bill McCalpin: Exactly, and where it goes really bonkers is, I think we wound up on the exact right business model here because I've done software startup companies before. I've gone out to the world and said, Hey, world, you could do something better. Buy this thing, spend money, change what you do. Rip out what you use right now and put this new thing in. And that's a little bit of an uphill slog, right? And if you got a really good mousetrap, some people do it. And, but that's a very competitive world, right? And I think the epiphany here with Biz Foresight is are some of those m and a disciplines that are used to paying origination fees.

Bill McCalpin: A referral is, if they're gonna stand to hugely financially gain that there are a few of those disciplines that are used to paying a referral origination fee for that. Well, for all the other tangential ones. If all they do is receive new business back for putting their clients in, as you said, at extreme value to those clients, there's no cost at all to them.

And actually there's no cost to the business owner. So why I think we're quote unquote batting a thousand again on talking to all of these advisors. Well, I haven't talked to one yet that said, I don't want, I don't wanna participate in this thing. So very exciting to think that there would be exponentially growing pipeline of new clients for all of these disciplines. And here's the key with Capitalize and Talbot, is we're creating an m and a deal that didn't exist, right? It was a business owner that was not ready for market and didn't know what they wanted to do. I think of the probably 30 to 40 other software providers of all the AI enabled data rooms and all the other stuff out there. They need a deal to exist, right? They need a deal to sell a data room into. We are creating deals.

Jacob Andra: Yeah.

Bill McCalpin: We're creating new deals, so we're so far upstream our, I think the business model, it's exciting. I think this will not only achieve all of that, but as you said a second ago, single largest thing that these advisors do all year long is try and find clients.

It addresses that, and I really, I can't think of another single platform or offering that is even addressing business development.

Jacob Andra: Yeah, it's exciting.

Bill McCalpin: Well, I hope the audience here can appreciate that all of this makes a huge difference. Not only in the price, but I captured all the data on the deals that closed. There are thousands of other deals that failed that I never even heard about. Right? So if you start adding those in, you couldn't possibly put, this transformation of digital technology, AI roadmap as being, it couldn't possibly be more important, right? For that kind of outcome.

Jacob Andra: Absolutely.

Bill McCalpin: And then applying it to the process itself. It's very, very exciting. Lot of great stuff coming up.

Jacob Andra: Exciting stuff, Bill. Well, thank you so much for your time and let's have you on again in a few months to talk about how it's going.

Bill McCalpin: The next data coming up is gonna talk about the margin of these companies so we can start to see. The companies like, like how much did they improve to have a sale? We can start to quantify some of this. So it should be exciting stuff.

Jacob Andra: Can't wait. All right. Thanks so much, Bill.