EP 103: Lumos: Your Business Based on Data That is Not Yours

Ed Mysogland  0:01  
Welcome to the defenders of business value. I'm your host, Ed Mysogland. I appreciate you coming back again for for some more excitement here on the podcast. So today, my guest is Brett canes of Loomis, Liu MOS. And Lumos is a is an organization that helps banks make better credit decisions. And you're sitting there saying, well, defenders business value, we're talking about value in deals and so on and so forth. Well, the reason I have him on is I, I really believe that that what he's doing is the future is a big part of the future of buying and selling a company. What what Louis does is they are aggregating data across, he was saying a billion, a billion data points that they're compiling and reviewing and helping banks determine whether or not this loan is is a good loan or not. And they help the banks establish the risk tolerance, you know, what do what do they have an appetite for? And where I'm at? And the reason I have him on is I believe that going forward that we're going to see someone him likely, Loomis, that is, they are the signal for buyers that that the business is worthy. And, and as I was, as I talked to Brett about this, one of the things that that we that we need in the marketplace, is an early warning system.

Brett Caines  2:02  
So when when you review the,

Ed Mysogland  2:07  
like a Luma status score that says yeah, thumbs up, this is a good opportunity. If you know that early on that it's a bankable deal. It's a different animal than if it you don't make the score. And so that business owner now knows either number one, either I gotta change my value, or I have to change my, how I'm operating in order to be bankable, or I have to become the bank. But wouldn't it be great to know that on the front end, to know that, you know, here's kind of how the deal is going to go down? And and you have the predictive information from Loomis, you have cashflow you have you know, and the buyer pool, I think it all compiles together and helps the business owner and that's that's kind of where I'm heading with, with, with our practice and just the future of buying and selling companies that I do believe that there's going to be more and more opportunities to to engage external analytic providers that are going to help buyers and sellers make better decisions. And that's why I have Brett canes of Loomis data on the pot. So I hope you I hope you enjoy the show. Well, Brett, welcome to the show. I've been looking for this for a long time. So welcome.

Brett Caines  3:34  
Thank you. Thank you. It's so good to be here. I really appreciate it. Well,

Ed Mysogland  3:37  
so.

Brett Caines  3:39  
So in recording

Ed Mysogland  3:42  
my introduction, I always think it comes comes best from, you know, the overview of my guests comes best from them. I butcher it. You know, I probably say it the way it shouldn't be said. But yeah, just give a high level of view and Louis. Yeah,

Brett Caines  3:59  
so So limos were just over two years old. So relatively young company. Probably the easiest way to sum up Windows is analytics as a service. Our primary focus is small business lending. So enabling banks to do more small business lending make better decisions around small business lending, build strategic plans around small business lending activity, and we do all that through data, those historical data, delivering that an easily or an easy to consume sort of way, as well as through predictive models primarily focused on credit

Brett Caines  4:45  
risk. I

Ed Mysogland  4:46  
got it well, and I'm certain a lot of my guests or a lot of my my, my audience is sitting there going, explain what in the world that has anything to do with defenders of business value. And now, when I was, when I was looking into this, you know, I do believe, I do believe that this, what you've got going is a big part of the future of buying and selling companies, I think people are gonna make better decisions because of people like you and I, and I, as I was telling you, before we hit record, I just, I believe that there is that, you know, we're seeing a lot of AI come in, we're seeing a lot of buyers, using them AI for just different stuff, to to, to understand industries, quickly understand industries, but more. So, you know, at some point, somebody has to pull the trigger, somebody has to be able to risk their equity in buying a company, and how do they mitigate their risk, you know, there's their structure, but at some point, they start turning to advisors. And that's why I look at at Lewis, and I'm like, you know, this really is probably the, at the very beginning of, of what the future of buying and selling companies looks like. So I guess that's kind of that's the long the long way of saying, Wow, where, tell tell me about Louis and, and in the buying and selling sphere, and I don't wanna say, where is it going? But I know banks are looking are are investors and businesses, they just, they're just called banks. So I'm curious to start there.

Brett Caines  6:34  
Yeah, absolutely. So I mean, maybe to sort of bridge that gap a little bit. So you know, from a business valuation perspective, you know, what, what the business valuation is saying to the bank is, hey, this is an appropriate loan amount, you know, for this businesses to devalue the business, you're not lending more than the business's worth. And that's, that's an important component for, for bank to look at. And that's also very important between a buyer and a seller, you know, a buyer must understand that Ben Zion, all of your listeners are, well aware that yeah, so where we come in and, you know, kind of bridging that is, it, we're saying to a bank, based on certain criteria of this business. And and it's not, it's not the same criteria that's in a business valuation is not margins, or cash flow, the business or anything like that, but just historically, lines in this industry lines of this size, this type of line, you know, this geography, we have models that look at local economic conditions. So we'll look at employment participation rate, as a as a factor that goes into the predicted performance of this business going forward. And so from that perspective, you know, you start getting the credit department or an underwriter the data, they need to make the appropriate risk decision, and then you know, for the buyer, the person getting the loan for the business, you know, where that starts coming into play is, that influences the rate that, that the buyer is going to get on their life. So, you know, great, you know, in an area, low unemployment rate, high labor participation rate, you know, very low unemployment, just growing wage growth in the area, you know, those sorts of things are going to mean that business has much less risk from a bank perspective. So you can start seeing that favorably impact pricing, and, you know, ultimately, you know, what you want to get to, and what we need to help banks get to is a decision that makes sense for both the bank and the person getting the loan to acquire the business or, you know, in our case, it's beyond acquisition, working capital equipment lens.

Brett Caines  9:02  
I got it. So.

Ed Mysogland  9:04  
So you were employee number eight, on the Live Oak rocket ship? Yes. And,

Brett Caines  9:13  
and what

Ed Mysogland  9:14  
prompted you to to get off that rocket ship and start building your own?

Brett Caines  9:20  
Um, you

Brett Caines  9:22  
know, I don't know, maybe, I don't know if it's, if it's like, an addiction to stress or an addiction to adrenaline. You know, but, yeah, so, we, we started organizing logic in 2007. Then we got to a bank charter in 2008. And for anyone that may not know why that is solely focused on small business lending, you know, started it really heavily, utilizing the Small Business Administration's seven eight program. They're still You know, the largest lender in the seven a program, but you know, they do a lot of business loans outside of the seven day program as well. But you know, there's this this early years, it was just a really fantastic experience. And I'm going to continue, you know, bigger antastic experience all the way through. But there's something about that, that startup phase, and I know that resonates with the folks listening right now. It's, you're kind of in it, you're doing everything, it is stressful, but there's also this level of excitement that you're building something neat, that's gonna last. And you gotta get back to the word adrenaline, there's an adrenaline there, that's, that's just, it's just really fun. So, you know, fast forward, whatever it was 15 1415 years, just the opportunity to build something, again, man is, you know, it would be wonderful if it's, you know, the rocket ship that, you know, grew into weaving, think we're doing, you know, amazing stuff is gonna last and make a difference. And the place where we think a small business is not an area within thinking that gets a lot of attention. We just want to things that may, you know, a lot, it's super special, just that focus on small business, small business. You know, banks tend to focus on the consumer side of things. If you look at those technology, even where, you know, non bank fintechs are playing, it's typically consumer focus. So we're, we're hoping to carve out a space and be a FinTech leader, thought leader at Conde Nast, Small Business Banking. No,

Ed Mysogland  11:51  
I love it. So while you were there, I guess.

Brett Caines  11:57  
Where did you get?

Ed Mysogland  11:59  
Where did you you come from, from Live Oak. And now all of a sudden, you start, you start Lumos. And now we're talking about aggregating data. Number one,

Unknown Speaker  12:10  
what?

Ed Mysogland  12:11  
Where did you get the data? What were you you're like, you know, I guess my question is, you know, how many points of data and then the prediction, you know, I'm certain there's a ton. Yeah. And so what made you say, you know, what, I think I can I can create a predictive type indicee that will help banks like Live Oak make great credit decisions. So yeah, so I'll take it from there.

Brett Caines  12:39  
Yeah. Okay. So to answer the data points, it's well over a billion data points that we look at, it's for

Brett Caines  12:49  
each business. Was that for each business? Owner

Brett Caines  12:54  
an aggregate Oh, okay. So I gotta get go. So we have going back about 30 years, 2027 years, we have 2 million individual small business loan records. Okay. And so that 30 years, 2 million small businesses, we look at monthly payments or debt service on those lines. So all of that together, you know, where it's located, original, one size, charge offs have occurred, we've got, I think I've said 400,000, defaults 300,000 charge offs. So that's a robust data set, you know, to to inform decisions. If you think at a vein, you know, you're here, you know, we're not going to we're not going to do the the pizza shop, because we did a pizza shop four years ago and went bad. So we're never doing another pizza shop. And it's like, you're making a decision on one data point, like, we've got, we've got 2 million lines, a billion data points across all this. Let's use that to make a decision. I mean, we can even drill it down, you know, to your local area. And it's still more than your one data point. So you see, you see that often in May, so we're trying to change that mindset. But, you know, really the step. I think they kind of lead us to believe is it just in banking in general. You know, the banks have their internal data. And so you know, larger bank, Chase, they have loads of internal data that they can look at and use to make decisions. But as things get smaller, that dataset gets less and less. And not only is the dataset shrinking, but the tools, the resources around properly using that data set also starts to diminish. And I mean, there's there's providers out there that that take is a bank's internal data set, and they help them organize it, create new solutions out of it. And that's a wonderful step up for a bank.

Brett Caines  15:11  
We, we sort of play outside

Brett Caines  15:14  
of that part where we're taking massive, massive amounts of data from a variety of sources, from the SBA from the Fred, Federal Reserve, economic database Bureau, Bureau of Labor Statistics, US Census Bureau, and putting all that together to say, hey, internally, you may not have all the data, you need to build a strategic plan around lending to pizza shops. But with all this external data, let's come in and do that. And then you mentioned AI, a few minutes ago. But with machine learning subsection of AI to build these predictive models, and, you know, looking at the source historic data, what are the highest correlations to predict how it's going to perform. And one of the things that makes us different than most models, most models have sort of a scorecard approach. So just use unemployment as an example. As unemployment changes, that factor will have the same impact on a loan, no matter what the loan is. So we're different in all the factors that go into making the right decision. It varies based on other factors of the line. So if you look at something like unemployment, as unemployment increases, businesses, and you know, there's a mortgage line breaker, or consumer construction, those are going to be significantly impacted. If you look at something like a taxi service, taxi services actually perform better as unemployment, right. So our models actually say, okay, employments going up, but because it's in this industry, that's a different impact than if it's in this other industry. So it's sort of a dynamic model, which, you know, we, we think it does kind of set it apart from other predict

Brett Caines  17:17  
rivals for long. Yeah. So,

Ed Mysogland  17:20  
and everybody, I'm certain everybody wants to know what, what size of businesses are. Are you talking

Brett Caines  17:28  
about? Yeah, yeah,

Brett Caines  17:30  
so we have a wish to have two models in the market now. One is called Loomis prime plus, is built specifically for loons less than 500,000. And it's, it's more purely sort of an audit decisioning tool. As we get back test, the model will get us performance it performs really well and, and it's good for auto decisioning different banks have different risk tolerances for you know, putting it on except to an audit decision, but it performs really well for that purpose. As I say most propolis $500,000 and less mine amount and then we have a separate score, we call it a qualification grade qualification grade is really good for any size one, it works fine up to $5 million, we do not market it as purely an auto decisioning grade is more of an early indicator of risk you can think of this getting loads of leads and can use it to prioritize lens, an initial screening of lens medicine to inform early decisions on pricing. Even early communication How do you initially interact with with that potential bar? Where would that that loon opportunity

Ed Mysogland  18:53  
I got it? So what's in what's in the tea leaves? So as credit tightens, does that help or hurt you? And

Brett Caines  19:02  
you know, how How hard

Ed Mysogland  19:05  
will it isn't going to be for you to turn this mammoth lending community more data focused and and like you said, you know, oh, so what you had a bad pizza a bad pizza alone. Alright, that does not mean that all pizza shops are bad. And so I mean, how do you how do you go how do you change like because like, in my practice, it's like look I'm following the data don't be don't be pissed at me because you know the empirical evidence is this and I'm sorry that's how how it shaking out but there's nothing there's nothing I can I shouldn't say there's nothing I could do it. I am only reporting on the findings ran so I guess that's so your but your your your battle is with the behemoths of of the history. So I mean, what's what's in the tea leaves? How do they adopt this?

Brett Caines  20:04  
Yeah. So that I guess the tea leaves on credit? And how that will impact us? Yeah. So I think I'll start with, yeah, we're probably we're probably at the beginning of, you know, kind of a credit, tightening cycle. Fortunately, banks have options. So sort of what you'll see as credit loosens, you'll see more use of, you know, just conventional lending products. And then as credit, credit, tightens, a lot of those conventional bills will sort of migrate down into the the SBA program. So banks have options, I think, you know, where you'll see a difference is probably in the use of conventional versus SBA products. And for listeners, you know, thinking about conventional SBA loan, I'm sure there's an opinion on the SBA loans come with a whole lot of paperwork. This is a fantastic program for expanding access to capital for small businesses. So I think you'll see an ebb and a flow.

Brett Caines  21:16  
I'm credit tightening.

Brett Caines  21:23  
This, we haven't been through a tightening phase yet as a company, but our who, you know, certainly did, you know, not prior experience, you know, when you're in a credit, tightening phase, banks tend to want more data to make a better decision, because there's just, there's a little more fear, you know, you're going to be we're taking on too much risk. So hopefully, that, you know, from a layman's perspective, as a shifter, wanting, you know, never data more information to make sure you're making the right decision, but also understanding, you know, where are the right opportunities? As a banker talking, where are the right opportunities for us what makes sense for us, our business model in our market, and that's where we can help versus really lose my way, right is lending lending lending to anything that comes along, there's less of a need for data in that

Ed Mysogland  22:16  
case. So when the when the when the banker or the underwriter or whomever is using the service, the Luma services is, so what are they required to input to get their output?

Brett Caines  22:30  
Yeah, so.

Brett Caines  22:32  
So our newest product, which is Loomis business report, and it has that credit qualification grade that I previously mentioned. And, you know, it's a tool for really early on in the process that really only requires five inputs. If it's an existing business, you know, the name of the business and you know, city where it's located. Once you start typing in the name, we use Google Places IDs to pick up locations. So it's an easy Drescher industry that is in a factor and you know, how it's going to perform the number of employees say, rough, you know, depending on how early in the deal a banker is, you know, that can be a rough estimate, you know, 10 to 1215, to, you know, whatever the number, the loan amount, and then the purpose of the line says it working capital, is it to purchase it? Is it actually acquisition is IT equipment, but interesting, so filled with this five pieces of information, how we generate a seven eight page report, which we do, where we've got a large language model, and we use prompts to ask questions, which finds I information about the business from their website, or any social media presence, you know, if they have, you know, Facebook page. And you know, the goal there is really to create efficiencies for the underwriter or the loan officer. So when they engage with that business, they sort of have what they need right out the gate, ready to go. So that's just five prime plus, which is a little more robust of a model for how to decisioning it requires more inputs, including the business owner's personal credit score, so that that model runs on. I think it's 15 points of information that are needed, but it's a much more robust decisioning model. Interesting.

Ed Mysogland  24:39  
So the in the business valuation community, the world has changed to algorithmic type valuation work, you know, we're seeing last I counted, there's like eight, eight. Now, online calculators You know, and, and, you know, some of them are pretty robust. I mean, it's pretty, pretty impressive, but it's pretty impressive on, you know, from from a business valuation guy, I'm like, you know, it makes me cringe. But at the same time, that's, that's the future. I mean, it's hard, it's hard to, it's hard to argue that, that somebody can pull far more information than I can I can make an opinion and I can I can communicate results. And, you know, as as, you know, as a deal guy, I feel it's easier for me to communicate it if I've done the work, you know what I mean? But I look at it at yours, and I'm trying to figure out,

Brett Caines  25:47  
you know, it is,

Ed Mysogland  25:50  
are you going down the same? Is your path the same as the is the business valuation group of five or seven years ago where, you know, and now it's just, it continues to improve with, like you said, machine learning with AI with all of that. It's, it's really becoming, I'm not as reluctant to send somebody that way. So I'm, I guess, I'm long, long, long question was, you know, just art, do you see yourself going down that same kind of path that this product is just going to continue learning and evolving and broadening its service?

Brett Caines  26:35  
I'm definitely looking to broaden my service. Yes, it definitely an evolution there. Um, yeah, I would say our approach a little bit different than maybe than an online business valuation calculator, our approach is more of farming banks, with the data, they need to make a better decision. And, you know, the product I was just mentioning, where we use large language models and machine learning for the, the early risk indicator.

Brett Caines  27:15  
That's really, that's really automating

Brett Caines  27:20  
a lot of the collection of information. And so why that enables is time to be spent on actually understanding the deal time, you know, to interact with that potential client. You know, there's, there's, there's a and banking I mean, there's, there's manual processes all over the place, and you know, and early stages of a land with the with the BDO, Business Development Officer and an underwriter there's, there's a large effort that goes into just collecting information, I need an underwriter, it's gonna sit down and go through your GIS and look at the Google reviews on the business, that they're getting ready to make lentic, we pull, we pull the Google reviews for them and show them in the document. So rather than spending your time a person spending time doing web searches, it's going to let us do all that it will automate it, you can see in 20 seconds, you put in this five inputs, then once you have that, study it and you start and you interact with the borrower at that point, if you if you'd like to. Yeah. So it's really it's really more automation on the last one has been manual. Is there an evolution to more more automation? I think so. And, but I think that human component, especially as deals get larger, you know, that human interaction continues to remain a key piece, you know, to assess risk by the underwriter. And,

Ed Mysogland  28:58  
yeah, I agree, I think that as we're talking, I think it becomes more of a filter, you know, that,

Unknown Speaker  29:06  
that?

Ed Mysogland  29:07  
The does this? Does this get passed? Down? does? Does it get past the first hurdle? You know, is it a bankable type, type of opportunity? And that's, that, that leads me to my next question is, you know, do do business, you know, can can an individual business contact you and say, Look, you know, I want to know, tell me about this. Tell me about this particular type of business or the business, the business I'm looking at here, you know, what's the likelihood? What's the what's the Loomis risk profile on it?

Brett Caines  29:47  
Can you do that? Yeah,

Brett Caines  29:49  
we've actually talked about that a lot internally. So I mean, our our focus as a company is expanding Small Biz as access to funding, expanding small businesses access to capital and the method

Brett Caines  30:05  
or the vehicle

Brett Caines  30:09  
by which we do that is through banks. So our clients historically have been and you know, our banks, but the end result is a positive impact of small businesses and at the same time a positive impact to the banks. But yes, internally, we we have discussed how do we, how do we go directly to the small business owner, or the potential small business owner or the person looking to acquire a business, you know, plus the platform for that, you know, maybe instead of the bank pulling this information on the one opportunity, maybe the loan opportunity goes to the bank and says, Hey, I've got this report, it is the risk profile for the business, I'm looking to operate. Take a look. So that, you know, I think there's a place there, but then also, sort of on the bicyle, between business owners on the buy sell side, person selling in business, having that report, a risk report showing into buyers, you know, hey, this business, the risks, this is how a bank is going to be the risk of my business that you're going to buy from me. And, you know, it's up to the seller to determine that they want to share that report or not. But if they share the report, you know, it's favorable. It's like, Hey, I've got, you know, kind of this this Loomis score this limits report on the risk, it's favorable, take a look, you know, if you're interested in buying them business. So there's, there's an angle there that we're definitely interested in.

Ed Mysogland  31:39  
Yeah, and I can totally shed, I mean, because

Brett Caines  31:44  
I think a lot of people,

Ed Mysogland  31:47  
especially those buyers, that are looking at businesses that, you know, if it's not a bankable deal, do I want to even go down that path? You know, and, and, and which is okay, I mean, there's, I mean, you can say, Look, you know, it didn't it, it didn't pass Lewis, you know, a predictive index score, it's not high enough to be a bankable deal. So at least that seller now understands that we have to move to Plan B, and that is now seller, financing earnout, some, some sort of vehicle, that will get them that will get them out, but at least they understand that this is the next step. Now, it is what it is. But now, you know, before before you're in it, and then figure out, I can't get I can't get the financing. I thought I would

Brett Caines  32:43  
say, so I wanted to

Ed Mysogland  32:46  
know, what are the leading and lagging indicators that you're that you're following? And, and I guess where I'm heading with it is, is when you gotten the data, were there any any surprises? You know, that you sit down and go? Holy crap, I didn't even think of that, you know, always.

Brett Caines  33:06  
Yeah, you know, um, you know, probably the, probably the,

Brett Caines  33:13  
some of the more interesting things are, where you can signed up pockets of good businesses. So, if you think, you know, within an industry that, you know, broadly, people view as owners, that's a risky industry to be and you don't want to start a business in that industry is not going to perform. There's always these these kind of pockets you see in there, and you're like, Wow, this, this pocket is completely different than kind of the stereotype of the stigma that comes with this industry. And any other places where, you know, the industry as a whole, you know, thing is this, you know, this glowing example of a wonderful industry to be in if you if you have a business in this industry, it's gonna it's gonna be perfect and perform well, and then you lose Pakistan, and I know they should. Probably one of the more interesting ones, and I've actually have a, I've shared this before. If you if you look at limited service restaurants, it has a riskier profile than something like a dentist office, which has a lower risk profile. But if you start digging into limited service restaurants, and you get down to looking at Jimmy John's to kind of the Jimmy John's franchise, what you'll see is a Jimmy John's franchise alone credit quality standpoint, a Jimmy John's performs the same as a dentist office. So Jimmy Johnson dentists have very similar risk profiles. but limited service restaurants has a much riskier profile as a whole. You know, so kind of back to the, you know, we did one pizza shop and it failed. It's, you know, it's kind of the same thing. If someone's shying away from the limited service restaurant industry, because it's risky. It's like, you probably need to look down into the data and sign this pockets. where it makes sense. Yeah,

Ed Mysogland  35:22  
I'm wondering, and like I said, I, you know, I've, I have this other platform that's been a hobby of mine. And and I'm just curious to know, do you do you inadvertently make businesses more saleable by, by your by your score? You know, what I mean, that that's not your intent. But the interesting thing is, you know, as I, as I hear you talk, and I look at it through the eyes of a buyer that, you know, if it has this, thumbs up from Louis? Yes. It's like, wow, I didn't know that. That says something. And I'm really interested. And that's kind of how I want to tie it up. Here's, you know, what is five years look like for you guys? What's the what's, where are you? And what are you doing? Yeah, well,

Brett Caines  36:18  
on the audit, if I'm if I'm dreaming big.

Ed Mysogland  36:24  
The only way to dream? You know, it's

Brett Caines  36:25  
exactly what you just said, you know, something, you know, banks. Right now, for a small business line, they will put a lot of emphasis on

Brett Caines  36:41  
personal credit score.

Brett Caines  36:43  
Too much emphasis actually on it's important, but too much emphasis, and it's and it kind of sets it like wouldn't it apply? You know, what is the owner's personal credit score, have such an outsize impact on this small business loan? That, you know, there's 15 employees? There's other managers, you know, there's so much more that goes into it. But nobody, nobody digs into that, you know, all his personal credit score, you know, what, what, what is it? 680? Really, what is this? Good, you know, it's just, they have these numbers, and they go back, dreaming big five years or now Lumas, you know, the counter to your two thumbs up, made a comment on this business, you know, I got a two thumbs up from from Loomis having that sort of appeal and trust among banks, or among buyers and sellers and businesses that

Brett Caines  37:41  
the limos score

Brett Caines  37:45  
or the Loomis grade, depending on the product, you know, the packet, the seven page packet, you know, that we have on the business, that there's a sort of broad acceptance and trust and that package of doing our jobs correctly. Where it makes us okay, you know, Loomis gives us, you know, X score y school, and the seller of business report like, hey, this, this, this is good. I want potential buyers to know this, that there's this this use of Lumas. That helps expand lending through a better understanding, versus Canada's over reliance on these legacy scores that sort of trickle into the small business world over time, but don't really mean as much as they they could. It's important. Don't get me wrong, because it's important. It's a factor. But I think there's an over reliance on on some of these legacy factors.

Ed Mysogland  38:48  
Yeah, I get you. So the last question I have asked this for, let's see you you're episode 103 or four. So I've asked us from every guest, and that is, if you had one piece of advice that you would give to our listeners that would have the most impact on their business. And you can read the data. What what would what would you say what makes the best impact or the greatest impact based on the LUMO score? How's that? Wow, um,

Brett Caines  39:23  
you know, honestly, I think probably surrounding yourself with good sites, you know, well, but one of the things we look at

Brett Caines  39:34  
is,

Brett Caines  39:35  
if you look at a business, you know, there's a single owner versus multiple owners, multiple owner businesses tend to perform better than single owner businesses.

Brett Caines  39:48  
Why, you know,

Brett Caines  39:51  
uncertain, but, you know, probably because there's sort of a healthy discussion about, you know, business trajectory. If you don't need multiple owners to have this kind of discussion, if you're if you're single owner, you know, find good folks in industry. I'm fortunate to work with a lot of good folks. And we have constructive debates on past, you know, what are the right decisions? You know, taking that approach, you know, was maybe set another way, you know, a mentor in the space, you know, just somebody to bounce ideas off of, you know, what's worked in the past was there's, there's lots of history, you know, with, with just dropping things, you need to Yeah, you got to kind of build on those learnings. Versus, and I've made this mistake, having to relearn the bad decisions yourself.

Ed Mysogland  40:43  
We've all paid a lot of tuition. All right. So what's the best way we can get in contact with you? I'll have it in the show notes. But where do we find you? Yeah, you

Brett Caines  40:54  
can check us out at Loomis data.com As l u n is da ta.com. Also LinkedIn I you can check me out on LinkedIn. But canes, as well as Loomis it's actually limitless technologies on LinkedIn.

Ed Mysogland  41:11  
Well, I will have that in the hour, we'll have that in the in the show notes. So Brett, man I've been I told you, I've been looking forward to this. And and like I said, I've been in the business for 31 years, I've been watching buying and selling for a long time. And, and and so you see the evolution of you know, you start to see where it's going. And I as when I was newer in the industry, I didn't see I didn't see the transaction patterns and the things that the things that I didn't think were were viable are now commonplace. And now you know, I see something, something like what you're doing and it's, you know, it really gets me stoked, so I'm really grateful that you came on to the hangout and share a little bit about what you're doing.

Brett Caines  42:04  
Oh, thank you definitely enjoyed it. Very much. Happy to come back anytime.

Transcribed by https://otter.ai