RHS 150 - Solving Industry Classification with Alan Ringvald

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Hello everyone and welcome back welcome back to the show. Today, we have an absolutely tremendous episode for you, a conversation with the CEO of Relativity 6, Alan Ringwald.
Now, you may or may not have heard of Relativity 6, and it's very possible that you haven't, and that's okay, because what Relativity 6 is doing is solving a very distinct problem in our industry, which is figuring out the NAICS code for a business, figuring that NAICS code accurately and being able to consistently deliver results that happen in real time so that we either either as frontline agents trying to figure out where best to place business or what industry class to associate a business with, and underwriters can easily have a single source of knowledge in which they can communicate around what the proper industry for a business is. Now, if any of you write commercial insurance, particularly small business, figuring out the industry class can often be a major challenge and can be a tremendous roadblock, especially when there's disagreements between, say, you, the agent, and the underwriter as to what a class should be.
And Relativity 6 is solving this problem. They're doing a tremendous job.
Any of you who are appointed with Coterie, as we'll discuss, are familiar with Relativity 6's technology in that Coterie is one of the best industry finders in the game, and it is powered by Relativity 6, which means that, from my perspective and the usage of many different portals for all these different carriers that we have access to at Rogue, the work Relativity 6 is doing is the best in the industry. It is a best-in-class tool for figuring out which industry or which class of business a particular business should be associated with.
Okay, so there's a lot of mouthfuls in there and hopefully that came across. It'll be much clearer once you get into the episode.
Listen to what Alan and I discussed and there's a lot of interesting stuff in here, not just about Relativity 6, but about the insurance industry in general, technology, what it's like to be someone who did not come from the insurance industry and is now doing work in our space and sharing, selling into our industry and all that. Full disclosure, I'm not an investor in Relativity 6.
We don't use Relativity 6 outside of the

carriers that use it. And they're not a sponsor of the show.
So just like to get that out to you

so you know where I stand versus this company. Just think Alan's a tremendous guy.
I think he's

very smart. Love what they're doing at Relativity 6 and wanted to get just kind of his ideas and the problems that Relativity 6 are solving out in front of you guys.
Before we get there, I want to give just a big thank you to all of you as always for listening and a simple ask. Guys, if you enjoy this show, tell a friend, share the show, maybe leave us a rating review on iTunes.
These kind of things help us grow our audience. Get in front of more insurance professionals.
There's more new people coming into our industry every day. And if you've been a long-time listener of the show, a simple share into social media or just text messaging a friend, hey, you should subscribe to this show.
It helps go a long way of just increasing our audience, helping more people get access to the companies, thought leaders that we bring onto the show. And obviously, I charge you nothing.
I mean, this show doesn't cost anything other than your time, which I guess is expensive. And I appreciate you helping us continue to grow the show because it helps us match these thoughts, these ideas,

the concepts, the way that I'd like to address problems and that the guests that we bring

on address problems, it exposes more like-minded people to those concepts.

So any kind of share, any kind of support, any kind of rating, review you can give for

the show, greatly appreciated.

It's how we grow the show.

And as always, I love you guys for listening. With that, let's get on to Alan Ringwald.
Yo. What are we eating? Yogurt.
Healthy. Yeah.
Gotta keep looking good, man. I know.
I know. You're taller than I thought you would be too.
That's cool. That probably helps in general, in life.
We got to put, got to put a fuel in the body. There's a lot of body to move around day to day.
So for sure, for sure. No, I, I can't tell you last time I just like had lunch.
Really? Well, cause I just sat down and yeah. It's just like, I don't know.
I just work all lunch really well because I just sat down and yeah it's just like I don't know I just work all day I know you know like I know that there are people I've heard of people like taking a lunch I know that's like a thing I don't know that that's happened in my life in years like it's just like oh I. I'm going to walk to the fridge, grab,

right. Try to shove it in my face before I let you into this zoom and it just didn't work.
I couldn't get it in the face fast face hole fast enough. Right.
Right. Yeah.
Yeah, exactly. Well, don't put on any errors for me.
Well, good. I didn't.
So I'm wearing a t-shirt. I'm eating yogurt.
I love it. But no, dude, I'm super excited to talk to you.
Cool. You know, we have a couple of mutual friends and obviously we met in person and we talked on the phone.
I think I may have been many six months or a year ago now. I can't remember when, but it was a while ago.
But yeah, I'm just so intrigued by what you do. And then, you know, I was talking to some of my friends at Coterie and they're, you know, they were telling me a little bit more.
And I know you've got a partnership with them and a bunch of other people. And just my experience with what you with with at least some functions of what you guys are doing.
And I want to get the full breath has been very, very positive. Awesome.
So I want to take this time together and just start with, and then I want to talk about some industry topics and get your thoughts and stuff on that too. But just start with like, what is relatively, what is relativity six? And like, what is the problem that you guys are solving? Let's, let's start there and then we'll, we'll, we'll cook.
Love it. That'll also give me a chance to eat my yogurt while you answer that question.
Yeah. Should I just start blabbing? Start blabbing.
Okay, cool. So Relativity 6, we're actually, it's pretty simple.
We're focused on one kind of a data point, which is what does a business actually do? So what's their primary business activity? And the value prop, like what I think sets us apart in general is that it's not about what the company did when they incorporated. It's not about what the company did when they got that DMV number.
It's not what they did last year. It's all about like, what is this company doing right now? And what was cool is actually at that InsureTech Boston conference, I think it was Risa who was like, who was talking about how since COVID, 20%, at least of small businesses changed their primary business activity.
And, you know, it makes a lot of sense, you know, there's, especially at that smaller tier, that segment that like a coterie cares about, there is a lot of movement, there is a lot of pivoting. And it's, it's hard to narrow down exactly what it is they do now versus what they did when they started or even when they started, right, it's self-reported a lot of the time, you know, and what do you care as a business saying what you do when you're reporting that, not realizing that it's a massive data point for an underwriting decision down the road.
So what we do is, so we focus on that, what we, the way we do it what we think different in that um you know we're not buying any third-party data and kind of reselling it at all um it's a true original data point and it's all about digital footprint so that's kind of our methodology is kind of got into the way that a commercial underwriter would take in a submission and basically go out on google and try to figure out, okay, let's find this company. Let's figure out what they do.
And then let's map it to one of the thousand six digit NAICS class codes, which is like the standard way to solve this problem. Now.
I don't know if you've ever done it, Ryan, but it's brutal. It's like, it can be a long process.
You have to do, you know, a lot of these small commercial underwriters doing 20, 30, 40 of these a day, maybe more. It can take half an hour, 40 plus minutes.
So what we do is we mimic that with technology. So our technology takes the name and address of a business.
We do about 400 pages worth of search results in real time. So we use search engines.
We grab all the metadata from that in that moment in time when we do the search. That becomes basically this big corpus of text about the business that we grab all that content.
And then we start predicting what does this company do from a six-digit NAICS class code level with some confidence scoring. We get into things like, what are the most relevant websites related to this business? Because a contractor is an example.
A lot of them don't make websites, but they're definitely reviewed on Yelp or porch.com or Facebook. So we compile all that quickly.
And then we even add what we call keywords. So these are the most relevant words related to the business.
And all of that happens in about one to two seconds so it's very fast it's happening in the moment we don't have a database actually so we're not calling anything static it's live it's happening in the moment in time and it's going through like an actual machine learning workflow so yeah okay So you don't have a database.

That's a gist. So, you don't have a database.
That's right. If I'm, wherever I am, a carrier, someplace else, some other tool that's using Relativity 6.
I know. It's hard to say.
Sorry. Yeah.
No, no, it is. You got to like, it's got to be like R6 or something.
I know. We call it R6.
I can't even spell it half the time. All right, I'm gonna say R6 from now on so I don't have to keep butchering that word with my stupid Irish mouth.
No, no, no, not at all. So you are not pulling.
So when I type in a company, I start typing in a company and I get to address and I've seen it as quick as like I have the basics of the address and whack. It's already pulled back.
That's actually happening behind the scenes in real time. That's not pinging a database.
That's really interesting. So, OK, so because my next question when you're answering when you're talking was like, how often are you refreshing the database with that information? And what you're saying is this is a real time function.
If I'm using your, we'll just say widget somewhere, your technology plugged into some company that that's actually happening as you're typing. It's taking that data, pushing it out and pulling back what they're finding in real time.
Wow. That is every single time.
That's pretty incredible. I appreciate it.
Yeah. It's just different, right? Like there's nothing, you know, I'm not here to disparage those other ways to do it.
This is just a different look. This is what happens when a human does it.
They're just a human can't go over one or two pages of Google without losing their minds. It's a lot of data.
We're doing hundreds of pages in that moment in time, grabbing that same amount of content and then displaying it. So, you know, just trying to make the job, like their jobs easier really helps with, you know, what they call premium leakage, right? Where, you know, a lot of the misclassification piece is a big part of that just makes things run smoother.
And again, it doesn't take away 100% of the work. percent of the work.
It just takes away a lot of it. So the underwriters can focus on what they need to focus on and not this kind of stuff.
So, yeah, I mean this classification, I mean, for any agent who's listening, I'm sure you've had, especially if you work in commercial, you've had a classification battle with an underwriter and it's brutal because they'll be looking at one website and you're, you know, and you're going, but, but this isn't what they do anymore. Look over here.
Look, I have seven, seven pages of pictures on Facebook of them not doing that thing that you're saying they do because on the seventh page of their website, back in 2014, they put that they might do that thing, but they don't really do it

anymore. And here's all this examples of not to.
And like that battle is unbelievably difficult. And you're like, and in my mind, I think a lot, this is another reason why I appreciate what you built is that I'm always thinking in how many brain cycles does it take to finish this task? That's just like, not that I have necessarily a meter going, but like not so much time, but like how much thought, how cranked up do I have to get my brain going to solve this task? Because if I'm battling with an underwriter for a half hour, the rest of my day might be hosed.
Because I just took all the energy and brain power that I had for that day and spent it on this battle over something as silly as NACE code or the word roofing was one place on the contract, you know, one place and one line on their website. And now they think they're roofers.
And it's like, that battle is exhausting. And if you can just get rid of that battle, you're just like, look, we're going to abide by whatever these guys say, because we trust this technology and bam, if you say they're a roofer, they're a roofer.
But if they say they're not a roofer, I'm not accepting that they're not. And just limit it.
You've, you've saved time. You've saved energy.
You've saved thought process. Like that's a huge part of our game.
There's just bigger things to think about than something as simple as what classification a business is, but it is incredibly important at the same time. Yep.
It's not in you know what, like, if someone told me that this is what I'd be doing now, like five years ago, I say you're crazy. Because why wouldn't you know that a roofer is a roofer and a carpenter is a carpenter, but it's actually, it's nuanced, like it can, it's not that easy, I guess, like, it's not, it's not an obvious thing.
So why not have a

little piece of technology to help you make that assessment? Again, like it doesn't have to be

the end all be all, but it'll give you a lot of data really quickly in our opinion on it. So you don't have to spend that, those brain cycles that you mentioned.
Now you guys didn't start doing this kind of, can you give us some of the background and how you got to this being, you know, and I'm, uh, uh, I'll operate under the assumption there may be more to come from you, but this, this tool today, how did you get to this place? What was the evolution that took you to get here? For sure. I was a, I was a fresh faced, uh, entrepreneur when I started this back in, uh, 2016 actually.
So, uh, it's a, it's like a cliche startup story. I started with my co-founder in grad school.
We were nerding out on actually lifetime value. So like predicting the future value of a company.
I'd worked at a lot of different companies where that was BS. Like, you know, they'd always ask you to do that.
And it's like, why? Based on what? Like what they spent the last year or two years years that's not really indicative really of much um so the whole concept was could we bring context to the table and make it make more sense which is why we call ourselves relativity which is obviously hard to say and spell but um we thought that was like a really interesting thesis so we ended up writing a whole research thesis pulled in a lot of of professors, got that going. The concept was, could you bring like modern advanced machine learning, bring all this external data about a company on top of their internal data and start being more accurate about what they're going to spend next month, stuff like that.
That was really the crux of the tech. And one little tiny piece of that was, wouldn't it be interesting to know what the company does from a contextual perspective? That could be something.
And we're not from insurance. So, like, we didn't think anything of it other than within the context of that lifetime value platform.
But we were grad students. We couldn't afford those large database providers and, like, what you would need to actually train a model on that.
So we kind of did it ourselves. It was really homegrown and it worked really well.
So we plugged it into this platform. And so we were out there for years selling this broader lifetime value platform across all, like literally our first customer ever was an aircraft manufacturer.
So I'm talking about like, you know, retail, like all these different types of companies. And then insurance

was like raising their hand saying, Hey, we care about LTV a lot. Can you start working with us?

So kind of naturally we started working with a bunch of carriers, brokers, wholesalers,

that kind of a thing. And that was the moment of like, wow, like they're not very good at

classifying businesses. Like we had no idea.
And, you know, long story short, during the pandemic, you know, we had to do a lot of soul searching of like, what are we, what are we really doing? And I'd be happy to get into why that LTV business didn't make much sense, like ultimately to scale, but made the decision like to go all in on classification because we, by that point realized we had something pretty unique uh not knowing that we did because we didn't come from the space we know all the players in the industry we really didn't know the value of it so once we really did we kind of just pivoted as they say um tech companies like to say and we went for it so um and that was probably like two years So still kind of newer on this, but it's tech that we've always had. We just never owned it and focused on it like we do now.
So why didn't the lifetime value tool work exactly the way you wanted it to? Yeah. I mean, like the output was good actually, but to get to the input was a super grind because you basically had to get monthly transaction data from large enterprises, including large carriers.
And that was really hard to do on a monthly basis. Also, the data that we would get in was really dirty.
And we had to actually spend a lot of actual hours of people's time cleaning it to the point where we couldn't make it profitable we'd we'd spend more money cleaning than we could ever make like actually outputting a prediction so that didn't make much sense and then ultimately honestly what was super interesting is um the output of our tech then was propensity to purchase more stuff, propensity to be retained, all that. The truth of the matter is a lot of the brokers and honestly, like the carriers and stuff, they didn't give us credit.
So it was like, oh, I knew that person was going to turn anyway. So like, thanks for nothing.
Or like, of course, I know that that customer is going to buy more. Like, I didn't need you for that.
So attribution became an actual battle.

And at that point, it's like, you know, we can't, this isn't working.

Yeah.

So that's why, like, and then we were like, man, like this one thing we built was super, super cool.

And we're starting to realize its value.

And, you know, it was hard, though.

Like, we'd spent years building that other thing.

And we literally scrapped it.

And we just went all in on this. So it was hard, but super paid off.
Definitely was the right call. So the technology that you've built around scraping search results pages and analyzing that and the keyword stuff, are you considering other applications for that as much as you can talk about it? Yeah, no, for sure.
I think like one thing we're working on now, it's really interesting is like address only. So as you think about like a lesser's risk and trying to understand like what's been going on in that building, you know, for the last 10 years, like what's going on with it now and what maybe the history of that building through web search like we're working on that like that's that's something we're excited about i mean we're we're doing more stuff around like detecting like the primary website as well like are we sure that which is hard actually in small business so like is this local coffee shop is this actually their primary domain or not so we're doing like a whole algorithm around that on the the keyword side, what's super cool is right now we're, we're doing like observable stuff.
Like, okay, this is a coffee shop. Here's all the things that we think that they do from a keyword perspective, but we're adding flags so that you can actually say, Hey, like if the word cannabis shows up, make sure like anywhere related to this business, make sure that we know about it.
Stuff like that. That's interesting.
Yeah. I'd say like, that's kind of like what's happening behind the scenes today.
Um, but honestly, dude, like, I don't think we're going to go well at like outside of what we're doing now. It's a really hard problem.
Uh, technically we like the idea of kind of focusing on one thing and being the best that we can at it. Yep.
Um, the simplicity and the focus from a, like a business strategy perspective is, is great. Um, cause I always know what like the KPI is like, what are we really trying to do better? Trying to be more accurate, faster, just easier to use and just like keep beating that drum.
So that like, if you're, I've done this before in other businesses where I've spread, you know, we spread out way too thin and weren't great at anything. And it's like, it's a bad feeling.
So. Do you have an internal accuracy score that you keep for the quality of the results that you return? Yeah.
So there's a thousand ish six digit NAICS codes. We have an accuracy score for every single one of them.
And it's constantly evolving actually. Like the secret sauce here is really good training data.
Um, it sounds simple, but it's honestly like just the truth about this, like AI type technology. It's really like, there's a core truth that if you feed it good training data you're going to get a good output yeah it's actually really hard to get good training data um you can't buy it so we actually have to create it from scratch so is it all just agent or user yes knows this seems to accurately describe this doesn't or how do you how do you train it no, that's definitely the way that's like the reinforcement learning side where like in production, they'll give us feedback and we'll tweak.
But it's literally people at our company constantly finding good examples of roofers and carpenters and electricians and this and that and feeding that into the platform.'s what it really needs to succeed gotcha actually so you're finding so finding examples of say a roofer who you know is a roofer they're a roofer here's here's here's exactly what a roofer is letting the system do its thing and then seeing what the output is and if the output matches and then you can. Ah, interesting.

Yeah.

What has been when someone.

I mean, why would someone push back against using what you're doing? What would be, do they like versus having a catalog of data pulls from say LLC formation data, which is where a lot of these come from, right? I mean, that's a big source of where they come from, which could be 10 years old, 12 years old. I mean, obviously I, when I formed my LLC, I did it through, uh, thankfully I have now reinforced a few of the pieces, but at the time it was just a legal Zoom LLC that I paid $400 for, right?

And you're just checking buttons as fast as you can to get through it, to get your documents.

So like why, you know, to me, there's a fairly obvious advantage to what you're doing.

What might be like some pushback that someone would give you?

What would be a, hey, yeah, we're not really sure because of this. Like what, what would that be? Yeah.
Like, honestly, there are limitations to the tech. I'd say one is if it's a holding company, then we're probably not going to find it.
Like the dependent variable for this thing to work is a digital footprint of some sort. So I actually don't think it's a bad idea to use us and one of these, you know, data providers that are pulling those LLCs, because then you're going to get the full picture, right? Like what if, what if we're, we're missing something on the, like, there's no website, there's nothing related to that company online.
That's, that's going to be an issue. So I'd say like that, that's why you should, like they say, waterfall this, like use us and one of those.
And now you've really completed the picture and solve the full problem. Why wouldn't you eventually just bring that type of like the, make the waterfall part of your product? Who says we're not right.
But yeah, like eventually, like, you know, know we're trying to add value and solve the problem so you know i think that that's a good path forward for sure yeah yeah that's awesome so okay so um that's very cool um not necessarily something that an agent would reach out to you to purchase but our carriers our mgas anyone like, who's listening, any of our lead providers, any of our, uh, um, scaled, um, it really, any, anyone who's scaling and needs to know industry quickly underwriters, uh, maybe even claims platforms. Um, so anything like that, uh, you would be a great fit for them.
Um, so if they, uh, relativity six.com, check it out, whatever. Cause I want to start talking about some industry.
I want to talk about some industry stuff. Um, and, and we'll, we'll hit that again.
Um, so, so when you look out over the industry, kind of now stepping back from, from our six and just looking at the industry in general as entrepreneur, been in the business for a few years, four or five years now, it sounded like just kind of dissecting that, but still kind of probably feel a little bit of an outsider to the insurance industry. When you start to look at the insurance space like what are some of the places where you see like really interesting things happening? Everyone tends to talk about the places that aren't working in our space, which, you know, I think that's almost like, you know, punching down.
What are some of the things that you see us, that you see our industry actually moving on that seem to be taking shape or taking hold? And, you know, maybe not necessarily compared to other spaces, but things that you see us doing well, entrepreneurs who you see kind of tackling problems in the right way. Yeah, no, for sure.
And when I started dipping into insurance, there were way less, I guess, of us. And by us, I mean, like outsiders, usually, usually when you're solving a deep enterprise problem, you probably come from the industry and you've like identified the problem in your job.
And you're like, Oh, why don't I start a company to solve this? But and that's how it was, I'd say five years ago, but like, because there weren't that many, like, I guess, like insure tech companies, it was like, Guidewire was considered an insure tech and then there's like kind of a blank space and then first wave and then I feel like we're in the second or third now but I have a lot more friends that had nothing to do with insurance finally like looking inward here and I think there's a lot of a lot of reasons why one I, I think stating the obvious, it's the industry is doing really well, right? The world is hurting, but I think at a high level, insurance is still clicking and not really skipping a beat, which is awesome and has been the case. So that's that.
Two, there's so many problems to solve. There's so many problems to solve and we don't have to get into that too much.
But the point is that there's a lot of great applications for technology that can slot in. There's a lot of data, right? It's scale.
Scale is something that is a dream for like a tech entrepreneur. And by scale, I mean, you know, the volume of people, but also like impacted, but also the volume of data available to do stuff.
So that's awesome. And yeah, I mean, I think like, like I said, like at a high level, it's, it's kind of open for business, like carriers are, you know, so I, like you said, I deal with carriers, carriers mgas wholesalers mainly some brokers some larger brokers um which i so i'd like to kind of like not counter your point but i think brokers could use this in some ways but like the whole i just don't want to give them any ideas because i have all the ideas that i don't want anyone else no i'm kidding yeah um but no, there's, there's a lot of openness and willingness where I think before there wasn't even from like a data privacy security kind of thing, like cloud is now it's kind of taken for granted, but like five years ago, it wasn't like you could say, Oh, I'm an AWS.
And they'd be like, cool. It was like, no, like, where's all this stuff now that if you're telling me you're in the cloud, I don't trust.
But that's changed totally. So I think it's just like, it's wide open for business.
It's kind of intimidating. Like, you know, again, like I don't come from this space.
And I was like, whoa, insurance seems complicated, which it is. Like, there's a lot of interesting ins and outs of how the ecosystem works.
But if you can figure it out and really understand where the value is at each point of the supply chain, there's so much opportunity to untap that, you know, like, come on in, like water is warm. Basically, it's like a good time.
Yeah, it's interesting. The talk about the different waves of say insured tech.
So 2015, 2016, I was at Trusted Choice. We just launched a nation and a big, a big part of that was a big part of the agency nation platform that we, that, that we built was about sorting through the new, this new insure tech revolution as it was initially built and all the disintermediation that was supposed to happen.
And I will very biasly say, I'm glad that most of those a-holes got dashed along the rocks, just mostly for the way they approach the industry. What I love about where we are now, and whether it's the 2.0, 3.0 version of insure tech is that where that first group came in, insider or outsider, very much.
We know better. You're all old, dumb idiots who move way too slow.
Don't know what's happening. Get out of our way.
Let us fix all your problems. Today, it is such a different conversation when you talk to entrepreneurs, even entrepreneurs who've come into the industry like yourself, who had no prior interest or experience in the insurance industry.
It's so much more, how do we work together? How do we find some sort of synchronous relationship? You know, how do we be a net value add to you? What are your problems? Let us help you solve them. And just across the board, the conversations are so much more productive.
And what ends up happening from that is you get this, you get a symbiotic relationship. You get a relationship where the tools are working together and even, you know, we'll, we'll bring Coterie up again.
Right. So Coterie is an agent

focused carrier. They also have a direct arm, you know, 2015, 2016, they come in, they launched that direct arm the way they did.
Um, they most likely at, with the, with the culture of that moment launch, we're going gonna change the game you know but they didn't do that as coming in and kind of wave two or three whatever we're in they they've they've been very agent focused very friendly agents in you know and i'm a fan so that so this is no way to knock on them um but at the same time they do have a direct and people don't seem to care. And I think that's much more the way it should be where, you know, everyone's got a business.
Everyone has to attack the opportunities they see. I personally think that them starting their own internal agency is a mistake.
And I've told them that. And I'm perfectly willing to say that in public.
But it's OK that they do that. They need to learn their lessons.
They need to learn

how to be successful. And, and, and what we found is that tech non-tech or non-insurance

tech entrepreneurs can work hand in hand with very wonky insurance professionals and be very

successful. And that is one of the most exciting things to me about this moment, because what it

does is it provides opportunity for someone like yourself to come in and provide a tool that, I mean, you're addressing a problem that I don't know anyone inside the industry would have seen. And addressing it in a way that certainly I had never heard of before, but is obviously making an impact.
So that's a tremendous thing. What's up guys? Sorry to take you away from the episode, but as you know, we do not run ads on this show in an exchange for that.
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Yeah. Coterie has been a, an awesome partner and I agree.
I think they, they think about automation and technology, but they also think about the, like very deeply think about the broker experience and that's actually a big, big piece of how they design stuff. And they've been, they've been a huge partner for us.
Yeah. Yeah.
I love it. I, you one of the things you talk about, brokers could use your tool as well.
And I completely agree. The number one problem that we have yet to solve at Rogue, I would say for most of the problems that we have to address at Rogue, we at least know what the solution is.
We may not have built it, implemented it, or have it where we want it to be, but we at least we have a whiteboarded concept that is fairly close to what the solution will be mapped out or currently in process and testing. Awesome.
The one thing we don't, and it is probably our largest roadblock, and every time you i don't know if your ears ring but every time i talk about this problem i reference you guys so hopefully you take that as a comment i'm blushing yeah um is is where does the business go this when you when you if you are old school one policy at a one account at a time, this is not an issue for you. But as soon as you try to scale, where does the business go becomes a major, major roadblock.
So just to give everyone context, and then I kind of would love your thoughts around this is what ends up happening is P companies that scale end up finding one, two, three, maybe five max partners because that the reason is not because that's all the partners they can get. The reason is because they can't manage the appetite of more than three to five partners.
As a human, I honestly think I give absolutely no legitimate data to back this up. This is just watching my team and myself.
I don't know that we as humans can understand and regurgitate the appetite for more than three to five carriers. I think that's about all we can have individually.
So let's say you're a national digital broker. You're getting accounts from every different state in all different markets, and you're getting them 12 to 15 times a day.
Where the hell does the business go? Where does it go? Because Hartford could be an amazing partner for a certain type of account in Minnesota and just be way off in Iowa. And, and, you know, they have the reasons that I'm not knocking them, you know, I mean, and again, this is an example, but like how the, the, the person who gets the business goes, well, geez, I just wrote the same exact account in Minnesota.
So I'm going to go right to Hartford. And then you look at it and you're like, oh shit, they don't even write it there.
Now you're backed out or you're going to Tarmaca and you're going through the thing with Tarmaca. Tarmaca helps a lot, but it doesn't solve every problem.
And there's all this mishmash of where does it go? Who's going to have the best price? Who has the best coverage? How as a leadership team do you set a series of levers which allows you to sculpt the business to a certain extent to the carriers that you want for whatever reason you want that business to be written? There is no tool in the market that does that. And to me, the starting piece to all of it is an accurate industry class code.
If you do not have an industry, accurate industry class code, you cannot move forward with that process because it just, it defines, it is the first, in my opinion, maybe, maybe zip code, maybe industry class. It's either one or the other is the starting point for this.
And if you don't have those two things, right. And you don't, you cannot, you cannot get to the next steps and you waste so much time.
So, you know, thinking about that problem, you know, have you seen anyone solve that, that, that, that obviously that you're capable of talking about what, where do you see that problem falling? Like what, what kind of ideas you have about that? I'm trying to get some free consulting out of you right now. You got it.
Yeah, no, a hundred percent. I mean, it's really interesting hearing it from a, like a broker agency perspective, because I usually, you know, I'm talking to carriers more, so I'm hearing it from their end.
So it's nice to hear from your end as well. I'd say, uh, I don't have a magic bullet, but I think.
So again, like this is everything you said is awesome. And exactly why it's I was like, I know I don't I don't show many emotions on my face, but I'm smiling.
You have that gorgeous beard. That's the problem.
Yeah. The man makeup.
Yeah. But yeah, like I'm thrilled that you're saying all these things and it just validates why we're working so hard on solving this one problem.
Cause it's just that important and that inaccurate today. So super validating there.
I'd say like, you know, we love, you know, ask Kodiak obviously, and in what they do. And, you know, we have a partnership with them for this exact reason, because, you know, we do what they do is amazing.
And what we do helps with what they like in what they do, right, make them more efficient. So I think it's got to be a tech solution to your point of like the human brain.
And I'm buying what you're saying. So, you know, who knows that you have anecdotal evidence, which is, which is science.
But like, yeah, like a human can't possibly comprehend all of those variables at the same time. So you do need technology to start pointing you in the right direction.
And I think that's the point is tech is never going to replace anything or solve that fully. But if it can at least point you in the right spot, so you don't have to waste all those brain cycles that you mentioned, starting from scratch all the time.
If you can get

50% of the way there, then I think we've done our jobs as a tech provider. I will never say that Relativity Six or any other type of company is fully solving any kind of...
That's like a crazy, not real thing to say. And I don't ever see that being the case.
But it's like this whole, you know, human machine working together deal. That sounds crazy.
But this is a good example of that, right? Even in our technology, it's like, we're good, we'll get you a lot of the data that you need. But you should still look at it and like double check as a broker, someone that's connected to the account, before you ship it off 100%.
Like, we're not here to replace the way human thinks. We're just trying to automate the process that could take you forever to do and help you do that better and incrementally improve.
So yeah, I don't know if that actually answered your question. No, it does.
Yeah. It does.
You know, the way that I was trying to describe, someone asked me like,

can you describe this thing? Cause this is like my someday I'm going to find someone who knows how to code, who will help me skunk works, this thing hint, hint to anyone out there that's looking for something to do, um, that will help me skunk works this project. Um, because it's such a huge issue for us.
Um, and I just, I'm not a tech guy. I'm a user guy.
So I need, you know, it's, I, I've, it's relativity six meets Tarmica meets ask Kodak meets Aureus analytics. Like that is essentially what I'm, what I have in my mind.
Like, and maybe it's just a platform that sits underneath those four tools. Really? I mean, that's probably more of what it is because what you need at the front, what is the industry? The industry tells you what carriers to go to.
That allows you to drastically reduce the amount of time, energy, brain cycles spent picking carriers, right? Your people aren't going because also that immediately allows you to go in Pennsylvania. That's ENS and our ENS provider that we use for this class of businesses, RT specialty or, or excess or whoever, you know, excess brokers, BTIS, whoever we go to.
And so now you're, you're immediately getting to the spot. Then you're pushing that through or so it's relativity six, ask Kodiak, Tarmica.
And then the Arias part, again, I'm just using these four companies that I like, but you know, put piecing together. The Arias part is then who do you actually bind it with? Right.
So, okay. So it said, so I got the industry from relativity six as Kodiak told me Hartford was number one, Chubb was number two and Liberty was number three.
Even though they ranked them one, two, three in that order, after going through Tarmica and actually placing the business, we placed it with Liberty who was number three. So now at the end, Ari has put the check marks in, showed these three.
Liberty was actually the winner. And now in the algorithm, Liberty might over time, if that result continues to happen, be bumped up to number two or actually number one.
So we have actual appetite, but we all know carriers when they talk about appetite, bending the truth is as nice a way as I'm willing to say. Or maybe are just naive to what they put out in marketing materials versus what they actually are willing to underwrite.
So you have what the industry actually is, what the carriers have said their appetite is, actual results returned and then re-algorithmized to recapture. So essentially what you're eventually getting is a hybrid between the Ask Kodiak, here's what the carriers say they'll write, and what results you're actually getting.
And that allows you to get closer and closer and closer and closer to the answer over time. And in a high volume shop, where now you might be talking about hundreds, thousands of quotes, now that whatever in Iowa, you don't go to Hartford, you immediately go to Liberty because you know not just that they'll write it, but that consistently over time, they've shown that they write it in that state with the most competitive pricing.
And as a company, we're okay with their coverage form. So now you're just one carrier quoting all the time.
One carrier quoting all the time over a broader carrier set. And that to me is the holy grail for scaling retail commercial lines, especially in small commercial.
No one has built that yet. And if anyone wants to build it in conjunction with me and give me equity, I am okay with that.
I mean, I don't know why you didn't call yourself a technologist. That was, that was great.
And I love the word, we algorithmize or whatever that was beautiful. Please steal that and use it.
Do not have to give attribution.

I just want to hear someone use it some other time and go, it worked. Yeah.
Yeah. Well done.
But yeah, no, that's, that's well said. It's not crazy is what you just said.
That's not a crazy

idea. That's not crazy.
All right. That makes a lot of sense.
Yeah. Yeah.
You just, you just

created a billion dollar company. Congratulations.
Yeah. Well, unfortunately, I have zero IP on it, can't code, and just set it on a public podcast.
So I'm kind of for turning it into it. I'm sure someone smarter than me and with fingers that know how to make things happen on a computer will make that before me.
We'll call it it the handling. Yeah.
Yeah. I'll be your first customer.
Yeah. Um, so you know what, um, where in general, uh, you know, again, this doesn't just have to be about your business, just from talking to other entrepreneurs, looking out over the industry, like where do you see, um, where do you see opportunity?

Where is there some untapped opportunity or space? You know, you talked a little bit about data. Data to me, there's like, data is such a weird thing.
Part of me, when I hear data, I get aroused. I'm like, oh, fucking data.
That sounds amazing. All right, let's do it.
And then I ultimately have no idea what that actually means in terms of what's useful, what's not, you know, I get lost in

that concept. So what do you, when you look out over the industry, where are you like, you know,

if I wasn't doing this, I'd be super into this thing over here.

Yeah. No, I mean, yeah, look, uh, you're giving data that, uh, I was going to say,

I'm sorry. super into this thing over here yeah no i mean yeah look uh you're giving data that uh i was gonna say a bad name but you're not it makes sense there's so much of that available but i guess what i've realized in insurance again not from the space but that information if used correctly is the strategic advantage i think yeah at least on the carrier I mean, for brokers too, right? Like you have all these broker platforms that are now arming people with better information about their client base to go out and take action.
So it's not that like data is bad or good or whatever. It's like, what's the problem you're trying to solve? And how much information can you gather about that problem to solve it? So I like, I personally love this space of like trying to, in my case, and this is biased, but create original data points, not like resell others and package it together, which there's a business for that and I'm not disparaging at all.
And there's a lot of value there, but I like the idea of like trying to find something original and then bring that to the table here's here's my opinion on this problem that you're trying to solve and that's what we're doing with with classification right obviously but there's a million other data points that need to be discovered to do that i like also in general like if your question's good of like what else would i do uh i actually love what coterie is doing. I mean, not to make this a Coterie centric odd, but why not? A lot of friends at Coterie, it's all good.
Yeah, they're great. They're really smart.
I think they're really thoughtful. And I like how they've architected things.
I like that they think about things from an automation perspective, but not fully, you know, like they're, it's a good balance. And I think the point of it is to let the humans do what humans should be doing and not what they shouldn't be doing, I guess is like the best way I can put that.
You should build a human optimized agency is what I hear you saying. I think so.
I think so. I think, I mean, look, this came up a lot in the conference we were at, like agents and brokers, they're not going anywhere.
Like they are so valuable to this process, but can we arm them with more stuff to be able to have them do their jobs more efficiently? Why not? Like, I don't like what's wrong with that. But it's again, it's back to the point of like it's not one or the other it's both it's like but how can the two like dance together to make it work versus like competing that's not the way yeah i think i agree i think also there are a lot of bad decisions around tech made in our industry because um because is the wrong word, as a result of considering agents that don't want to grow.
So there, you know, if I, if I were working at a carrier today and I was tasked with understanding where do we want to spend our time, resources, energy, right? Obviously you always have to maintain your current plant and continue to do what you've done. But what I see a lot of carriers do a lot of, unfortunately, a lot of legacy tech platforms.
This is a, not a concept that culturally seems to be intrinsic to more of the insured techs, but legacy technology companies is they, they look out over their agency plant and they value the opinion of every agent exactly the same. And not that anyone's opinion is wrong.
I don't mean that. But there is a substantial portion of the agent population that has no intention of growing regardless of what they say.
They're perfectly content with where they are. And God freaking bless them for being in that position.
There's nothing wrong with this. This is not a knock on them, but that mentality is not going to push us into the future or sustain us into the future.
That is the mentality of a human or a group of humans who've done an incredible amount of work and gotten their business to a place where now they don't want to put more stress on themselves or whatever. And I, I am relishing the day that although understanding my personality, I'll probably never be content.
But, but I, hopefully there is a day when I feel that way, right? When I'm like, we're good, we're making plenty of money. It's all good.
We just want to kind of keep carrying on. But that, but I see a lot of carriers will say, well, our agents aren't really asking for that.
And I'm like, OK, what about the agents that are growing? How about you cut all the agents out who aren't growing and just talk about the agents that are growing? What are they asking for? Because I bet that although a much smaller segment of your overall population, I bet they're asking for very similar things and they're not the things that any of the other agents are asking for. And that is, that is, that is how I would cross cut them out because that the, there are decisions like, I, I mean, this is, this is crazy, but like, and it has changed in the last year, but there was a carrier 24 months ago that I couldn't do business with because I use a Mac.
No way. Oh yeah.
And I said to them, um, guys, I'm not getting a windows computer, not doing it. You know what I mean? Like I just refuse.
I'm not using shitty virus ridden fucking technology that doesn't work half the time that I have to update every seven days when I could have a Mac and it just works all the time. Yeah.
You know, why would I do that? So they're like, well, you know, you can VPN into this hard. And I'm like, they're like, you know, our agents aren't asking for it.
I'm like, I bet if you went out and you looked at your growth-focused agencies, I bet many of them have users who love Macs and are using Macs. Now this is a microcosm.
So I'm just, you know, I'm not trying to make this like a big deal. But that idea of, of course, your agency that's still using big box desktop computers, that agency, of course, they're not asking about it.
But they're also most likely not the agency that's just throwing business on the books and growing and pushing and going to be the future. So it's a really interesting, there's just so much opportunity in our space.
It just gets me all fired up. There's a lot.
Like literally, I think you've come up with $4 billion businesses in the last 20 minutes. So, yeah.

That's definitely not true. But no, no, I think it's interesting.
You know, and you answer this, don't answer it if you don't know or aren't interested. But like, I think one of the places, this is not about cryptocurrency, but the technology of blockchain, I see, I'm not 100%.
I have some ideas around the application to insurance. But in general, that tech to me, again, taking cryptocurrencies out of that, talking about that, I'm talking about the actual tech of having this distributed ledger that allows us to have a single point agreed upon, you know, kind of discernible truth.
Do you see application in the insurance industry one and two, what would be a use case, you know, if you're comfortable answering this and have thought about it that, that that you think could actually be implemented honestly i don't know um i've thought about it i think there's a lot of value like you said to the ledger and smart contracts and you know kind of tracking what where everything is um why not have like a like a real like system of truth to that like there's a lot of value inherently in that i'm not smart enough from like an insurance understanding perspective to know where that like like i could give you wild guesses but i don't know where that legitimately slots in to a workflow or makes the most sense today for the way that insurance is consumed today i guess like you know maybe like know, maybe like a future insurance product, but not the second. Do you have one? Well, it actually isn't, it's insurance industry related, but not.
I think a really, you got, no one can see me, I'm doing air codes. Easy first pass at this would actually actually be licensing a universal ledger of truth for licensing that is pinged on by all the carriers, right? I mean, a very one simple machine in every, in every carrier or every agency or whatever, a few different, you know, every state insurance department, what have you, right.
Could, could, could know the absolute truth for who is licensed and who isn't licensed in which states at all times at any given moment. And then at any time, if a carrier wanted to appoint somebody, they would ping that single ledger of truth and know enforced license, not enforced license, and for which states at any given moment.
And, you know, that to me, you know, you could even, again, if you wanted to, if you did want to go with a type of currency would be if you held a machine or if you were part of the, a node in the, in the database or, you know, whatever, there's different types of staking or whatever, but you could actually like, let's say Rogue Risk was one of the entities who was keeping the ledger going, right? Yep. Well, that would award us just the ability to maybe pay for licensing, right? So it gave us some sort of currency back, which we then could only use to pay for our licensing.
So there was an advantage to us to maintaining the database overall for the ecosystem of agents that wasn't a currency that had value out in the real world. It just was redeemable for credits to keep my people licensed, which gave me a benefit to keep the database up to date for the entire ecosystem of agents.
I thought of something like that and I was like, that would be a really interesting first use case in our industry that would not impact all the craziness of underwriting, which I get why this technology and underwriting would scare the shit out of people. We're not nearly there yet, but like this would be something that we all could start to use as an industry that could be really interesting.
So I like that. It's a closed, closed system.
That's cool. That's really interesting.
Yeah. Fifth business started.
You can't help yourself. Can't help my, I don't know what it is today.
I just, it's that fucking beard. It's so goddamn sexy.
I just want to, I just want you to love me and think that I'm smart and all this stuff. I can't help myself.
I'm validating you right now. Yes, you are.
Or the beard is dude. Um, I want to be respectful of your time.
I appreciate you. I appreciate you coming on here and let me somehow this turned into me peppering you with ideas.
I don't know why I've been writing them down. I got the receipt, but I, uh, I'm a huge fan of what you're doing.
Um, I really wanted to just chat with you and then ultimately get what you're doing for as much as this show can, and our audience can get what you're doing out in front of everyone, because, um, the few instances in which I've used, um, uh, a tool that, that is pinging off your, your system. I've been incredibly impressed.
I've told as many people as I can that I think Coterie's Industry Finder,

powered by you guys, is absolutely one of the best in the industry.

And I just wish you nothing but success, man.

It means the world.

Thank you, Ryan.

Yeah.

All right.

We're out of here.

All right.

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