The Exchanges

Q And who, and who's we? Give some people some perspective on what you're building there.

A Yeah. So, effectively, Assemble is owned by a venture equity fund, uh, by the name of Scaleworks. Um, they're a San Antonio based. I mean, their, their tenant is that, Venture equity, uh, venture capital rather, uh, works very well for, for, for businesses that are looking to give away a small amount of their equity, um, and drive growth. Private equity works very well for larger businesses that are looking for an exit. Um, private equity will come in. They'll take, uh, they'll take dividends and distributions out of those businesses, but there exists nothing in the middle. So you've got a business that's doing, say, you know, three to ten million. Private equity aren't interested in them, in that they're too small. Venture, venture capital aren't interested in them, in that, you know, if they're 10 years old, if they haven't hockey sticks yet, they're not gonna. Um, so where do they go? Um, so we buy businesses that are product focused, and, uh, we then, we, we turn on our sales and marketing engines, and we drive both.

AI assessment note: “Assemble is owned by a venture equity fund, uh, by the name of Scaleworks.”

Q You're my kind of guy. Okay. So what's the company do and is it a pure play SaaS model?

A It is a pure play SaaS model. So movable Inc. exists in a world where we work with lots of big consumer brands that have harvested a huge amount of data. They really understand their customers. There's APIs, data, CSV files. They manage all of this. What they struggle with is taking all this great data and translating that into compelling visual experiences. That's where movable Inc. comes in. We have a SaaS platform. Uh, it is completely on the cloud. There there's no on premise and any marketer will log into our system, be able to configure a piece of intelligent creative that they can embed into their email marketing. And so when that email opens up, uh, our code fires and we're able to generate the perfect visually compelling content at that moment of open.

AI assessment note: “It is a pure play SaaS model. So movable Inc. exists in a world”

Q start off with that, you know, a pricing plan that might be less than 30 bucks a month, they then drive growth by moving towards more expansion revenue, more variable pricing axes. Is it typical, and do you see in your data set, a time period where logo churn could be 30% annually, but revenue churn is five percent as pricing increases and expansion revenue machine really gets dialed in?

A Yes. So that, that can definitely happen, but to me, it's a bad sign. Um, any logo churn number that's greater than 20% per annum is worrying, and it's evidence that you don't have good product market fit in one of your customer segments. So what I would do there is I would recommend every startup look at the segments in their customer base and split them and start doing the metrics by different segments. So for example, you might have large customers, medium customers, and small customers as your segments, or you might have Some industry specific thing about them. Like you might have high tech as, as one segment and, um, healthcare is maybe a different segment. If you've got high churn, what you want to be trying to do is understand why is there a difference between the people who are sticking with me and expanding and the group that are signing out? There must be something, some characteristic about them that makes the product not work. So one example of a company where I saw a big difference like this was conducted on a New York They had some customers that were expanding like crazy and love the product and some customers that were churning. And we found out that the real key was that it was the nature of the users. The users that were sticking with the product were pretty advanced users that really understood how to take a tool and apply a tool. Whereas the ones who were ch…

AI assessment note: “Yes. So that, that can definitely happen, but to me, it's a bad sign.”

Q How old was it at that point? When did the actual company launch?

A The company was founded in 2001, so it had been around quite a long time, and they've done, like, most small business, most, you know, startup software companies, got to four million in revenue, and then couldn't get past it, right, and it was just, like, stagnated at four million for, like, four years, and as a board, we said, hey, we got to do something completely different, and that's kind of when I stepped in. My background is I do a lot of acquisitions. I grow companies pretty quickly that way, so we very rapidly bought two companies. We bought the Act Product, and we bought SalesLogix from Sage, ah, over in the UK. Um, when we, when we bought the company, uh, it was, it was.

AI assessment note: “The company was founded in 2001, so it had been around quite a long time”

Q And then, so you're at 106 customers now. Let's say a bunch of sign up from the show. So you have 137. What, what, what actually happens right when I sign up and start paying you?

A So what happens is you sign up, sign up process takes about five minutes. You connect up to your marketing automation system, whether that be HubSpot or Marketo, which literally takes about a minute. Um, and then we start analyzing all of the historical data that you have within your marketing automation system or in your corporate email system. We then go through an analysis phase, depending on, you know, total number of email addresses that you have anywhere from, I think our smallest customer probably has 2000 email addresses. Our largest has around ten million email addresses. Um, and so depending on that, it can take anywhere from 24 to 48 hours to, to, uh, complete that initial analysis.

AI assessment note: “So what happens is you sign up, sign up process takes about five minutes.”

Q That's pretty healthy. That's pretty healthy. And what are you, what's the number one way, way that you're kind of pulling people out of the Vegas strip experience to your location?

A Uh, it's a three-legged stool, perhaps four. Uh, I'll tell you all four, but three really drive it. Um, direct to consumer over internet is a really big part of what we do. Uh, I, I like to think that we're quite good at digital marketing, and so that's a big area of investment for us. We're located on a major, uh, interstate corridor that sits between, uh, uh, Los Angeles and Las Vegas, so depending on the time of the year, 30 or 40% of the total visitors drive in, and so we have tremendous drive-by access. That's, uh, perhaps about a quarter of what we do. Another approximate quarter of what we do are large groups. So these could be everything from Rolls Royce doing a manufacturer, uh, new model rollout, uh, to, you know, pharmaceutical industry. They'll bring out a thousand people, uh, use the facilities. They're beautiful facilities and do a beautiful event. And then the remaining quarter is really chopped up, right? It's everything from social and email marketing, casino hosts and, uh, nightclubs and, you know, billboards and town, things like that.

AI assessment note: “direct to consumer over internet is a really big part of what we do.”

Q was putting together my LATCA 100, the fastest growing ZAS companies. And I said, I should touch base with Hank, see how vitamins doing. And you were back and said, actually it's dead. And I said, what you were doing, like 1.2 million in revenue back in, what was it during February, March, May, 2016. When I had you on, what the hell happened? So let's start there. What happened?

A Yeah, sure. So we had a really fast run. Uh, we found, uh, Uh, that what we were doing with automation on social was really helping drive web traffic for small businesses and early stage companies. A lot of likes, favorites, follows, retweets, comments, mostly on Twitter, but it could work on like Pinterest and Tumblr, but Twitter was really working well for us. And, you know, we're charging a thousand dollars a month for the service. Uh, we were bringing really high quality traffic to our clients and customers and, uh, the growth is really happening rapidly. Like you mentioned, we got to a little over a hundred K a month and, uh, and recurring revenue and, uh, May 29th, 2015. I believe it was, we lost all of our Twitter accounts that we were running. It was thousands.

AI assessment note: “we lost all of our Twitter accounts that we were running. It was thousands.”

Q Interesting. Okay. Give me more of the backstory here. So when did you launch the company?

A Yeah, so, you know, started working on the company in, uh, 2009, uh, and it was a small team of us, myself, my co-founder, Ashu, who had built a lot of the search engine at Google, and we pulled a team of people mostly out of Google. It was a group of five or six of us, and the original pitch was, we can build a platform that you can plug any website or app into, and it's gonna Immediately generate highly relevant experiences for consumers. Wouldn't that improve the consumer experience and drive more revenue for whoever's publishing the website or app? And if we could build that platform, it would serve everybody. So we spent about a year, year and a half kind of an R and D built a machine learning system around that basic problem, prove that it could work by kind of 2010 started to approach a set of clients and really only launched the company publicly in 2012. Uh, or maybe it was end of 2011, and that was when we sort of began to take it to market.

AI assessment note: “really only launched the company publicly in 2012. Uh, or maybe it was end”

Q So when I bring up off the top of my head some, some folks that I think about when I, when you give me that description, I think of Segment, Work Auto Elastic, Zapier, Snap Logic, Jitterbit kind of companies. What do you think when you hear those companies relative to what you do?

A Uh, so kind of Jitterbits and, and Zapiers or SnapLogic, those would be a little more into a category called integration platform as a service. So we're in kind of business process management or BPM or workflow. So workflow and BPM has an element, an overlap with the integration platform. So we do do integration, but a lot of times we'll see customers that already have an integration platform, which is good news for us because then it makes it easier to get the data we want in and out. And we're going to be much more of the kind of human powered forms that are getting routed around. So, uh, those kinds of companies won't do very well with the approval and, and rejection part of a workflow.

AI assessment note: “those would be a little more into a category called integration platform as a service”

Q Okay. Um, we'll jump more into that in a second, but I want to take a step back. Tell us about the product. What does data stacks do and what's the business model? Is it pure play SAS or is it pay as you go based off your usage?

A Yeah. So data stacks is a leader in data management for cloud applications, which we'll talk about, have a whole different kind of scale, um, and, and set of requirements for the database. Uh, the way we make money is we sell our, our flagship product, DataStax Enterprise, uh, on an annual subscription basis, and you can consume that either as a service, where we have a managed service that we'll do for you, or you can consume it where you manage it, and you may decide to run it in the cloud, or you may decide to run it on-prem, but we have about 60 to 70% of our workloads are, are already being run, uh, in the cloud, either with us managing it or our customers managing it.

AI assessment note: “we sell our, our flagship product, DataStax Enterprise, uh, on an annual subscription basis”

Q 11. Okay, good. So, I mean, it's healthy growth, especially considering bootstrapped. How are you getting more talent On your system, you went from my, what, 400 to five 50 or something like that?

A Yeah, we have about 500 contractors, um, with our team right now, and about 61 employees here in the Atlanta metro area. You know, when people do something that they love, they tell other people about it, so word of mouth continues to be our number one source of finding great talent. Now, we only bring on, um, about two percent of the resumes that we get, so we're Very selective in who we partner with because it has to check a lot of boxes. It has to make sense for the long term. So we actually have had very little outbound recruiting effort because the pool of resources who want to partner with Belay is so large, we can be very selective.

AI assessment note: “word of mouth continues to be our number one source of finding great talent”

Q Interesting. And are they, I mean, so how does this compare to other things on the market? I mean, we mentioned Nielsen a little bit in the, in the, in the intro. Do they not already do this?

A No. So Nielsen and Milward Brown and, uh, some of these other copy testing outfits are really pre-automation guys. And so, Our fundamental difference was on the technology and the normative data and all of the competitive assets. Um, Nielsen measures, uh, more on a recall basis. So what you watched, if you watched a show last night, they'll ask you questions about the show and they'll try to ask you questions about what ads you saw. And it's much more about, do I remember seeing it? Um, that's valuable for certain things, but for us that gets tangled up in where the ad's running and how much media waits behind it, not necessarily the creative itself. And so we wanted that pure form measure of the creative effect.

AI assessment note: “No. So Nielsen and Milward Brown and, uh, some of these other copy testing outfits”

Q Do you remember it? What was your, what were your monthly expenses? Do you mind sharing your monthly expenses personally back then? What would you keep them under?

A Oh, it was almost nothing. We were, um, we, when we lived in Boston, we shared an apartment with two other people and we were probably spending a total between the two of us of about a thousand dollars a month in rent. And, you know, we'd buy like frozen burgers from Costco and we'd eat those every night and ramen and you know, all that. And then when we moved out to Silicon Valley, we lived in kind of Southeast San Jose, and, you know, in a house that we rented for 2000 dollars a month, and we had three other roommates, and just really kept that burn rate as low as we could, um, because we were self-financing in the early days, and it just gives you options. It lets you stay alive for longer.

AI assessment note: “spending a total between the two of us of about a thousand dollars a month”

Q Going down that funding path. So up to us today, how much total capital has been infused?

A We raised fifty million at this point. So, so basically the trajectory was, um, it was the first 12,000 from Y Combinator. Then we raised 40,000 in angel money. Um, and then, and then at that point we got some tractions. We really quickly went to raise three and a half million from, uh, from red point and then another 10 from CRV and then another 10 from Silicon Valley Bank, and then another 25 from Coastal Ventures. Uh, I think that adds up to 50, but I got my math wrong. Um, so it's about 50 to date. Um, and at this point we're profitable, so we're just living off profits, uh, and, which is a, which is a good spot to be. We're not really intending to, to raise any more money for the time being.

AI assessment note: “We raised fifty million at this point.”

Q And what are you pricing that based off? Is it number of seats or the features they have turned on or what?

A Yeah. So it's interesting when we switched to, so traditionally we used to charge for block projects. And when we went to enterprise, uh, enterprise customers only want to deal with per seed prices. So we have to go per seed and we kind of plucked the number out of the air. We charged 10 dollars per user to start with. Today we're charging 25 dollars per user for a minimum enterprise price. And what we've just done last month is we've changed all our self-service, uh, pricing tiers to the per seed model. And the reason we've done that is for a couple of reasons. It's, um, First of all, we weren't capturing enough value from the mid market. The second thing is our customers were actually telling us that they, our potential customers were going to our competitors because they perceived our competitors as cheaper, even though they weren't. So we were, for example, selling our lowest package was 64 dollars a month for 10 projects and unlimited users, whereas our competitors were just advertising nine dollars per user. And to the layman, they were, they were interpreting that as our competitors.

AI assessment note: “enterprise customers only want to deal with per seed prices. So we have to go per seed”

Q So what was the first failure? You going door to door one on one classes?

A No, the first failure was a web app. And so it was back in, uh, 2004 and, uh, you couldn't email large files in 2004. Uh, you could email two meg files back then, which is, it feels like that's the cave ages. Like what? And, uh, so I built a web app called, um, flight deck and it allowed you to send large files and you would click to download. And I actually then, uh, I priced it way too high. It was like, it was like, 500 dollars a month. And it was meant for businesses. And I had, I had no clue what I was doing. I didn't know, oh, that means I need a sales force. Like, I, I, what am I doing? And, uh, I kept getting no's and no's and no's. And I got, I think it was 800 dollars in recurring monthly revenue before I flatlined and I realized, This is either, either I need to change the whole thing and raise some money and get serious, or I need to move on and admit this is a failure. So I moved on.

AI assessment note: “No, the first failure was a web app.”

Q Got it. Okay. So, so you're obviously, you saw there on a seat based model. Uh, give me more of the, the background story here. What year did you launch the company in?

A So we started in 2011. I worked in consulting and the co-founder was forming a lot of big data and machine learning startups in India. We both studied at Indian Institute of Technology, Bombay together. And we said, uh, in AI, there are four elements. You have computational power, you have algorithms, you have people, and you have data. The whole world seemed to be focusing on either the computational power aspect of it, or throwing a new algorithm to an already existing problem, uh, like deep learning, neural nets, et cetera. Nobody was looking at the data side of the problem. We believe data will move the cheese. A, in terms of making it accessible to also smaller biotechs, the smaller treatment centers in different parts of the world, and B, if you would input more relevant data into these computational engines, you would, you would get more relevant, uh, insights that would really help you in decision making.

AI assessment note: “So we started in 2011. I worked in consulting and the co-founder”

Q All right, so it was 2004 was launch date, and have you decided to bootstrap this or raise capital?

A Yeah, we've initially, it was, I funded it a bit, uh, and, uh, then we got some early investors as well, and then, so we've gone the traditional venture capital route, so we, uh, we've, we have, uh, Excel, Index, Mayfield, um, and so fast forward, 12 years, uh, the last round we raised was four years ago, uh, where we raised forty million dollars, but all told, we have about ninety million dollars, uh, into the business, and, The last round also included some strategics. We got Samsung to invest in us, uh, Docomo Capital, uh, Fortinet, uh, et cetera. So it's been a mix of both your traditional venture capitalist, and then in the last round, we brought some strategics and raised a little less than a hundred million dollars through five rounds.

AI assessment note: “we've gone the traditional venture capital route”

Q a lot of cold-hearted capitalists that listen to this, along with a lot of developers, but I don't want to lose my capitalists, so I have to ask the question. You know, you're a, you're a guy that just seems hyper-focused, and we'll talk about what happened in 2007 or 2005 here in a second, but, um, talk money to me for a second. How do you guys make money?

A So we are, you know, vast, vast majority, 98, 99%, uh, subscription business. So, uh, the three main things people subscribe to are wordpress.com, which is hosting for WordPress, and Jetpack, which is services for WordPress if you host it someplace else, like, uh, could be Bluehost or GoDaddy or Rackspace or anywhere, and then finally WooCommerce, which is our e-commerce platform, and so that's people who build stores, listings, they sell digital goods, physical goods, or just take bookings, like, for salons and stuff. People use it for all sorts of e-commerce. So between those three, we have Kind of products you can subscribe to at each. And, um, that's really the main driver of the business for Automatic.

AI assessment note: “vast, vast majority, 98, 99%, uh, subscription business.”

Q Yeah. Very good stuff. Tell me more about customer acquisition. So how are you acquiring customers?

A So we do a lot of marketing. Next week's a big event, Dreamforce. We'll go to Dreamforce. We host a booth. We host executive suites. We'll probably come out of Dreamforce having spoken with 20, 30,000 different people. I mean, it's a massive event. That's an example of a trade show that we go to, and we do many trade shows in different ecosystems, Microsoft, SAP, etc. Um, the other thing we do is we do, we host webinars. So we will Uh, host probably 60 webinars in a year to invite our database of 200,000 people to, uh, come and hear different topics on how we help with their digital transformations, connectivity, API management, et cetera. Um, so it's a lot of outbound marketing, and the majority of our sales folks are taking inbound calls. We don't do a lot of outbound selling activity other than our sales development reps We'll, um, we'll do some of that, but most of it is driven by both marketing and partnerships.

AI assessment note: “we do many trade shows in different ecosystems... we host webinars... driven by both marketing”

Q And so here's, here's my question to you. How do people find you, right? I park in Austin. How do I know to go open my phone, download the app and use you?

A Sure. So Austin, ironically, is one of the, one of the few cities we don't have, but we're in places like Washington, DC, Atlanta, and New York. We're launching Philadelphia next week, Los Angeles, Minneapolis, Austin, uh, Dallas, Fort Worth, Houston. Uh, you'll see when you park on the street, you'll see signs that say, you know, pay by app, download park mobile, uh, or if we've created a white label. So like park Houston is powered by the park mobile network. Um, they'll see to download the app and therefore you can avoid putting coins into a machine. Uh, or like I said, walking half a block to print a ticket and then put it on, on your dashboard. Uh, we had about, about 250,000 people download or register our app every month. Right now, about seven and a half million people use us, uh, with, with relative consistency.

AI assessment note: “you'll see when you park on the street, you'll see signs that say”

Q Makes good sense. Now give me, now that we understand kind of pricing and what you do, give me some of the backstory here. So what was launch year?

A Launch year as a tech company was 2011. Initial launch was actually a charity pub crawl in San Diego for the American Cancer Society because my mom had battled breast cancer, uh, through growing up and we, we wanted to do something good and sort of our frustration through the process of trying to give to the ACS. I love them now. Um, don't, don't get me wrong. Um, it, it inspired us to basically do all sorts of Fundraising events in San Diego and bring young people into the fold. And eventually we sort of discovered this gap with these nonprofits we were working with that their technology was really, uh, you know, outdated and not modern. And we decided to, I like to say naively, ambitiously throw our hat in the ring and build a platform that would help them basically modernize and reach new supporters.

AI assessment note: “Launch year as a tech company was 2011.”

Q And what was going through your head? Like, what did you just leave corporate or what was your story?

A No. So my background is, uh, actually when I was 22 years old, I dropped out, I was gonna go to law school and didn't go. I'm East Indian, so I'm supposed to be an accountant, lawyer, a doctor, and so my parents were very happy about that. Uh, and I started this company in Toronto called Barter Business Exchange, uh, and we grew it to, uh, about 6000 businesses across Canada, uh, In 99, uh, we merged with a smaller company out of Seattle, and we created ubarter.com, took it public during the whole, you know, first wave of the dot-com boom, uh, and, uh, had a successful exit, and, and we were acquired, and, uh, uh, basically, you know, took some time off, so I was part of my

AI assessment note: “No. So my background is, uh, actually when I was 22 years old”

Q So So, uh, so what did you try early on? What was, what was not working from an acquisition perspective?

A So early on, we thought we would go like enterprise, uh, just cause you know, Hey, you know, we want to validate their product. People have to pay us a lot of money, uh, that before we build it, you know, we were all into the lean startup thing. Uh, and, and we had some, what I call like false starts. So we managed to get a few customers that when I met a few, I met like less than five who were paying us, uh, Between like 1500 and like 5000 dollars a month to use our tool, which was a lot of money for us. And then we thought, oh, we can do this model. And then nine months later, that number pretty much stayed the same. So we like acquired nobody.

AI assessment note: “early on, we thought we would go like enterprise”

Q Very cool. Um, yeah, and I can see from the site, so your Alexa traffic ring is 30,256 sites linking in. Like, it's clearly a good, I mean, a highly trafficked site for the, the space it's serving. Um, what, uh, take me back to the early days. The Hacker News article was a good example, but is there anything weird that you've done, non-traditional, to acquire customers?

A Yeah. Also, one weird thing we did, we did try to take advantage of the fact that we were a Y Combinator company in a, in one particularly interesting way. So we tried to, we went to Paul Graham again, and we're like, hey, this thing is working. Uh, would you make it a requirement for all of the winter batch of Y Combinator to use our tool? And in return, we will give you a dashboard. They'll know about this, but we'll give you a dashboard that they can share with you that has all of their growth metrics in it. And he was like, sure. Uh, so we built the dashboard. We got all those, all the YC companies on board, which I think was important because that was probably 50% of our growth that month. Uh, and then he never looked at those dashboards ever again. Um, so, so we cut that part of the product, but, um, yeah, we did some stuff like that, that, that didn't scale, um, We also built something called analytics academy, which was really popular. Um, we basically just explained the basics of how to use analytics tools and what the difference between all the massive variety of different tools out there was. Uh, and that also worked really well for sort of reaching that audience.

AI assessment note: “one weird thing we did, we did try to take advantage of the fact”

Q Four people total. Okay. And this was 2012 yet or no, still 20 11?

A Still 2011. And we spent a little more than the next year, uh, trying to build out an analytics tool. And the idea was to compete with Google Analytics or Kissmetrics or Mixpanel. Exactly. And it turns out this is a bad idea too. And the reason is that the space is incredibly crowded. Um, this now plays to our advantage. We integrate with all of these tools. Um, there's hundreds of analytics tools out there. It's also very difficult to sell the value of insights. Um, and, um, the concept was that we were going to be very segmentation focused, which is actually where the name segment came from. Uh, at any rate, we spent about a year trying to get this, trying to get this right. Never really got any customers and our, our cash was dwindling. And so we went and had office hours with, uh, with Paul Graham, head of Y Combinator and basically gave him the story.

AI assessment note: “Still 2011.”

Q So let's say I pay you 1200 bucks to, to run my account next month. What do I get for that?

A Yeah. So you get your own virtual assistant that's doing, um, these DM engagement groups and what, what you call rounds. So these are very time consuming, but one of the best, best methods to actually grow your account. And, you know, rounds are a method in which multiple Instagram accounts help each other grow organically by mutually liking and commenting on their content. So usually each group in a DM has 15 Um, people, and you know, it takes about maybe 50 to a hundred different groups of 15 people to actually grow your account like crazy. Nobody has the time to do that stuff. So, um, that's why they hire my company so that we can do those, um, pretty much all day.

AI assessment note: “you get your own virtual assistant that's doing, um, these DM engagement groups”

Q used the same. He said, oh, well, we're going to raise like a pretty normal like series A, and I said, well, what are you doing? And he goes, well, it's like this husband and wife who's like our neighbor that like wants some cap table, and they want to invest over the next five years. I'm like, that is not normal. So like typical is different for different people.

A So I'll give you, maybe you're asking for more. So I would say our, our capital raises have been fairly old school in terms of their, their, maybe the better word is classic, right? Within a classic, uh, seed round or angel round, we called it of, uh, uh, 650 K. Then we did, uh, you know, classic real seed round of two and a quarter million dollars. Then we did a series A of six million dollars. Um, so, you know, series B, you know, eight to 15, you know, eight to 10, that's the kind of range you see in the valley, uh, Um, and that's kind of what we're, what we would be likely looking to raise. So it's pretty broad range, but it's, it's fairly typical here.

AI assessment note: “seed round or angel round, we called it of, uh, uh, 650 K”

Q start landing and expanding and you're looking at the email addresses and seeing, you know, at abccompany.com, there's one, the first month, there's 10 a month after that, there's a hundred after that. How do you transition literally technically from your pricing back? And how do you get those people move from paying with their personal cards to selling to a decision maker and a big kind of annual contract?

A It's a great question. And that there is a, we put a lot of time into the upgrade past. And so basically like when you first sign up for the mobile app, we ask you essentially, do you want to collect receipts from someone else or do you want to submit receipts to someone? And if you click submit, it's like, cool. Who do you want to submit them to? And you type in the email address, your manager, it's like, great. Now we know who you Your manager is. Thank you for that introduction. Let me say like, who else submits to that person? And it's like, Oh, he's typing some friends. It's like, great. Now we know your coworkers. We just created a company for you. And then every time anybody submits a receipt, that's another time to promote that to your decision maker. And then we use basically every extension report as a highly targeted marketing message to the actual buyer. And then we say, it's like, Hey, click here to take over this entire policy. And then you can get all this additional functionality.

AI assessment note: “every extension report as a highly targeted marketing message to the actual buyer”

Q Yep. Got it. Okay. Makes good sense. So what's the backstory here? When did you launch the company?

A Yeah. So I actually started when I was in college and so amongst our competitors and us, we have a white label reseller program. So, um, basically what you can do is take our platforms and Completely brand it as your own and start selling to your own customers. And that's actually how I got started. So I was white labeling one of our competitors products. What year? Let's see. That would have been 2012. I think I just got started and then we became, I think I incorporated in March of 2013. Um, but started off as a reseller, started, um, you know, just with a couple hundred bucks a month. And then we ended up building up a 300,000 dollar recurring revenue stream in 12 months. And we realized like, Hey, there's some serious potential here.

AI assessment note: “That would have been 2012... I think I incorporated in March of 2013.”