The Exchanges

Q So how many folks are full-time at the company today, and how many of those are engineers thinking about agentic workflows for dental offices?

A So we have about 80 people, uh, worldwide, and about, uh, 42, 43 of them are in the U.S., and the rest of them are in India, and, uh, uh, engineering-wise, we have about 18, 17, 18 developers, and at least three or four of them are thinking about agent workflows. Uh, the rest of them are still working on a lot of the poise, payments, and other stuff, because that stuff doesn't go away, meaning you still have to Make sure your product is stable later on as well. But I personally spend a lot of time because I'm, I'm very technically involved myself, spend a lot of time looking at agentic workflows and how do we make all our existing stack fully agentic as well.

AI assessment note: “we have about 80 people... three or four of them are thinking about agent workflows”

Q things like that. I also think about obviously someone that might've built the, you know, inventory, you know, robotic system to manage Amazon warehouses, to get delivery time down by a millisecond, because then we spend more. I think about someone like you work with DARPA, right? You know, great university going to, I mean, why is your background and your team sort of best suited to win this space?

A Two things. The three co-founders, Daniel Gitesh and myself, like you mentioned, worked on the world's first full autonomous helicopter, won national awards for the work we did with aerial autonomy. So we had deep expertise in physical AI for aerial autonomy, and my thesis focused on how to make robots curious, and they're curious here in warehouses about boxes, barcodes, inventory, and workflows. So that, that makes the technology alignment quite strong. And the second thing is over the last six or seven years, how our stack has evolved. Now our stack is the only stack in the world that you can put on a moving camera that you buy out of Best Buy and turns it into an autonomous data gatherer. So that's the technical side of it where we have a data moat and a tech moat of, of given our technical backgrounds. But also over the years, We have assembled a bench of people from Amazon, from Uber, from, uh, Secret with deep logistics background. So our product has evolved to support logistics players in how they want to be supported. So I think those two combinations give us, uh, an unfair advantage to, to serve effectively in this space.

AI assessment note: “I think those two combinations give us, uh, an unfair advantage”

Q Very cool. Help me understand how you've thought about pricing, then we'll get the backstory here. What's the average director of golf paying you for the software?

A So our list price, which we stick very close to at a private club today is about 4200 dollars per year for essentially unlimited use of the product for up to, ah, two 18 hole golf facilities. So if you're a pine hearse with seven different courses, that's all custom priced. But it's actually, as I like to say, every business is price times quantity. P times Q, you learn in economics one. We're relatively low P, A high Q, high quantity. We're in 11,000 courses, so we're pretty, plus we do lots of other things, but it's certainly the most inexpensive software that club will have because they also need software to, you know, do their point of sale, to manage their T-sheet, to do their website, to do member billing, and things like that.

AI assessment note: “about 4200 dollars per year for essentially unlimited use of the product”

Q Really interesting. Okay. Let's do a couple of these examples here. HubSpot, VSP, just to be clear, are these real, these are real paying customers, real examples?

A They are real enterprise paying customers with logos that we are allowed to talk about. So these are not, uh, experimental budgets. Most of these customers are paying the cost of a human, um, plus and have multiple like suit, like HubSpot, for example, we are working on, I believe it is their fourth superhuman, um, to go live across their journey. Fiona, the one you're seeing here, was the first superhuman that we built for them. It's in the top left corner. Fiona is set to talk to their SMB business, so when somebody asks for a demo, they engage with Fiona, she gives the demo, she qualifies, she takes them through to close, and they were able to increase their revenue by 25% in their SMB small business segment.

AI assessment note: “They are real enterprise paying customers with logos that we are allowed to talk about.”

Q Ok, well, now we have to, like, I gotta figure out where to jump around. I'm just curious about so many things. So, I guess, why did you feel like you needed to buy the IP versus just build it from scratch, or the million bucks just bought you so much time?

A Uh, it bought me a ton of time for one. For two, uh, a lot of my competition, again, the goal is to, to both build the moat and pull the drawbridge up from competition. So a lot of folks in my space were starting to, to look at it, see it, use it a little bit. And there were some big behemoth competitors like Memory Blue, abstract marketing and things of that nature on the like outsource sales development world that were starting to get their hands on it. And I was like, if I'm going to protect this and have a unique value prop, I got to own it. And I'm going to dictate who can use it.

AI assessment note: “it bought me a ton of time for one. For two... build the moat”

Q Six million homes. Really? And, okay, sorry, where are you selling into? Are you bottoms up selling to one homeowner, then you spread or you're top down selling to the logo?

A Yeah, absolutely top down. And, and we even started kind of far up market, large management companies, and we've gone kind of further and further kind of across that, that segment as we go. So our first customers had, you know, 50,000 plus doors or homes that they would manage at a time, but we sell to the community association management company. Those folks, we become the general ledger system of record for them and for all the communities that they manage, as well as the system of work for all the work that gets done within that community, coordinating with vendors, collecting dues, paying invoices, reporting, as well as the system of engagement for them to provide a technology kind of front door for all of the homeowners and residents in the communities that they manage.

AI assessment note: “Yeah, absolutely top down. And, and we even started kind of far up market”

Q Yeah, that's great. That's great. So, um, so now that we know, 600 customers, nine million of revenue, have you bootstrapped this from scratch, or did you raise a bunch of capital?

A Tried to, almost went broke doing it. Um, ultimately, 2015 to 2019, um, friends and family covered it myself, um, and we got to a certain, a certain level where we needed, you know, more significant investment to handle the opportunity, and so, Um, we signed a 50 course, multi-course operator. Um, then they were called Brown Golf. Now they've merged and they've become Great Life Golf. And we, we didn't have the infrastructure that, you know, go across the country and implement all of these over a week or two. And they needed custom development that exceeded, you know, then a fairly small dev team. And so, um, had raised and gotten committed, I think it was like 300,000 short of my Series A. Um, it started off with a 600,000 dollar seed round that I funded a good portion of, then went to, um, raise a two and a half million dollar Series A, raised about 2.2, um, and an organization called Constellation Software out of Canada, um, you know, approached us about an acquisition and, you know, happy to tell that story, but ended up selling Club Caddy to Constellation in 2020. Um, they hired me and I worked for them today.

AI assessment note: “Tried to, almost went broke doing it. Um, ultimately, 2015 to 2019”

Q Okay, so you're sitting there looking, you know, I'm Rajesh, I'm refreshing my Chase account, you're like, whoa, that's a lot of digits. Uh, you say, what do I do with all this money? And you say, you know what, let's bet it all. Let's spend a hundred million bucks cash to go acquire Unbox. Why'd you do this deal?

A So a couple of reasons. One is we wanted to look at adjacencies. We want to, first we want to do a large deal. We've done a couple of small tuck-ins where you sort of add on to the tech, but that's not as exciting as a larger deal which can do, which did two things for us. Number one is gave us a complimentary product which we can sell into the same, ah, marketing department. So Unboxed, Uh, does search and product discovery. So competitors include Algolia, Bloomreach, Constructors, so you can sort of place them. There. And it also gave us a presence in the U.S. market. For a company like ours, primarily India, Southeast Asia, emerging markets, it's very hard building an organic presence, uh, uh, organic base and organic growth in the U.S. And that's where Unboxed came in. So at one shot, we got about 200 plus customers whom we could potentially cross-sell our products to.

AI assessment note: “So a couple of reasons. One is we wanted to look at adjacencies.”

Q Okay. And then, so we talked about voice a customer. We talked about paid to amplify. Talk to me a little bit about your own team. So, so what do you mean by your team in LinkedIn?

A Yeah. So we created a channel called Operation LinkedIn, and essentially we have everyone share the posts that they're doing. We try to have it be tend to be topical focus. So talking about marketing automation, talking about owned assets, talking about AI, anything that kind of ties back or relates to our product. And we tried to gamify it a little bit. We had what we call the 10 K club, which means you got at least 10,000 views that week. And we tried to show what the top performing content was each week to give people specific examples of how they could up level. And so we continued to grow that. Our first goal was as a team to have 150,000 views a week, and then 200,250 thousand. And I think we're a little bit north of 300,000 a week. Impressions is what I'm talking about right now, right now. So we're continuing to try to iterate and improve and just have many different known faces on channels like LinkedIn that can help spread and distribute topical leadership. I think, again, the key here is we're not just sitting here talking about active campaign. We're talking about the category. So we're talking about email best practices. We're talking about the tactical layer. Um, not just company or product focused content.

AI assessment note: “we created a channel called Operation LinkedIn, and essentially we have everyone share the posts”

Q Why, Alessandra, why people are thinking, why can't I just set up a will to prevent that? Why do I need a revocable living trust to do that? Why can't a will solve that?

A A will goes through probate. It has to be processed through probate court. A will is just instructions for who you want to inherit your assets, but the government will still process that will. And, and people will have to actually show up for court and make a claim for those assets. And so that process takes on an average 18 months. If you have a trust, a trust is an actual legal entity. You put everything you own in your trust. Your trust now owns your home. It owns your investment accounts. And so if something happens to you, your successor trustee takes control of your trust and can do whatever you want with your assets based on the instructions that you created.

AI assessment note: “A will goes through probate. It has to be processed through probate court.”

Q Well, it's great. Obviously you build a product, you eat your own dog food. That by itself is a natural advantage getting into any new startup. You're now building Beehive, which is effectively a marketplace between publishers and advertisers. Anything you'd add to that sort of one line overview?

A Yeah, I actually say that would be like the second line of what we're doing. The first is we are a SaaS platform for publishers, content creators, um, businesses to send email. So anything from MailChimp, Constant Contact, Substack, like those are kind of the competitors. If you are sending email to your audience or to your customers, we are first and foremost a SaaS platform to send emails. What you hit on is actually the second part, which is we are building an ad network on top of the SaaS platform. So As someone who is sending newsletters to their audience, we have advertisers like Netflix, HubSpot, monday.com, Betterment, that are looking to reach these niche audiences of newsletters, and we help connect them so you can send a newsletter with the premium sponsor without having a sales team.

AI assessment note: “I actually say that would be like the second line of what we're doing.”

Q How do you do that? Cause like, if I go to cloudbeds.com, I just see software. Like what's your equivalent of Expedia.com?

A We don't have the equivalent. So what we do is we feed it into various sources. So for example, 62% of all origination of travel these days is happening through social media influence. So using ads, Very targeted ads that are automated using generative AI. We can place an advertisement in front of a search population that's looking for a property that could be event specific. That could be, I'm just looking for a property in Costa Rica. It's called our Amplify solution. So we're not at, we're not a brand. We're not a place that you go. We are just originating the way to reach the guests and then sending them right back to our, our booking engine experiences or landing pages. That we create on behalf of the property, help them transact, and we take a very tiny, tiny sliver of that in comparison to what Google, or excuse me, what Expedia or Booking.com would charge at 20%.

AI assessment note: “We don't have the equivalent. So what we do is we feed it into various sources.”

Q Um, you just launched us eight weeks ago. Obviously we're in a very interesting macroeconomic time. I believe as recently as three years ago in July of 2020, your last company strategy box announced a two million dollar seed round. What happened to that company?

A Uh, unfortunately we had a series of events where, um, I had, we had some non-payment by customers. We had a deal fall through for acquisition. Um, and Got to a point where macroeconomic climate was such where I was like, okay, well, if we continue with this rate, A, you know, the valuation exit's not going to be where any of us want to be. B, we also saw we had early access to ChatGPT just because it was a data management platform, and we did AI and machine learning. Um, I had a look at a lot of the functionality that we were building and investing in, and I looked at the capabilities of ChatGPT, and I went, well, This business is going to be usurped within, you know, a couple of years if we continue on this path. So I shuttered it.

AI assessment note: “This business is going to be usurped... So I shuttered it.”

Q And Anupam, if you guys look at timelines, right, so from an, on average, from initial email to term sheet signed to DD done and final closing docs, what do you guys typically close in?

A Yeah, quite a wide range, safe rounds, pretty clean. We can do it in as little as a few days, and we have done it. And then in some cases where there's complex, you know, we have quite a few cross geography companies. So all our companies are US market focused, but we have quite a few companies that are building in places like India. We also have companies from places like, you know, Europe and other places. But sometimes those require more work and more legal review, and sometimes they may require changing the structure. Which the founders and you're planning to do. And those could take, you know, a few months to three months. That's a median is probably three, four weeks.

AI assessment note: “That's a median is probably three, four weeks.”

Q Yep. Interesting. Well, you go, you obviously know me well, you know what, I'm always biased towards debt, but how do you think about debt versus equity if you want to raise money next year?

A I think it depends what you want to do, right? So I think that if, um, if you, if you really genuinely think that you could build a hundred million dollar business, then you're probably going to want to go out to venture money because you're going to need to raise two or three times. Um, and debt probably won't help you do that over the longer term. I think if you, if you think, and you're happy to build out a twenty million ARR business, um, and flip it for the two hundred million, um, Um, then debt could be a really good opportunity for you because you don't have to go out and raise all those venture rounds and you retain the equity.

AI assessment note: “if you really genuinely think that you could build a hundred million dollar business”

Q Oh, wow. Interesting. Okay. Got it. And, and you came in and said, now, did you come in because, you know, current investors weren't happy with the founders and they said, we got to bring in Russ or how'd that happen?

A Yeah, so my, uh, my prior company was a high-performance computing company, and my controller was married to a venture capitalist in the Philadelphia area, so I had gotten to know him, and when I sold that company successfully, uh, he asked me if I would, uh, consider running one of his portfolio companies. I actually looked at three of them, and this was the one that I thought, uh, Had the most interesting technology. And to me, it was a great technology with, with poor go to market and poor marketing. And so that's what attracted me there. It also was the value was in the software, but it was delivered in a, in a piece of hardware that we put servers out at each grocery store, essentially.

AI assessment note: “he asked me if I would, uh, consider running one of his portfolio companies.”

Q Yep. That makes a lot of sense. We're talking about team today. How many folks are full-time?

A So we have 50 people full-time, and 80% of the team is actually product and tech. We're API-first company, so it requires a lot of engineers. Uh, we have, uh, people from all across European and even global fintech, um, so very senior, uh, leadership team. For example, our CPO, Dan Osborne, is ex-VP product at Marketa, which he scaled from 30 people to IPO. Um, our chief of staff, Sophie, was CEO of Atombank. And we have a number of other great technical experts, like, for example, Alex Akimov, ex-head of API at Edian, or Andre Ifriam, one of the first technical leaders at Mambu. And so this is more or less how we think about the team. We're on a fairly low development cost base because we base them in Eastern Europe, but we then have very- Which part of Eastern Europe? Georgia. Georgia. One percent techs. Very, very, very favorable.

AI assessment note: “we have 50 people full-time, and 80% of the team is actually product and tech”

Q The 18. Yeah. That makes a lot of sense. It sounds like there's a story there. Did you have a white level partnership with a partner and then they went out of business and then you took it over or what do you mean inherited?

A No, so the story was there's a Swedish company called Fort Knox that does, uh, small business accounting and invoicing, uh, and they used to have a CRM in, in, in their product, which they wanted to discontinue. Uh, so we made a partnership deal where we offered up sales to, to these customers who were using their own product. Um, and, uh, we had that partnership for, I think two or three years, uh, but we realized that Churn was a little bit too high and, and the growth was, was not really coming from this, these customers. So we, uh, just renegotiated the contract and, and migrated these customers to, um, to become direct customers of up sales.

AI assessment note: “renegotiated the contract and migrated these customers to become direct customers”

Q And where's the growth today coming from? If you've shut down the partnership channel, how are you getting more direct customers?

A So, I mean, we, we divided our, our sales team into a new sales team and an expansion sales team. And, um, we also, we have a kind of deliberate land and expand pricing model. So, so I think maybe two thirds come from, from existing accounts and one third from, from new accounts. Um, and I mean, we, we're actually spending some time now thinking about our pricing because we realized that Companies up to a hundred employees for those companies are, our pricing makes total sense. And, and a good customer pays us around one percent of their revenue. Um, but as you go up looking at bigger customers, we tend to have a lower and lower take rate. Um, so now we're working on, on, um, differentiating the pricing to have more of a kind of an enterprise offering for larger customers. Uh, so when I talk to investors, I usually say that we think that we can triple our revenue without bringing in a single new customer, uh, because the, the, the potential in the existing customer base is still massive. Um, and, and in our kind of Target list of new customers, uh, in only in Sweden, I think we have like three or four percent of those customers today. So there's also like a massive opportunity and a long runway of, of new customers to sell to.

AI assessment note: “maybe two thirds come from, from existing accounts and one third from, from new accounts”

Q Now this, you don't all have a, you know, rosy stories on all your startup ventures. Cause the last imagine on the show is probably four years ago. You were at a company called inspire beats. What happened there?

A Inspire beats was, it was a lead generation startups to give everybody a little backstory where we were selling leads every month. Um, and that was doing really well. It was over a million a month. Um, very, very quickly. We were getting like all these companies in Silicon Valley. Um, the problem with it though, is it wasn't a SAS, right? It was an agency which required A lot of work on the back end to fulfill. Um, and I, I wrote about this in the book, actually the founder, uh, that was running everything, you know, cause I, I was a minority partner. I had 10% of this company. The founder was handling the accounting. He was handling the books. He was handling the production. He was handling even a lot of the sales stuff. Um, he went fully, like fully insane, uh, to the point where he was committed to a mental hospital. And, uh, two, three months of nobody running the company and me not having access to bank accounts to refund customers, me not having access to anything, um, would be enough to basically ruin the company's rep and, and, and shut it down. So.

AI assessment note: “the point where he was committed to a mental hospital. And, uh, two, three months”

Q Make us feel that. What did you actually do at WeWork? And most people are going to go say, wait, isn't Gil like super rich? WeWork was worth a lot of money. Did you own equity there?

A So no, not rich. Um, but I had the best Five, six years, you know, amazing time working for WeWork. I joined in 2015, and I left when COVID hit in May 2020, unfortunately. What I did for WeWork at the beginning was I, um, I programmed and streamlined a lot of the experiences that took place Inside our facilities, inside the WeWork buildings, and about two or three years afterwards, after I began working for WeWork, I've identified an awesome opportunity to rent WeWork locations for private events, not just for offices. So take in an unacquipied, unmonetized space, and rent it for people that are interested to host daily workshops, conferences, Multi-day events and so on and so forth.

AI assessment note: “So no, not rich. Um, but I had the best Five, six years”

Q How did you take those customers? Are they the same customers paying more or did you fire those customers and just bring on more mid market enterprise accounts?

A So those customers are still there. And so they are still significantly, uh, keeping the average down, I'll say. Um, but since we last, since we last talked, uh, currently we've got a 155, uh, companies. Um, we're at about 650 in annual reoccurring revenue. Um, we purchased one of our competitors, safety tech, Um, rolled them in, in June and, um, did a, about a 180 degree pivot in our product and went from a very rigid, uh, system to now that was very designed for those smaller companies. That's why the contract value was so low to now we're, you know, uh, putting out proposals and, and, uh, and signing contracts that are anywhere from, you know, 20 to 60,000 a year.

AI assessment note: “those customers are still there. And so they are still significantly, uh, keeping the average down”

Q Well, did this other thing fail? Like, I mean, what got you off of the small business tool?

A Oh, right. Yeah. So it didn't fail at all. We hit our milestone, which was to rebuild the entire product, which was only built for WordPress at the time on the HubSpot infrastructure. So there's like a cloud version and a WordPress plugin. Um, so we got, we built that out with the team in Dublin, and then we actually got it announced on stage at Inbound as like a big product launch as well. Um, so when we left, it was in good hands. They knew what they were doing. There was another product manager who's working on it too. So we kind of like transferred all that knowledge that was in our heads into the heads of the team moving forward. Uh, and then we left to go start Tetra. So all is well. Very good.

AI assessment note: “So it didn't fail at all. We hit our milestone”

Q Oh, amazing. Okay. Got it. Got it. Um, okay. Very interesting. And then put this all on a timeline for me. When did you write the first line of code for the company?

A Yeah. Um, so, uh, we, we launched and we, we started the company in 2018, me and my tech co-founder, Kashi. Uh, we launched the OKRs product in 2019. Um, and from there, we, uh, in the same year, we actually realized that many teams being new to OKRs used to come over to us and say that, hey, tell us more about OKRs and how to use it correctly. We're familiar with it, but we want to know how to use it correctly. Um, so we got certified as OKR coaches, coached about six, 50 plus teams, ran about a thousand plus check-in meetings and built the product as we were close to users. Um, uh, so from there.

AI assessment note: “we started the company in 2018, me and my tech co-founder”

Q when we last spoke, uh, this would have been back, um, in early 20, 21, actually. You told me, you know, your largest customer was 240,000 bucks a year. You know, you had 1200 customers paying a hundred bucks a month on average. You're doing about 1.5 million in total ARR. Um, and you, I believe you were basically bootstrapped outside of a small seed round. How have things changed?

A Oh my God. There's been a lot of change. So, so at the time we had, you know, a base has always had the intention of being full stack, low code, but we had essentially half the products stood up. So we started with the backend. We had a backend as a service product, and we had a professional services offering that would help people use that backend. And so part of our bootstrapping and dog fooding strategy was to bring services to the table. Uh, do large engagements that implement a base while we were building out the rest of the product. So that rest of the product, which is all the front end tools is now in the market. Uh, in the process of all this, we raise venture capital. Uh, so we closed the 10.6 million dollar round, uh, earlier this year. And, you know, we're in the process of shifting the business model. So taking the services side of what we do, and instead of us doing it ourselves, creating an ecosystem of external providers that do it on behalf of our customers, we've already got, you know, a seed, you know, a bunch of those in place and we're, we're building out more. And then really focusing our efforts on product led growth. So really implementing a product led growth flywheel, and then a B to B sales, uh, effort that goes on top of that.

AI assessment note: “we closed the 10.6 million dollar round, uh, earlier this year”

Q Okay. Interesting. Um, how do you create like alignment between you and the startup? Cause if you find those nine candidates in the first month, they obviously want to move quick. They want to do that, but you make way less money because then they can just stop at the end of the first month. So how do you create alignment here?

A Yeah. So a few ways. One is we'll take on your top three priority roles at a time. Um, and so say it's month one, you have three priority roles. That's just seven K for that month. If you wanted to add additional roles, that's just two K per role. Um, but we're very flexible. So typically as we fill a role, then a startup will backfill that with another priority role that's coming up for them. Um, so we work very flexibly just in terms of how our startups and our clients want to hire. Um, if they have higher volume, say you're hiring a senior full stack engineer, but you have five head count that would all fall under one rule. So we can lock those all out for you and lower your cost per hire significantly.

AI assessment note: “as we fill a role, then a startup will backfill that with another priority role”

Q And so is that your only model right now? Are you selling the SaaS stuff now too?

A No, we still sell the SaaS product. So our initial plan when we work with the retailer is to educate them on our SaaS product, and that's going to range anywhere from 1500 to 3000 a year. Right now, our average customer is paying us about 225 dollars a month for the software. So once they have our software, we plug all of their lenders into the platform. And what we do is we identify their lender lineup and look for gaps. So if they don't have a near prime option or if they don't have a good subprime option, we'll introduce them to the people that we use and then we'll add a lender to to their portfolio of lenders.

AI assessment note: “No, we still sell the SaaS product.”

Q 20 14. Okay. And for folks not familiar with the product, maybe tell an example, give an example of a customer and what they pay you for, what do they get?

A Okay, so our average customer is a mid-market company, uh, that is very concerned about security, uh, cybersecurity, I should say, um, and can't afford or deal with all the, uh, Uh, products that are out there to create a, uh, cybersecurity environment for themselves. They would need to buy anywhere between six to 15 different products, uh, spend between 40 to a 115 dollars per user per month. And, um, and then deal with all managing and integrating and, Uh, dealing with all of these platforms, and what we've done was we created a, uh, single platform that takes care of all the security needs of a mid-market or a small business, uh, company, uh, for seven dollars a month, um, and, uh, just covering everything from their users, to the devices they use, to the networks that they connect through, to the cloud services, to their email, everything through one platform, which is extremely simple to use.

AI assessment note: “our average customer is a mid-market company... for seven dollars a month”

Q Who was your first partner in building this?

A So who was my first partner? So my first partner is actually, uh, Daniel Portoyo. Daniel Portoyo was the head of talent in, uh, Greylock. And I knew him for many years. And every time I met him, he gave me, you know, the right, uh, connections and contacts and introductions. And when I read that he's starting, uh, sweat equity ventures, now it's called the general partnership. I immediately called him. So let's work on this together. And, uh, it was transformational. He quickly connected me with the right, Recruiters and advisors and so on. So we got it off the ground very quickly. It still took two full years of development in stealth mode to reach the point we're in right now.

AI assessment note: “my first partner is actually, uh, Daniel Portoyo.”

Q So, so is that what you're doing? You're almost like, you're almost like Sotheby's you're, you're actually spending all your time recruiting artists effectively.

A Uh, yeah. So we, we've got two main business lines. We've got, uh, a business line called launch pad where we help artists launch their NFTs for the first time. And that is absolutely what, you know, as you described, it's very much like artist outreach, right? And then we have a, another business, which is called secondary, uh, secondary trading. So this is where the art is already in the hands of holders and they're trading it back and forth. It's more like a Craigslist kind of thing. Um, that, that piece of it is much more about being in touch with the collector community and, you know, uh, marketing to them and incentivizing them to come to Magic Eat It.

AI assessment note: “And that is absolutely what, you know, as you described”