The Exchanges

Q So let's talk about the SAS component first. What is the customer paying you for on the SAS side?

A So we actually haven't even launched it publicly yet. Um, the, uh, SaaS platform is called fuel. Um, we've publicly announced it because it's actually, it's a market and competitive intelligence platform. So it's how we build our investments practice, how we do market tracking, uh, uh, tracking, uh, proactive discovery, market theses. Um, and it's also, we've today launched, um, it's SaaS, uh, subscription model. We've launched three services modules that are almost managed services On top of the SaaS platform, market product strategy, business growth strategy, and Marcom services. And so those services start at three K a month. And they scale up from there. And we basically productize and modularize, uh, these services using our technology capabilities so that they can be hyper scalable, uh, really, uh, margin friendly. Uh, and, and then over time, the idea is that we'll then open up the SaaS platform, uh, to the market. Once we build up a bunch of captive, uh, demand and customers on top of the managed services practice in the investments business.

AI assessment note: “it's a market and competitive intelligence platform”

Q So what is the native services practice? You mentioned there's, there's technology there, right?

A Yeah. So the services practice, uh, think of it like a private company database. Um, think of it, uh, you know, almost an operator, uh, version of like Traxin or PitchBook, uh, that are more based or built for venture funds or private equity funds. What we're trying to do, um, is basically have the most accurate and connected data sets on companies and markets. And then we're building a capability called smart notebooks, which is really like smart automated templates for things like market research or Uh, strength or share of voice, uh, collaboration or marketing competitive, um, sizing and things like that. Uh, company pitch decks are really like operator tools on top of the data sets to, uh, scale businesses and we think disrupt markets.

AI assessment note: “think of it like a private company database... an operator version of like Traxin”

Q Okay. So it sounds like, and so try and quantify this for me. So when did you officially launch York IE? What year?

A Yeah. So we launched York IE last September, uh, 2019. Um, we left Oracle in the summer of last year after our, our near three year run there. Um, but again, we brought, you know, 75 plus angel investments and boards and advisor work that we had been doing me and my two partners, Joe and Adam, um, to bear. So we brought that kind of into the mix. So we had a sort of a captive starting point. Uh, but we, we started writing checks last September and, you You know, really, really aggressively going. We didn't launch our advisory services practice till this past May. Um, we hired Kate Campbell out of Pan Communications. What we learned about ourselves as operators is we knew how to operate, and we had a lot of know-how, but managing accounts and making sure we had processes and, and we were more programmatic, and we could actually account manage really well and do better reporting. Um, we hired someone who came from the services spectrum. She's a VP for us Who, uh, who, who helps run that practice and she started in May and we launched the service.

AI assessment note: “we launched York IE last September, uh, 2019.”

Q Why so many? Why go so wide instead of deep on a specific, specific sector?

A Yeah, I think it's, um, you need to get a broad enough cross section of startups in the sort of, uh, startup community. I mean, most of the companies think of it like a private company, Bloomberg portal. Um, there's so many small companies, the ability for these companies to get bigger and bigger and bigger, um, you know, it's just a long tail to the startup market, right? So to be able to cover all the disruptors, all the innovations, all the Features, capabilities. You need to have a pretty long tail on the market. Uh, we think a lot of the big use case of the technology, I mean, a lot of it was built on the backs of dying people that know this, we actually acquired 11 companies and we, and we spun out four different technologies that we sold to other companies. And then at Oracle, my team, we had, I had hundreds of people who worked for me, but we had a dedicated 35 strategic development team, which is basically marketing competitive intelligence. And it was a lot of manual. Automated research, market sizing, uh, doing proactive market theses, um, took a lot of human bodies to basically scrape the internet, uh, without technology. So to do this really well and keep an eye on the ankle biters and also the kind of heavily funded fast growth pre IPO startups, you just need automation and you need a wide, a widespread database.

AI assessment note: “you need to get a broad enough cross section of startups”

Q Walk us through that. How many investments have you made and what's the fund size?

A Yeah. So we don't run a traditional, uh, venture fund. Um, we operate an evergreen syndicate. So back in 2014, I co-founded the SAS syndicate on AngelList, which remains the largest SAS specific, uh, syndicate on the platform. Um, I co-founded that with Gil Pencina, uh, who's a good friend of mine from the industry. And, um, back when I was leaving Oracle, uh, we took that over from Gil and we thought at first we just invest our own capital and then leverage the AngelList syndicate. Pretty quickly, what we started to learn is that a lot of high net worth individuals and family offices were looking for an alternative In alternative investments from traditional kiss the ring venture funds. So what we basically created is a master series vehicle, a high net worth individuals and family offices invest alongside our capital. There's no traditional management fee and there's no traditional fund economics. We get a five year commitment from our investors to give an annual amount per year. Uh, and they get a percentage of every single deal we do every year. And then the economics, the York IE, or we take a carried interest on a deal by deal basis, not on the fund wide basis. So we pass through no management fees, no deal fees. Uh, and we just make money on the economics on the deal by deal carry interest. So it's just a different model. It's a little bit more fluid. Um, our backers ten…

AI assessment note: “we don't run a traditional, uh, venture fund. Um, we operate an evergreen syndicate.”

Q You could just go to pitch book crunch. So, so you either have to have a differentiated data set and then go wide and have a data point per each company that other people don't currently have. Or you say super, super focused and go really deep on a specific cohort. You're going wide. What data point are you going to have on all companies that they can't get elsewhere?

A Yeah, so I think a lot of those companies you just mentioned, Mattermark, Crunchbase, Pitchfuck, they're relying on lots of point solutions and point data sets as partners and integrators, like in Owler, Built With, or, and a lot of these, I was an investor and shareholder and board member of Datanize. I was a founding investor who sold the Zoom Info. A lot of these companies are good little companies, but they're never going to be venture-backed big companies, right? So a lot of the capabilities that are being integrated into the Crunchbases and others from these point products, we're Actually building ourselves and integrating it. The other reason why Metamark wasn't a successful company is because they fundraise too much. Um, the entire thesis of my investment firm is take less capital. I mean, the best part of the Dine story is that we didn't raise a dollar of outside capital till we were a thirty million ARR. I'm in the fortunate position to self-fund York IE and self-fund our fuel platform. So I can actually, uh, control our destiny, control our fate, control our cap table, and not be beholden Uh, to investors definition of success or failure. So I think it's those two things. I mean, it's building a lot of the IP ourselves. Um, I think it's launching our services and investments practice on top of the platform ourselves so that we can hone the product, the capabilities, …

AI assessment note: “a lot of the capabilities that are being integrated... we're Actually building ourselves”