A Product Market Fit Show | Startup Podcast for Founders
00:28:25 · Pablo Srugo, Chaz Englander
[00:28:25] S1: Yeah, so now we can dive into kind of what you're doing today, is ModelML, what's the origin story there? [00:28:31] S0: Well for those three years, so we set up a small family office type setup where given Arnie was only 21, I was probably 27, we're like, well, we don't wanna just like give our money to like a wealth manager and just do nothing with our day. What are gonna do with our day? Why don't we invest our own money? Which was a great decision in hindsight in the sense that like, you know, you just learn so much, right? Like although there was advisors, investment banks, and even one private equity bid, and obviously we had that thing with Fat Lama where we to spark business. So we learned a lot about investing in the world of finance basically. I mean, it helps us study the accounting, but I didn't really know much prior to any of that. So we did that and we hired people to run our own money, right? So that's what we were doing and we were investing across. I always say when I speak to you, a variety of strategies, but the actual thing is looking back on this, we were just investing in like anything, right? Anything we thought was like cool, it would make money and we had like, we wanted to allocate risk like proportionately, We were kind of just doing, like, anything. Right? And so Do you think...
00:29:32 · Pablo Srugo, Chaz Englander
[00:29:32] S1: Was it smart, do you think, like, looking back, or was it, like, naive where you thought... Because, I mean, getting alpha in any asset class is, like, very hard to do. You need edge and you need all this stuff, assuming you assume, like, rational market and all that stuff. Like, were you just like diving into stuff and looking back, you're like, fuck. I can't believe like it worked or what's the [00:29:49] S0: Polite is, if you're asking whether we made money doing it, no. On balance, no. But but we didn't lose money. I... But we did make some money on some things, and then we did do some great investments and a couple of things, but generally speaking like we weren't making any money, right? So why are we doing it? I think so we're spending a lot of our day, you know, writing software to make that process better in one way or another. So either more efficient or we were trying to get to a level of insight quicker. And I, you know, I spent so much of my time just thinking of things that we could work on next, like as brothers, right? So Arnie must have got so fed up with me. I mean he had a full time job and every two minutes I'm like pitching him on like this new idea. [00:30:36] S1: So you wanted to start, you actively wanted to start another startup with him?
00:30:36 · Pablo Srugo, Chaz Englander
[00:30:36] S1: So you wanted to start, you actively wanted to start another startup with him? [00:30:39] S0: Yeah, hell yeah. This is so boring. So we were kinda writing software, bit of a day job, and then like there was all sorts of like different ideas and like we'd invest in things and we were like learning as we would go. And then we noticed that the idea that we should be working on full time was like the idea that was literally staring us in the face, which was the software that we are writing for ourselves to improve our own investment decision making process was great and people wanted that. Right? So that's how it started. And then, you know, we met a few people that, you know, were very senior in finance, know, a bunch of CEOs of the largest banks in the world and, you know, a bunch of really well known private equity investors and so on. And they were like, Hey, yeah, what's that? Like, this is pretty cool. Like, can we use that? Or like, how do I get hold of that? And then, you know, one thing leads to another and then we're like, hey, we obviously have to go at this full time. You know, the more the more time we then spent thinking about the value that we would bring to an actual customer, particularly when AI started to explode because then, you know, LLMs are really what took the software from being frankly not intelligent to intelligent, it was a no brainer. So the truth of the matter is like, it got to maybe end of twenty four or '24 time, and like we were kinda pushed out the door just based on customers wanting to use the product.
00:32:01 · Pablo Srugo, Chaz Englander
[00:32:01] S1: And yeah, that's how it started. It's, know, very similar to the kind of like Toby Shopify story, right, where he builds like this this ecommerce store so he can sell snowboards and like the snowboards are okay, but the store everybody everybody wants. [00:32:14] S0: Exactly. Because the thing is as well is like where it was and to a certain extent where it is, it's a productivity tool. So it wasn't necessarily making us better investors but it was making us more productive. [00:32:25] S1: What did it do? That was my main question, yeah, like what exactly was the product?
00:32:29 · Chaz Englander
[00:32:29] S0: It was basically, we would receive an opportunity. So when I say an opportunity, anything. It could be to invest in a startup, it could be to invest in a fund, it could be like some random co investment, it could be like a bunch of like stocks, it could be anything, right? And we'd get these opportunities through a whole variety of different avenues, we get them via email, and like there's a bunch of things that you do really really quickly as a human to validate those things. Now almost all of that information that you do to validate is not in the materials you received, because what you've received is a sales pitch, sales materials. They're not gonna tell you the bad things or the things that you might quickly get you to an answer early on, right? They're just trying to get you to like pick up the phone or get on a call or potentially be interested. So we basically set up this... Well, then we were just referring to it as like automatically calling functions. Now you would call an agent, but it would receive an email, it would look at the opportunity, and it would go and then do a bunch of things. So for example, if you... And maybe relatable to this audience, If you receive an opportunity to invest in a startup, right, one of the very, very first things that you do is you look at who is running the startup and you might see whether you've got like any connections in common with that particular individual on something like LinkedIn. Right? And you can get to the answer programmatically. So an example might be, I receive a deck and if that's one of the first thing that I do, I don't wanna look at the deck. I just wanna ping Joe Bloggs on, you know, WhatsApp, hey, just got this opportunity. What do you think of, you know, James Smith? Right? Or whatever it is. And so it was just building automations off the back of what you'd receive that could enrich the data that you'd ultimately got via email. So either via different data points, the example of, like, connections in common, things in the news. Now if it was a consumer company, you may have loads of bad reviews on Trustpilot or equivalent. Or if it's a a fund or or a new GP, are they posting strong political views on Twitter? I don't know. Like, you know, there was a lots of things that you could do. So that's where it started, and it just got more sophisticated.
00:34:35 · Chaz Englander, Pablo Srugo
So it wouldn't just give you the bullet points, it would actually create you like a word doc or a PowerPoint presentation of the opportunity that you could really quickly like get ramped up on and then quickly roll it in or out. So that's where it started. And for better or for worse, I mean, that's kind of what the product does today. We call it a workflow automation product for finance, but basically it's doing that, predominantly being used for the automation of the creation of materials. So Word, PowerPoint, Excel, etcetera, and particularly things that folks in finance are doing on a repetitive basis. [00:35:08] S1: So it's kinda like, I mean, like data enrichment, I guess, is is the primary piece. When you mentioned the the WhatsApp part of it, does it actually go out and reach out to people for you, or it just tells you like, hey, you know these people, maybe you wanna reach out, and then you can you can do it on your own?