Our Future Podcast
00:13:36 · Michael Sikand, Simran Sandhu
[00:13:36] S0: Yeah. I mean, I'm buying a robot, I mean, would be nice to pay later for it. Like, okay, dollars 100,000 for a little Boston Dynamics dog that's going to lift my packages. Yeah. Think about the productivity gains that could come with that, right? Yeah. Cut my payroll down. [00:13:50] S1: There we go. Yeah. So definitely big kudos to Alice and Lawrence. I mean, you know, they raised another $30,000,000 this past September. It's a tough time to be raising that kind of money in this venture market. But I mean, again, they've got the who's who of this space on their cap table. So I mean, truly super impressive. And you don't typically hear people in their late 20s. I mean, would have started this three years ago. So that would have put them at 25, 26 years old, like very, very impressive. And I think they chose a great space and they're well positioned to take over. And so for the second business we are covering today, it is in the fintech space. Now, it started by these three guys, Gabriel Stengel, Tomas Rakitas and John Willett. They're in their mid-20s and they've raised $7,000,000 for this company called Rogo. And they've got big ambitions. They're trying to displace Bloomberg. What they're ultimately trying to do is help you have your own AI version of a personal research analyst. And so they're selling to banks. They're selling to hedge fund... Hedge funds. They're selling to private equity firms. And it's really cool. You and I had the chance to look at the behind the scenes version
00:13:50 · Simran Sandhu, Michael Sikand
[00:13:50] S1: There we go. Yeah. So definitely big kudos to Alice and Lawrence. I mean, you know, they raised another $30,000,000 this past September. It's a tough time to be raising that kind of money in this venture market. But I mean, again, they've got the who's who of this space on their cap table. So I mean, truly super impressive. And you don't typically hear people in their late 20s. I mean, would have started this three years ago. So that would have put them at 25, 26 years old, like very, very impressive. And I think they chose a great space and they're well positioned to take over. And so for the second business we are covering today, it is in the fintech space. Now, it started by these three guys, Gabriel Stengel, Tomas Rakitas and John Willett. They're in their mid-20s and they've raised $7,000,000 for this company called Rogo. And they've got big ambitions. They're trying to displace Bloomberg. What they're ultimately trying to do is help you have your own AI version of a personal research analyst. And so they're selling to banks. They're selling to hedge fund... Hedge funds. They're selling to private equity firms. And it's really cool. You and I had the chance to look at the behind the scenes version [00:14:59] S0: of We got the privileged information that We funds really did. Can was cool.
00:14:59 · Michael Sikand, Simran Sandhu
[00:14:59] S0: of We got the privileged information that We funds really did. Can was cool. [00:15:03] S1: It was cool. So they've compiled over 100,000,000 documents, think like pitch decks, reports, all of that stuff. And, you know, kind of in this GPT style interface, I can essentially get any information that I need and that synthesis is available to me in real time. And so I think it's really cool. I mean, what's funny about them is they started this business a few years ago. They were incubated out of Ali Corp. And I think they have a really unique model where they essentially deploy, you know, a million dollars with these businesses and they kind of give you the resources to get off the ground. And so I believe Gabe and the guy who runs Ali Corp, Kevin Ryan, had some kind of personal connection and he took a chance on him and wow, did it pay off. [00:15:46] S0: So Dude, having a personal Having a personal connection to Kevin Ryan would just be perfect for, like, a young college grad, like, hotshot. Right? Like, he knows everybody. He is, He was a co founder of our parent company here at Morning Brew Business Insider. [00:15:59] S1: Yep.
00:15:59 · Simran Sandhu, Michael Sikand
[00:15:59] S1: Yep. [00:15:59] S0: And I love their venture studio model. It's one of the best in the industry, and they've had so many successes out of a model that many people have, like, failed at when trying to build multiple companies at once. Yeah. So yeah, they've just raised a $7,000,000 seed, is really cool, added some buzz and got the word out about them. A few press outlets covered them. But, I just wanna mention like a few of kind of the natural language queries you might expect on the platform. So think of it as ChatGPT for finance. So you could be like, compare Tesla's earnings to recent broker estimates or find me exit comps in the media industry or what is analyst sentiment on Nvidia per recent earnings? So it's very contextual. And I just, I'm making a story right now for our future on Michael Bloomberg. And one of the biggest parts that made Bloomberg, the best player in financial data was its ability to add context and analysis as opposed to raw data. These companies pay for data streams from so many different companies. But the question is, how do you actually make it useful? And I think that's what the superpower of AI is. Bloomberg brought that in with software and an intuitive user interface to become kind of the the language of finance.
00:17:03 · Simran Sandhu, Michael Sikand
[00:17:03] S1: In real time, though, that's also super important. Before you had to get these like daily reports with like prices. Yeah. And so that was really hard. Same thing here, right? If I told an analyst, Hey, I need this information. You're probably gonna give them, you know, ten, twelve hours to go do it. Like it's physically, humanely impossible for them to do it any quicker, but now you don't need that. It's one, you know, rogue search away to the answer you're looking for. [00:17:27] S0: And it's natural language, right? There's just less like, you know, keyboard strokes and Excel entries, and it's really just all of this is at your fingertips. What's really cool about this company is it's a very B2B focused play and that financial companies, all of their own methodologies, they have their own proprietary data sets, have their own histories of trading, right? They have a lot of bespoke information. And that's what they're building is like this turnkey solution specifically designed for each of these financial firms to get the most out of their data. [00:17:52] S1: But you can also implement and add your own proprietary documents with the public data. Right? So you're able to cross reference. And that's really interesting too.
00:17:52 · Simran Sandhu, Michael Sikand
[00:17:52] S1: But you can also implement and add your own proprietary documents with the public data. Right? So you're able to cross reference. And that's really interesting too. [00:18:02] S0: Yeah. That's where I think the value is, right? Because, you know, there's even you could like prompt it to update a deck. And that gets me to my next point, which is think of how much menial rote labor is involved in the financial services industry. Yeah. There's so much, you know, just putting words in a document. You know, you you have Princeton's hottest grad, you know, putting stuff in Excel and and and and a PowerPoint, right, when they could be working on higher leverage research activities. And I think that's what this kind of personal ChatGPT for finance is enabling, to pull data, you know, right out of thin air and be able to add value to communications very quickly and be a just for analysts to be a greater value add to their partners and inside the organization as a whole and for partners to depend less on the low... The lower guys, right, to be able to use this tool, to quickly source data instead of waiting on an analyst to be on call to get it done.