Ignite AI: How AI Can Let One Fund Controller Manage 10X More Capital with Rajesh Gopi | Ep297

Rajesh Gopi (0:00)

You need people in the middle of things, right? It doesn't matter what, is it a bank, is it a fun admin, whatever it is, you need a human to be in the mix of all the events that happen within whatever the workflow is. But now I'm like, you don't need that. You need somebody in the beginning, you need somebody overseeing what the work is, look at the person at the end. AI can take over all the workflow that happens in between. I think that is a fundamental switch that I'm pretty convinced it's gonna be in the future.

Brian Bell (0:50)

Hey, everyone, welcome back to the Ignite Podcast. Today we are delighted to have Rajesh Gopi on the mic. He is the founder and CEO of Zive, an AI-native, fun operating system that helps GPs, fun admins, and CFOs automate back office work such as compliance, capital calls, and reporting. Before Zive, he co-founded 212, an Austin-based equity management modeling platform, after earlier stints at IBM, Freescale, Coinbase, Hypori, and others. Thanks for coming on, Rajesh.

Rajesh Gopi (1:15)

Thanks, Brian. Thanks for having me.

Brian Bell (1:16)

Well, I'd love to start with your origin story. What's your background?

Rajesh Gopi (1:19)

My background is pretty much writing software code. So I've been a software engineer for the last 30 years. I got excited about the Internet back in the mid-90s. When I first saw what was an early version of a laptop, connecting to sony.com, it took about three minutes for the page to appear.

But that really told me something magic was happening here. And then I worked my way into building applications in the Internet era, built a lot of protocol stack, worked on device drivers, worked on wireless technology, blockchain that led to equity management. And there, I met with a lawyer who was basically helping a VC make their shadow books match with what the fund admin was putting out. And that's how I got into the nuances of complexities of fund administration. And that led to starting Zive. So it's been a journey, a fantastic journey.

Brian Bell (2:09)

What's been the most surprising thing about building Zive? Because you're sort of, you know, it's not like you spent your whole career in this space, right? So you're an engineer who got exposed to it and decided, I can build something better. What's been your biggest surprise as you've been working on this project for a number of years now?

Rajesh Gopi (2:28)

So I think I see everything as like a math problem. Everything has got a lot of variables and it's really trying to understand how to best optimize those variables for the optimal solution. So that's how I see problems in general. Fund admin, in particular, the traditional thinking was, okay, you need a lot of fund accountants or controllers. They use something like a spreadsheet to run the operations and they get like dashboarding to see how everything would perform, what the state of the fund is, but they always had a fund control in the middle of everything. So now the disruption here was can we have AI do a lot of those tasks and be in the middle of the entire workflow operations, and then take the controllers away from doing day-to-day manual tasks and get them to be part of the final judgment call, making sure they are seeing all the numbers accurately and whether they can stand by the numbers that are being produced by the system. So it is really having these fund admins think differently out of the box that, okay, they don't have to be in the middle of the entire workflow, but they can be at the beginning and overseeing what happens through the entire workflow that has happened. So that switch is where we kind of started working on. And I think we are beginning to deliver. We have more than $6 billion of assets on the platform. So we can prove that, okay, we are able to show how that transfer...

Brian Bell (3:56)

Six billion with a B, A, U, N.

Rajesh Gopi (3:58)

That is correct, yes.

Brian Bell (3:59)

On the platform. Pretty incredible.

Rajesh Gopi (4:01)

Yeah.

Brian Bell (4:01)

And if I recall, there's like two tracks. There's the self-administered track, meaning like, hey, I can just use your platform and kind of run it myself. And there's the full service. Walk us through kind of why you have this, you know, two levels of service model.

Rajesh Gopi (4:14)

Yeah.

So we started with emerging managers. So for us, emerging managers are like sub 70 million AUM. And we picked them because of some very specific pain points that have, especially in terms of the cost of being fund administration. So a $20 million fund and a $2 billion fund is no different. It's the exact same requirements. It's just that the AUM...