Hanover Park raises $27M Series A to replace 'human duct tape' in fund administration with AI

and more. Well, Railway automatically takes care of scaling, monitoring, and security. And let me also tell you about Labelbox, RL Environments, Voice, Robotics, Evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams. Expecting our next guest to be duct taped to his chair.

Oh. Oh. Is he? Is he? He was duct taped. Oh, he's free. He got free.

I'm alive.

Okay. Okay. Introduce yourself. introduce the company and then explain the duct tape uh uh stunt.

I love it. Co-founder, CEO of Hannover Park. Think about us as financial infrastructure to power investment firms, private equity, venture funds, the most unsexy industry in the planet. We're now making sexy.

Thank you for your

Yeah. Yeah. So, I was duct taped to a chair and I announced a blooper that I tagged Jordan and you guys in. I was like, "Okay, how can we make the most boring industry in the world sexy?" And that was obviously replacing human duct tape. And so yeah, pumped to do it. We launched our announcer series today.

Okay. So the metaphor is there's a lot of human duct tape inside these funds piecing different puzzle pieces together to manage the financial assets and LP relationships and you make all of that go away. Correct.

100%. And also like I don't know, I've been saying this for two years like B2B SAS is dead. We want to sell outcomes not tools. And so tools are things that are a bunch of duct tape around with humans and software and we're like we're going to replace the human heavy services business out there too.

Sure. Sure. Sure.

Uh what is the what is the key moment for an allocator using the platform that that really wows them or clicks

when you want to make a $und00 million follow-on decision and you have to ping your CFO and say, "Hey, can you pull together the data that we haven't had in real time for the past two months? can you figure this out? Okay,

AI agents solve the problem by getting you real-time data and then help you make those decisions. Um, and so we're pulling in data from granola notes. We're pulling in data from emails and board decks. We're pulling in data from all the boring accounting data on those positions. And so people are like, "Oh my god, I can finally make a decision in real time without waiting a bunch of days." Okay, so there might be a whole bunch of decks from all the different investments and all the different companies that have various ARR figures and growth rates, but they're sort of buried. Uh, handover can go in there, get that data, put it in some sort of centralized database and then uh visualize that or maybe even help with marks. Is that something you do or is there still a human in the loop for that?

Yeah, even more importantly, we think there's a world where you don't even need to log into Hannover Park. we're gonna expose all the data via MCP server and so we launched that where people are accessing it via claude co-work and via GPT etc. Um

and so that's been a key piece I would say for like GPS whereas like CFOs are going to use us for things like capital calls distributions financial reporting to LPs etc.

Got it. Got it. What what uh so interesting uh so if somebody's on like the like enterprise open AAI plan or something they uh they do they have to integrate this themselves or is that just like a offthe-shelf plugin and then and then uh if they want to actually get this into like a deck what's the current stack to get that information they would be exporting it trans uh like transforming it over in their LLM tool of choice and then taking it to the LPS. It's actually even worse. You would have to email some human called your fund admin and say, "Hey, can you pull that data that's locked in some random tool you don't give me access to? You then get a spreadsheet. You then put that into another tool. You then put that into Claude or GPT, etc." And so, a lot of the value prop here is you're going to pay a fund admin anyway to do this boring financial reporting. LPs demand this from a third party. And so, instead of having that data locked away, we can at least give you access to it and then you can put it into Claude and other things. Got it.

How big is the market? I This is a market that like, you know, compared to like SMB,

there will never be too much venture capital.

I know. I know. I know. And we're trying to we're trying to to to get more people to be

there's billion dollar raised this month. Okay.

Um No, but but yeah. So, so I'm I'm assuming with with you know, venture funds, private equity, all this stuff, you know, you you have to kind of ignore like individual SPVS and entities. Um But but uh I'm assuming you can kind of clock pretty precisely like what the how big the market is and then you got to go and try to get as much of it as you can.

Yeah. So there's a hundred trillion of global assets and there's a $20 billion public

but isn't that isn't that isn't that like somewhat of a

like are you going to get PIMCO at some point right like

it's yeah it's like hedge funds right you have like private equity funds real estate private equity venture etc. Like SSNC is a public company today. They have like 5 billion of revenue. Sitco has 5 billion of revenue. Right. So there's a bunch of like these massive dinosaur companies that exist. And it's really like

venture and private equity is just the start.

Okay. Okay. And and and so within I mean venture also scales from $15 million fund to $15 billion fund. Like I imagine that there's some trade-offs where the bigger you go, the bigger the dollars, but also the bigger integration, the more requests versus somebody who's just starting a you know a new fund. They don't have any software, so it's super easy to get off the ground where have you been picking one or the other as like a beach head market or have you just been doing like whoever you know?

Yeah, you'd be surprised. The bigger it is, the the easier it is to differentiate actually. And so a lot of these bigger funds, they've been like running around with players like SSNC, which I call like the evil empire, which is basically like you're using them and all of your data is kind of trapped. Whereas like an early stage venture fund that's just getting off the ground, things are pretty clean and pretty easy. And so we've actually focused on like mid-market enterprise. So think like 250 million plus in assets, venture and private equity to start at least. Mhm. Uh do you do any work on the on is it all equity or are you starting to do stuff in private credit or private or like public debt or any of the other asset classes or are you just purely in alternatives?

Purely in alternatives today I would say like 6 to 12 months from now obviously focus on expanding into things like private credit obviously big opportunity being here in New York. I' I've been saying this for a long time. Favorite sponsor ramp. It's like Stripe for payments, RAM for expenses, Hannover Park for investments. And so that's kind of the the the

Have you had any customers just ask you to just handle just all the actual investment decision making?

They're like, I'll just put money in a box and then you you deploy it. Let me know how it goes. Talk to my LPs, too. I don't want to talk to I don't want to talk to them anymore.

Talk to founders or LPs.

No, not yet. Not yet.

I I I think it's been funny. It's like a lot of LPs that we talk to are like I keep, you know, my venture funds are investing in AI, but they're back in middle office is run by the anti- AI. And so this idea of like we're investing in it, we might as well move to it as well has been pretty exciting for people. But I think long term it's like unlocking alpha for the investment firm based on all the unsexy financial data that we have could be interesting. Um, but we got a lot a lot of work to do to get there.

Uh, unpack a little bit of more of like the dream unsexy proprietary data set. Does that look like uh pitchbook or crunchbased data? There's a lot of different data sources that venture capitalists go to throughout Diligence. Is do you want to be a conduit to those sources or do you imagine that the LLM tools that venture capitalists are using will interface with those separately and just do the joins in the whatever work session is happening?

Yeah, it's actually not really crunchbased pitchbook. It's really like the unsexy financial cash flow data. to like give me the cash flows from every LP through history and how that flows into our next cap call or our next distribution or our next you know financial statement. So it's actually that data uh which is the data that's mostly trapped in these fund adins. I think crunchbased and pitchbook access will get commoditized those will go into the the underlying models and I don't think we want to play that game.

Yeah. Uh talk about the overall health of the venture capital market. I feel like you're in a unique position. There's been these like sort of waring narratives. we joked earlier like $10 billion raised but that was open AI. Uh there's a lot of there's like sort of a crunch in uh K-shaped recovery maybe in venture capital. There's a variety of mega funds that are scaling up. Like what are you seeing when someone just asks you from the outside maybe they're you know a public markets investor and they say like how is how is uh how is venture capital doing these days?

We're actually seeing a lot of halves and have nots. It's a very stark bifurcation because when you start a fund, you basically sign a lawyer and a fund admin. And so we see from inception of how your raise is going. And so literally it's there's people that are raising in 3 6 9 10 weeks for a first fund, which is crazy fast versus 6 to 12 months. And then there are people who are never raising. And so I think it's the people that are spinning out of a lot of the major funds that are targeting call it a hundred to $200 million fund ones are having actually an easier time from some of the emerging managers that are focused on like $25 million fund ones. Um and so it's a pretty big bifurcation there.

How are you processing this new holding company rollup firm? It looks like a private equity firm but it also sort of looks like a startup. We've had a couple of these founders on where

Yeah, those probably aren't clients because they just get a bunch of money.

Yeah. Would they be or could they be in the future? How do you think about that?

It's actually funny. We've had a lot of these folks reach out because fund admin and like accounting services more broadly, right? Think about us as a subset of that because we're doing financial accounting reporting for investment firms. That is a ripe industry for rollup. And so people have been like, "Oh my god, should this be a fund admin rollup as an idea in terms of vertical buyout?" What we've realized is like if you just toss agents the the word agents on top of any accounting data, it doesn't really do anything. Having like the core ERP for the fund and the system of record that we had to build from day zero is actually like way more important uh than just saying like AI solves all our problems which I don't think does quite yet.

Yeah. Have you had to do any like fine-tuning on your own data or your system or are the agents sort of able to, you know, find their way around your system pretty quickly? Like did you need to build your own MCP servers or your own CLIs for these things? Uh we were just talking about this with Door Dash. There's like demand for a Door Dash CLI now. And it's funny, but it makes a lot of sense in the context of agentic engineering. Yeah, we've actually had to build our own little AI fund accountant, I call it, which is doing simple things like AI cash reconciliation. When you get an email from someone to make a decision, how does a human do that? It's actually client specific. Different clients have different preferences and so almost how do you build that like AI accountant? So, we're using a bunch of the models off the shelf uh to do that as well. And then we're doing some fine tuning on top.

Yeah. Does does that look like like a like an M like a MD file like a skill or is this more of like a full harness that's actually uh you know writ like a whole bunch of code that you've written like h how do you see that system growing as you develop more core capabilities? Yeah, I I think one so there's a bunch of different ways that we sliced it, but like for something like migration, which is how do I get the most complex financial data in the entire world from one system to another, that's a lot about building harnesses and building skills in and around the core underlying model providers to say this is the weird messy financial data from pick your massive investment firm. Here's how we need to think about this. Um, and then for things like doc processing a little bit differently. So depends on depends on the workflow.

Yeah. Tell me a little bit about the progress of the company like where are you based? How big is the firm? How are you growing? Where do you see this going over the next couple years?

Yep. So, two years old, raised 31 million. Obviously, we're today we're announcing a $27 million series A led by merchants. We went

Congratulations.

There we go. We did it.

We're just getting started though. We're just getting started.

There we go.

We're just getting started. What are you talking about?

I love it. I love it.

Um, we went 1 to 15 billion in assets in the past 12 months. We 15xed. We've had a lot of excitement from folks. I actually I was joking with the team. I said, "Guys, this is a top.1% problem." Uh, having unlimited demand and people excited now. Let's go make them raving fans, which is our goal for 26. And so, not cursor, but we're focused on, you know, keeping our heads down and executing.

That's great. That's great. Well, thank you so much for taking the time.

I love it, dude. It's awesome. Awesome to see your your progress. I remember years. Yeah. just the absolute best thread grinder from the 2021 era. Just ran it up and you're just

and so I'm sure you angel invested, right?

I did. I did miss.

What happened, guys? Saw got in. You didn't get in.

This is this is the nature of the show. This is why we're podcasting because uh we we we we we see people like you all the time and we just miss everything. So, back to the show. Yeah. Jordy makes a lot of good investments. I I just don't I just don't do it. Anyway, thank you so much for taking the time to come. Great to see you. We'll talk to you soon. See you, Chris. Let me tell you