← The Peel with Turner Novak
The Peel with Turner Novak
Inside Hanover Park: Building an AI-Native Service Business, Growing to $15B in Assets
01:11:41
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- [00:03]
A
Chris, welcome to the Peel.
- [00:05]
B
We're back.
- [00:06]
A
The. The second ever, second time guest. First one was Dan at Chainguard which they went 0 to 40 in revenue in two years. It's. Those are big shoes to fill.
- [00:15]
B
I know we went 0 to 15 billion in under two years. 20 months to be exact.
- [00:20]
A
So we're going 15 billion in revenue.
- [00:23]
B
That would be a lot. That would be a lot of revenue. I'm not cursor. Assets on platform.
- [00:27]
A
Assets on platform. Okay. So for someone who isn't familiar with Hanover park, they didn't listen to the first one which we'll link in the show notes for people if they want to listen to the year old conversation. What is Hanover park for people who don't know?
- [00:40]
B
You can think about us as financial infrastructure for the investment firm. And so today there's like all these insane armies of human duct tape we call it, that sticks together all the back and middle office to do all the financial reporting for the limited partners at these firms, for the CFOs and all that kind of stuff. And we're. What we've built is like unified software plus AI plus services to do all the financial reporting, which would be called fund administration. And then we also have a bunch of portfolio management and monitoring tools. And kind of like our thesis is that B2B SaaS is dead, which I said literally on this podcast a year and a half ago that's come true with Claude. These thin layers on top of data that you don't own are things that are being disrupted. And so our goal is build the system of records for the fund. We did that. And then owning and controlling that data can deliver better product for the cfo.
- [01:27]
A
So I know you just announced some news within the past day or two, three. Whenever people are listening to this. What's the thing you just announced?
- [01:35]
B
Breaking news heard here on the Peel. We raised a $27 million Series A LED by Emergence Capital Locks. Sousa participated as well to build the financial infrastructure for the investment firm.
- [01:50]
A
And how did this kind of come about? What was sort of the setup sort of leading into it and the process of raising a Series A because it can be hard sometimes.
- [01:59]
B
We were growing really fast. We went from 1 to 7 ish billion of assets on platform late last year. People were super excited and we were kind of like what I wanted to validate is the size of the opportunity. It's like you have 100 trillion of global assets. Largely these investment firms are paying millions and millions of dollars a year to these outsourced providers. And we Said, can I provably take this from a human heavy services business, from something that's scalable? And so that's what we validated and then we went to the market. It was very quick process. It only took kind of a few weeks or so. And there was this crazy moment where Jake Saper, who joined our board from Emergence, flew in from San Francisco to New York City on Friday night. He's like, I'm going to take you out to dinner. It was like a three hour long dinner. And I was like, when are we actually going to talk about the terms here? Are we just going to keep looking at each other, eating omakase back and forth? And at the very end he's like, all right, so let's talk about the terms. And so we end up negotiating these terms and he literally nothing. It's like Friday night at 9pm I go back to my apartment and at midnight I get a phone call. I'm like, why am I still up right now? And he's like, term sheets in your inbox right now. What are you doing? You have 48 hours to make a decision. I was like, oh, that was fun. So I was like, this is great. Now we'd done a bunch of back channeling with Jake and he had been super close to the team at SUSE as well. And he has kind of been the leader in what I call like AI enabled services, which we can talk about. And so pretty excited to team up with him and the Emergence team.
- [03:31]
A
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- [05:51]
B
Yeah, it's very, it's like army of humans with like a set of disconnected tools that people are buying. And so if you, they might buy. You know, you have a bunch of people in Kentucky, they are fund accountants, they are CPAs, they buy QuickBooks, they buy Excel, they buy build.com, they don't build any of their own tech because they call engineering it. They don't have engineers on their, at their companies. And so a lot of it's just disconnected SaaS tools with human duct tape on top. And so kind of the opportunity set is like we're like, okay, if we build this ERP for the fund, right? Which is like this, like everyone told us from day zero, this is crazy. Don't do this. Don't build this insanely hard thing to build. You're building financial infrastructure for the most complex firms in the world. We did it. And it was like if you build this, that gives us the opportunity to have AI agents action on top of that data. And so instead of having people clicking buttons, you can have agents actioning and then kind of the paradigm that we've had is AIs preparing things and then humans are reviewing things. And so we have well trained fund accountants on our team that are reviewing outputs to ensure accuracy. But that's never been done before. Most people I think in 2018 would be like selling software to a fund admin instead of saying like, I'm actually going to be the full stack fund admin.
- [07:02]
A
Yeah, because a lot of people then would say, you know, what's the size of the fund admin software market? And it's like tiny. Yeah, it's like not existent. I mean they pay for Bill.com and QuickBooks, maybe Intuit is a big company, but like, you know, it's tiny. And so what kind of changed then over the past couple years to just make this possible? And then you talked about how you built your own general ledger. Why did you need to build a general ledger? So like what's kind of changed and then why did you do what you did?
- [07:33]
B
Yeah, I think the big why now about this market is like it's possible now with AI to act as a fund accountant. We call it like an AI fund accountant. And so it's like, okay, we can take this and thing that used to be really disconnected tool set with a bunch of humans in a room trying to click buttons and do work to agent can actually click the buttons and do the preparation work for our team to review. And so I think it was a lot about what does AI unlock. But what I tell the team all day long is like if you don't have the right bedrock, the right like core foundational system of record, it doesn't matter what AI is doing on top. AI is not going to figure out Bill.com, which randomly isn't going to give access unless you're doing some computer usage agent. AI is not going to figure out Excel because there's a lot of limitations. AI's not going to figure out QuickBooks and other things. And so we said like the 80% is building the general ledger from scratch and then on top of that having agents action on. So I think the big change here was it's now possible to have agents doing work that would require an army of people. And now, you know, our, our fund accounting team can just review work.
- [08:35]
A
And it sounds like really what a fund administrator is, is basically an accounting firm for an investment fund.
- [08:43]
B
Like in the most simple terms, simple terms, financial reporting. You know, they also do like investor services.
- [08:49]
A
And you kind of talked about how we're entering this era of you can Build an AI native services company. So traditionally, if I'm thinking of it from like a technology business perspective, I'd look at a fund administrator and say, you know, they're not building any technology, it's just mostly people. It doesn't scale in the most efficient way. So what's kind of happening in this sort of like broader AI native services? Like are there certain things that's, that needs to be true in order for that to like unlock like this massive opportunity?
- [09:18]
B
Yeah, I think we think a lot and this is something we've spoken a lot at the board level in the past, like quarter or so, which is like how do we productize the services layer? Which is like we are tracking key metrics on things like what percent of cash is auto categorized, what percent of times when a customer sends us an email with a request that AI agent can action on it with no edits, right by the, by the human team.
- [09:39]
A
This is sort of like a customer service type of automation as well. And it's like, so you're automating like the accounting, you're automating the customer service, you're automating like other software that you're kind of starting to build on top of things.
- [09:52]
B
Yeah, a lot of it is like, like productizing these like core services delivery metrics we call it, which are things like cash categorization, email agents that are action on like customer requests and other stuff. And so that's been like the key part. Without that you are just. And I think the reckoning will happen in 2026 for AI native services businesses that are growing revenue but not actually productizing the services part.
- [10:13]
A
Oh wow. Is that a common.
- [10:15]
B
Very common. I think a lot of people are doing that.
- [10:18]
A
Are there certain categories you think it works best in fund admin? I'm assuming that's one of them.
- [10:23]
B
Well, I'm talking my own book now. This is talking about my own book. I think there's a lot around what is the data layer that we have access to that can enable us to deliver a better service? And so part of what we've done is said how do we build wedge products around the core fund admin? Because if I go to someone and be like, I'm going to give you slightly better fund accounting or I'm going to give you 10 times better fund, that's still kind of interesting but not the most compelling. And so we built a lot around AI native waterfall modeling, which is adjacent, or portfolio management, which is adjacent, or portfolio monitoring, which is adjacent. So it's like what does the full bundle look like? That's not just the core fund admin.
- [10:59]
A
And so the kind of like the core customer or core user bulletproof buyer decision. Maker of this is a CFO of an investment firm, like the finance leader in an investment firm.
- [11:10]
B
The CFOs are my heroes.
- [11:12]
A
Yeah, I know, I know you love CFOs. So what can they use AI for? Cause you just mentioned so many things like a waterfall model. Maybe you can explain why that is. Maybe it's not worth explaining, but you can just make that in Excel kind of. Right? So what's the importance of all this stuff?
- [11:29]
B
So I think there's like our goal is to become the default for how fun CFOs adopt AI. I think there's a lot of noise in the market. There's a bunch of providers, I call it the army of overpriced SaaS tools that are offering like, here's what AI is. And the CFO is like, this doesn't actually help me. And so part of our goal was we're launching an MCP server, which you can think about that as an API for AI, right? Which is like, I can have all of this data that Hanover park has inside, which is your LP data, your portfolio data, your fund performance data, all the data that might be in disconnected systems is now one place. And now you can give that and feed that directly into Claude, you can feed it into ChatGPT or Gemini. And now you can instantly access and say like, generate me a report with Yale Endowments commitments across our five funds with a pretty graph with my logo on it with our top five performing portfolio companies by ownership percentage, MOIC and Gross irr. That is like literally hundred hours of work to do across a bunch of random tools today. And now you can instantly do that through Hanover Park. And so I think that's some of the power is being able to like feed this into the tool you're already using as well.
- [12:38]
A
And that's even something, that's something like the IR team might make. So it sounds like it's not even just CFOs, it's like other people at the firm can maybe start using the tool too.
- [12:47]
B
What we realized is there's so many like CFOs and finance teams are like drowning because they get like hundreds of data requests that are like, hey, can you pull this like random initial versus follow on thing that like, of my venture fund portfolio companies that we have no idea what the stat is. And the CFO is like, oh my God, what do I do. They're like, do I just like, run around and like, try to go into 17 spreadsheets that haven't been updated in three months to figure out where this is? This enables anyone to instantly access your data as well as like the managing partner, the founder of the firm. So they don't have to be begging their CFO to get back to them in three days. They can instantly access it, which gives a lot of credibility to the finance team.
- [13:28]
A
There's a lot of these kind of like, I don't even know what you call it, like, banker AI tools or like, you know, junior credit analyst type AI modeling tools. Does this start to kind of flow into that? Not really. Like, where's the delineation between all that stuff?
- [13:44]
B
Yeah, I think like part of our. We call ourselves the anti GPT wrapper. There's a lot of companies that are fine, that are basically like, I am going to take GPT, I'm going to verticalize it for something specific. I'm going to enable it to be better for a lawyer, a banker, or whatever it is. Part of our goal was actually, we're the opposite of that because we did the really hard thing first. Building a general ledger from scratch is one of the hardest technical challenges you have. So hard that our early investors were like, what is going on? This is crazy. And so we're like, once you do that, though, you unlock all the ability for AI to action on data that you couldn't before. And so part of this was building the GL sets the stage to build the magical MCP server on top versus the opposite, which is I'm going to get data that everyone else has access to and then I'm going to make it slightly better on the afr. And so that's kind of how we thought about the paradigm, which was different.
- [14:36]
A
And it's basically, you know, you're people you might describe if you're trying to like, hype up this in the most simple terms possible. We'd say it's like an AI native fund administrator.
- [14:45]
B
Like, yeah, I think AI Native Fund admin. Strike that. Fund admin. Most unsexy term in the world. I kind of think about it as like, financial infrastructure for the investment firm. So Stripe did this for payments, Ramp did this for expenses. Hanover Park's doing it for investments.
- [14:59]
A
Okay.
- [15:00]
B
That's kind of how we think about it.
- [15:00]
A
And like, you didn't even start with like, hey, we're building an AI model for your fund. You started with like, we're building a general ledger that I mean, general ledgers have existed since like the invention of commerce, basically, like ancient Italy or whatever.
- [15:15]
B
Yeah, I think, I think the vertical integration story is around like, okay, what is the core job to be done? Every single fund in the entire world needs to generate quarterly financials for their limited partners. Great. You're going to have to pay someone to do that. May as well be us. Right? And kind of think about that as like the core layer. But on top of that, now it's like, okay, I need to help a CFO make better decisions. Great. All that data is now sitting in Hanover park to help you make better decisions. On top of that, maybe in the long term it's like, how can I unlock alpha for the investment firm? How can we have this investment firm make better decisions on top of all the source of truth data that Hannover park has? And so that's kind of how I think about the layering from most unsexy to most sexy.
- [15:55]
A
And so what makes it so hard to make a general ledger? Because it's just like some accounting, like, it's like debits and credits. Like, I don't know, it just seem, it doesn't seem that hard.
- [16:02]
B
Yeah, I know. So I think partnership accounting and this is tune out if this is the most boring thing you've ever heard ever. So, um, part, there's a lot of complexity with fund accounting. And so we're kind of like, okay, build debits and credits for a simple small business is like table stakes, honestly. But saying, okay, I have all of these different limited partners in a fund. They have different allocation percentages, they have different side letters waving economic terms. They have blockers and splitters and aggregators, and they have 50 legal entities for one fund. All of that complexity of the interaction between all these legal entities and all of the partners in those entities gets crazy.
- [16:35]
A
And then there's multiple funds sometimes too, right?
- [16:37]
B
Dozens of funds. And then you have a management company that needs to talk to the funds. And so I think the complexity lies in like, think about these investment firms as the most complex financial institutions in the world. And organizing that data is crazy. Right? And so we kind of had to build a system that can handle the most complex investment firms in the world.
- [16:55]
A
And is this sort of why it was just like a. Let's just throw some bodies at this and people just manually do it? Correct.
- [17:01]
B
That's kind of how it works. And I think a lot of the underlying tools that were built, there's some like, specific fund accounting tools that people had tried to build but it's like the problem is there was a disconnect between the people doing the work, the fund accountants and the people building the product. Random engineers at a different company. That disconnect created tons of problems because no one's actually talking to their quote unquote customer all day. And so what we've done is said, hey, we have this 60 person room in Flatiron where we all go to every day called an office. Let's all put the best fund, I call it the Navy seals of fund accounting, alongside lead engineers to kind of work in harmony.
- [17:37]
A
The last time you came on the podcast, we had an interesting conversation where the traditional fund admin sees an engineer, they call them the IT department. Your job is to get people access to the HR system or something, or sign up for QuickBooks and generate someone an account on the different software.
- [17:57]
B
I love you talking about fund accounting. This is hilarious.
- [18:00]
A
Well, and so, so is so just basically like who you're competing against. You're like you are an engineering product led company that is competing against people who think about it as an IT department.
- [18:12]
B
Yes.
- [18:12]
A
Basically like it's not. It's like a back of house versus front of house thing.
- [18:15]
B
Yeah, I think, I think, I think about like, of like if you're one of the greatest engineers in the world and we've like built this hacker culture, you know, it's only dropped out of Harvard. You know, he was sophomore in college. We have a team USA drone racer. We have people that have multiple multip ex founders, former and future founders, I call it. So like we built this like really talent dense engine product team. Those people would never in their wildest, wildest considerations or nightmares join a legacy fund admin who doesn't care about them. And so our goal is like, how do we build this financial infrastructure for the most complex firms in the world? If RAMP can make expense management sexy, we can make investments sexy. And so I kind of think about this as like the most elite engineers on the planet will never join a legacy fund admin because no one cares about them there. What we've done is say, how do we build this world class team of engineers, people that drop out of Harvard, Team USA drone racers shout out JT. Former founders, future founders. Like people that are top 1% that might join an AI lab say, Hey, I have this deep obsession with building for FinTech and building for the most complex investment firms in the world. This is a series of insanely hard technical challenges. When you think about the data complexity that we have, let me go do this here. That's very different, obviously value prop than a legacy fund Admin.
- [19:35]
A
Yeah. Okay, so you've built this environment where the top 0.1% of engineers want to go. How do you convince people to join? And then maybe another interesting thing to hit on is how has that changed over time? If somebody listened to this first conversation, they can hear your original philosophy. What's changed over the past year?
- [19:52]
B
Yeah, I think I kind of say growth solves a lot of problems. We went 0 to 15 billion in 21 months since our first line of code. That level of growth proves to the most skeptical engineer on the planet, like, hey, this is working. And if I have a deep interest in fintech, this could be compelling and interesting. And the second piece is you are what you prioritize. There's a lot of companies who have a hundred people on the team and like 80 salespeople. That is not the company that I'm building. I have still scaled us to 15 billion of assets with no other salespeople in the team. Primarily because I'm like, I'm just a founder with a product and a plan. We don't need an army of salespeople. That resonates with the best engineering teams and the best engineers on the planet because they're thinking like, okay, what is prioritized? What is hired for? If this is an eng first hacker culture, that matters deeply. When I think about how I'm going to be prioritized, first class citizen, et cetera in the type of company I'm at, versus an army of salespeople that are pushing on engineering when it comes to building.
- [20:56]
A
So then how do you guys figure out kind of what to build? When you're talking about the engineering being first class, are you. And it sounds like it's literally just you. Are you talking to customers? Are engineers joining calls? Are engineers like using demoing the products? Like, I know I've seen, I think I've seen something around like when I was hanging out in the office one day, like, everyone uploads stuff or something. I may be remembering the story wrong,
- [21:21]
B
but so we have demo night every Friday night where literally people are like showing what they're building both to the fund accounting team as well as on the engineering side, which is really fun, but kind of how we think about what to build is we have a slack channel with every customer. I literally, I said I live in constant paranoia that my customer is, you know, is finding a better solution. Just like this Jeff Bezos quote of like, oh my God, live in Fear that you're not, that your customer's like unhappy, that they'll find something better. And so like, we constantly want to be like pushing the envelope to invent on our customer's behalf. And so we take that super seriously. When it comes to feedback and being in a Slack chat with every customer, our engineering team is like blown away by like how much this matters for the cfo. If we are their most important vendor, the things that we deliver for them can really change everything. And so like, the level of importance creates a sense of urgency, especially on the team. And so, and then on, on what we're building or working on, it's like, you know, we really said start with the unsexy Automate Core Financial reporting, Automate Core Fund Admin. And then now we built like a series of portfolio management and portfolio monitoring and all the adjacencies that like should live in one place that haven't. But stay tuned for more stuff.
- [22:27]
A
So can you give me some examples if I'm not super familiar of like what some of those tools might be and like what I'm using them for?
- [22:34]
B
Yeah, so say, you know, you invest in Hanover park at the Series A. You know, you get a set of legal documents or cap table or something like that. Typically these legacy providers, all they do is like save that random those docs randomly random box.com or Google Drive or something super random and be like, oh yeah, like, I guess I'll look at that if I need to look at it for audit at the end of year and they'll like book some super boring accounting stuff that the CFO doesn't care about.
- [23:02]
A
Sometimes there will be like a shared drive though. You can access it from like your browser and you can download it, you
- [23:08]
B
can download, you can download the file. And so we said is, we were like, amazing. We have this leverage position because we're doing our fund accounting that we have all those docs in real time. And so you just forward that over email to us and say, hey, I don't need to click 50 buttons in a UI that was built in 2018 to create more work for me. As the CFO, I can just delegate to a Hanover Park AI email agent. That email agent reads it, it uploads it, it AI extracts and process like 150 key terms. And so now I've enriched and been like, hey, not just cost and fair value, I have. How much do I own to this company? What's the ownership percentage from the cap table? What's the latest valuation? Post money valuation who are my co investors in the deal? Right. Like, all these other, like, important details that should live in one place that don't. And so we bundled this like quote unquote, AI portfolio management tool in for free alongside the core fund admin services.
- [23:57]
A
And I think you mentioned it took you about nine months to kind of make this. Am I remembering that number right?
- [24:01]
B
Boy, yeah. There's a. So this is a very complex technical. Like, if you're an engineer listening to this, it's like you want the hardest technical challenges in the most complex industry. Like, this is the place for you. We've processed 200,000 documents at this point. I'm talking random Indian language docs where AI translating into English and like all this crazy complexity in the pursuit of how does the customer lift zero fingers? Just forward it over to us and let us take care of the rest.
- [24:34]
A
What was the hardest part about doing all this? Is it natural language processing extraction? Is it organizing it in a sortable, efficient way?
- [24:46]
B
The extraction is really complex because it's really simple. If you're doing a Series A in the United States like we did, but. But like, if you're doing a deal in Europe, if you're having a random mistake made by the lawyers on the cap table, okay, if we have like a random Excel file that doesn't make it in, that we don't get access. And so there's just like, I call it the land of Infinite Edge cases, which is just like highly complex documents that like, you know kind of what the answer should be at the end potentially. But it's really, really hard to figure out with all the different legalese that's in there. And so that was part of the. Part of the challenge.
- [25:19]
A
So you walk into the office at Hanover park in the morning. What's it like?
- [25:23]
B
So at 9am exactly on the dot, I literally walk out of my office and we just have a speaker blasting music. My team will hate this, but it's literally one of two songs every single day for the past 21 months since we founded the company. It's One More Time by Daft Punk or it's Levels by Vici. There was a period where we shifted a little bit, given literally my entire team now says to me, these are the songs that I never want to hear outside of work ever again. But we do that. And so it's a fun environment where we're literally blasting music. We go right into engineering standup. We then go right into the accounting team stand up, and we kind of get right into our day. But my goal is, how do we create this overwhelming sense of energy and how much we're building and how fast things are moving?
- [26:09]
A
Is there a gong in the office?
- [26:11]
B
How did you hear about this? Tyler? You heard about the gong? So. So we have this gong in the office. So we. We've moved off this three times in under a year. It's been very entertaining for. For everyone involved.
- [26:21]
A
I actually haven't seen the new one yet.
- [26:22]
B
You haven't seen the new one?
- [26:23]
A
How close is it?
- [26:23]
B
Yeah, it's right. It's right near here.
- [26:25]
A
Okay. It's literally like, can I stop by, like, right after. I want to see it right after the site and I'll head to the airport.
- [26:30]
B
So. So we have this. We, like, in our first office, which was this tiny little office in Fi Di, we had this, like, gong. Anytime we would get a sale, anytime something great would happen, we did this. Now we've moved offices to much bigger offices and we still have a small gong. We've gotten people to say, why do you have this tiny gong? You need to have a bigger gong. Adam Newman. We crash style. We have not upgraded yet, but the gong is very. The only people allowed to bring the gong are one customers. And so we literally had a customer in the office the other day. And I told Johnny, I was like, johnny, I know this sounds really weird. I'm going to now interrupt the entire team of what they're doing. And they have to ring. You have to ring the gong. So he comes over, he rings the gong, and the entire team goes wild. Like, literally, people are cheering their. Like, I think people are gonna, like, jump on top of their desks at this point and people are getting fired up or we ring the gong. When it comes to, like, we ship some massive product update or close the sale.
- [27:28]
A
And so those are the only people that are allowed to ring it, right? No outsiders.
- [27:32]
B
No outsiders.
- [27:33]
A
I technically cannot ring the gong.
- [27:34]
B
No investors.
- [27:35]
A
I'd have to be a customer.
- [27:37]
B
You'd have to be a customer, which
- [27:38]
A
I need to hit that institutional sky. I don't have a CFO. It's just me.
- [27:42]
B
We're just CFOs.
- [27:43]
A
Soon. Soon. We'll be on that level soon. And so you had this one guy who I think he biked to work during a snowstorm one time or something. Like, what's the story with that?
- [27:56]
B
So I gotta give a shout out to Philip. We literally. It was like a Sunday at 2pm There's a crazy blizzard happening in New York City. And of course, I don't Expect people to be in the office. Like, this is like hunker down and survive. Somehow. Philip decided to go and rent a city bike and bike in a 10 inches snowstorm to the office. And he shows up. He's like, I just biked here. I'm like, how are you alive right now? And he's like. Just goes right to like coding. And he's like, I'm good. I'm just biking. So I'm like, okay. This is what we screen for though. We have forces of nature that are figuring stuff out.
- [28:35]
A
Was the subway like down because there was so much snow or like, I
- [28:38]
B
think he's anti subway. That's what he is. He's not a subway guy. He's like a bike guy.
- [28:42]
A
Interesting. I mean, the streets would probably be open, like very clear. You could probably just keep cruising. You probably wouldn't have to stop.
- [28:50]
B
Yeah, like maybe. Yeah, it's crazy. It's like if. If it even got plowed that day.
- [28:54]
A
So then what do you guys do on Friday night? So you have like a Friday night thing that you do.
- [28:57]
B
So we have this thing where we love to celebrate, like our product velocity is everything. Right? Like, we're literally doing multiple releases a day, I would say compared to many legacy players who call engineering it and don't actually ship net new product. Our goal is like, how do we have the highest product velocity out there? And so we have multiple product releases a day. And what's really fun is we have engineers demo what they built like every few weeks on Friday at like 6pm where they'll literally like, everyone will huddle around what we call the podcasting couch. It's not actually for podcasting, but we should have done this on the podcasting cast. We have this massive couch, which people have gotten excited about that. Literally everyone goes onto that couch and we demo the latest and greatest and people go crazy. We're playing music. People are getting fired up about what's going on. And so it's been a fun little ritual to inform the broader team as we've scaled a lot in terms of team in the past six months to tell everyone what we're working on.
- [29:54]
A
So this is not a hackathon, random side project type of thing. It is. You're showing what you built in the product.
- [30:00]
B
Exactly.
- [30:01]
A
Okay. And you said you're shipping multiple things per day. So is it Friday? You spend like an hour and just everything that was shipped, people just kind of go through and show what they shipped.
- [30:12]
B
And there's a lot of times when people get Feedback. So, like, we'll ship something and it'll be like an iteration. And the fun accounting team, like, oh my God, this could be amazing with these two changes. Or hey, we get CFO feedback and people are excited. I actually want to start bringing on, bringing customers to the office for these Friday demos to see the latest and greatest. Because, like, what we've had is like, I had a customer call me and be like, hey, you're our most important vendor. I love Hanover Park. I don't think anyone's ever said that about a fund admin before. Or like, I love Hanover Park. Can we host a customer conference at the office? And can everyone just like, jam and huddle about, like, what the future of finance can look like in this space? And so we've not done that yet. Stay tuned. But it'd be great to get more like live feedback at these demo nights.
- [30:54]
A
So when somebody comes across Hanover park, what is like the reason that they choose Hanover park versus? I mean, there's a couple other options that are out there. Like what is usually the discovery process of finding it and then the decision making process.
- [31:08]
B
Usually all the problems come from as you're. If you're just, you know, a $50 million venture fund and it's super simple and it's one person in a room, like, things are super simplistic, like, there's not a lot of complexity. But as you scale, all of these manual processes break. And so you're like, it went from, oh, I did this one manual process for two hours a month to I'm doing five hours of manual processes a day just to tread water. And so therein lies the problem with all the legacy players, where things are break, broken and held together by legacy human duct tape and Excel, right? And so that's problem one. It's like, oh my God, I can't scale. Problem two is like, I've heard of all these good things about AI. ChatGPT's out, applauds out. But what has it even done for CFOs? Nothing, right? And people are frustrated by that. And so it's a combination of things are breaking while we scale. And oh my God, how can I adopt AI? And so we're kind of at the intersection where it's like, hey, instead of buying a random army of overpriced SaaS tools on one side to complement a broken system of record, which is your core fund admin today, why don't we marry that into a single source of truth where you can expose all of your data to an MCP via, you know, LLM to Claude or ChatGPT or Gemini and like be able to action on your data. And so it's this like, oh my God, my data's super stale. Everything's broken. As we're scaling, I have no idea what's going on. I have no visibility to oh my God. The only way to duct tape this together is buy 20 other SaaS tools and we solve both those problems.
- [32:38]
A
Isn't it really hard to, to switch a fund admin though? Like, it's gotta be one of the most difficult problems in the history of humanity.
- [32:46]
B
So I joke, I literally on like I'll be on like a first call with a CFO and I'd be like, look, I know I'm asking you to marry me on the first date, but here's what we're doing, right? Because like it is a. And I take that like insanely seriously of like the level of trust that our customers put in us. Like, that's what keeps me up at night, right? Of like how much I care about, about their trust and, and what that matters. And so one, it's a massive decision. Two is oh my God, Hanover Park's amazing, but isn't it such a pain in the ass to switch? That's literally what everyone says.
- [33:15]
A
That seems like that would be the disqualifier. Like, seems cool but like, I don't want to do this.
- [33:19]
B
I don't want to deal with it. I'm not going to put up with this. So I'm, I literally tell our team like, we're building a one click migration future today. It's not one click. Obviously we did migrate someone in, you know, only a handful of days, which was pretty crazy. Shout out mackenzie at Asylum Ventures. She's amazing. And so we did that. But our goal is now like, what's possible with AI is like, you know, there's a lot of Long Horizon agents that can run for hours and hours and days and days. And we're experimenting right now on how that can supercharge migration. And so I see a future where we get to one click migration.
- [33:51]
A
Really what needs to happen, you think to get there just do the models have to get better? Does the context windows have to get longer?
- [33:58]
B
I think it's just if you're a world class engineer that's looking at this all like, this is a example of like a really fun technique technical challenge to work on, which is like super challenging technical problem wrangling the most complex financial data in the world. It's really just Like ENG bandwidth, plus some pushes on the frontier of how do we think about these long running agents that need to operate over days and weeks, not minutes.
- [34:22]
A
So that is probably the big kind of just overarching problem that people are trying to solve right now is cracking how to speed this up.
- [34:29]
B
Yeah, I think it's a massive problem that traditionally people like hired an army of humans to solve it. And it's like, well, if that doesn't deliver a 10x better experience, like what would? And I think there's an opportunity to do that.
- [34:40]
A
And I know there was a time where you, I think when you, when you first kind of started the company or getting customers and it's even like harder ask. Back when you started it, you, I think you promised that you'd literally sleep in people's office until the migration was done. Is that still a thing that you promise?
- [34:56]
B
Or so I, People have been like, don't sleep in my office. What are you talking about? I don't want you here, Chris. I don't want to spend more time with you. So it did. I'll never forget though, one of our earliest customer. And like, by the way, I have like a crazy place in my heart for like our earliest customers that trusted us with their most important financial data. And I was one of our earlier customers and I'm on a call with him on like a Tuesday and he's like. And I'm like, hey, where do you, where do you live? Where are you? And he's like, why are you asking me where I live? And he's like, he's like, I'm in this random town in Florida. And I'm like, okay, I'm booking a flight right now. I'm coming down to Florida. This is like the first call. He's like, who is this guy?
- [35:33]
A
I'm like, he wasn't a customer yet, no prospective customer.
- [35:36]
B
And I'm literally booked a flight and I go and literally me and him spend like 5 hours at his house till like 2 in the morning, basically like talking about how the future of finance is possible. They became one of our earlier key critical customers and has been like a massive advocate for us. So credit to them and kind of like what happened? But in the early days, like, do whatever it takes to win.
- [36:00]
A
What did you talk about in that five hours? Like, what was the biggest takeaway?
- [36:03]
B
Everything that was broken about the current, you know, system. He had been, you know, using a legacy fund admin. He had been duct taping additional tools on top. And because a lot of the Problems is like, oh my God. This might be surprising for the audience, but like CFOs don't have visibility in real time of anything that's going on. That's crazy. Think about you're making $100 million investment decisions, but you don't know what's going on today with your data. And so he was constantly struggling with I have no idea what's going on. I'm asking these humans to book cash and do super basic things. It gets delayed by weeks and weeks and weeks and months. And I tried to buy another SaaS tool, but it had the same problem because it didn't talk to my underlying data. Right. So it was just a frustration layer. And with what's possible with AI now, like, I think now is the time where we should solve that problem.
- [36:48]
A
Speaking of real time data, I have another portfolio company. She was just on the podcast a couple weeks ago. Arty. They basically enable real time data, basically syncing between all your databases. The data warehouse. I don't know if you guys have tried it yet, but I'm giving a plug. I'm giving a plug.
- [37:04]
B
This isn't Pod plug. Have not tried it.
- [37:07]
A
You've not tried it. It might be interesting. We can maybe talk about it after. I'll throw a link in the show notes if people want to check out that episode. But basically like their thesis is if you have AI agents that are like doing things automatically, you just need real time data. Everything needs to be synced. Because if something's off by let's, you know, let's say you have to wait for a sync or the data's off and the agent starts to make a decision. Like you're making decisions and it's just doing things with incorrect information 100%. So you mentioned getting on the plane, you jumped on this plane, went down and talked to the customer in Florida, spent five hours at his house. That's something. The first episode we spent a lot of time talking about what you had learned about sales. Before you started Hanover, you spent some time at meow. I don't know to what extent we should re hit on that stuff and to what extent we should talk about how you're thinking about understanding how to sell things. Understanding customers has evolved over time. But it may be interesting for the first people hearing this for the first time, what was Meow and what was your journey like there?
- [38:09]
B
Yeah. So ended up joining Series A Fintech that was doing business banking. Helped us scale from, call it like, you know, 10 to a thousand ish customers became chief revenue officer of the business, Brandon and Bryce, the founders of meow, were the first checks almost pre idea into Hanover park today. And so ton of like, you know, respect and credit for them, but it taught me a lot. It literally like SVB collapsed. We scaled exponentially, you know, closed hundreds of customers. Myself personally and like, you know, I wrote this like almost manifesto which I call like always get on the plane that I think has like become popular now. I think people are just stealing my tweet and like retweeting it. But it's like, you came up with this. I came up with this, yeah. So I wrote this thing of like always get on the plane. And the key principle is the following. If you are asking someone to trust you with something as important as what we build and what we sell, the fact that if I won't get on the plane to spend four hours in a room with them, like this is a decade long relationship.
- [39:04]
A
Yeah. Can they really trust you if you're not going to do that?
- [39:06]
B
And it's like I can't build trust over a zoom call. Right. And so we, I like did this, I popularized it and now like it is like one of the key philosophies, especially for us. And so, you know, I was in, there was a 10 person finance team at a massive private equity firm that we're talking to that like I literally told him, I was like, I'll just go to your office, wherever in random place in California and like I'm going to be there for five hours with their whole finance team. After five hours you really get a chance to know someone and you build that level of let's just be honest with each other about what the trust and the blunt feedback is. And so I've obsessively been focused on this always get on the plane thing. And I'm glad to see people are taking it.
- [39:44]
A
Yeah. So how do you manage that though? You're trying to run a company, you're trying to hire and recruit people and then suddenly in two hours you got a flight you got to jump on and you're spending two days in a random town in California.
- [39:59]
B
So I look, time management, prioritization, there's just like, there has to be like a level of like, okay, how do we think about what is the highest ROI thing? I think a lot about like I've taken a lot of inspo from Elon on this of like, what is the limiting factor in the company and then how do I parachute myself into the biggest problem and how do I take that and like obsess over that problem until it's solved. And so, you know, limiting factor is migration. We need to go like parachute in, work with our head of ops, Emily, who joined and like obsess over what does AI native migration look like. Right. So at different times, whatever the limiting factor is in the company, my job is like, jump into battle and figure it out.
- [40:37]
A
One of the things that you've done really well, people call it founder led sales, where you're like, I think you said you're the only person that's like on the sales team still.
- [40:45]
B
I don't know how. I'm just a founder with a plan. I'm not even a sales guy.
- [40:47]
A
Yeah. So. And maybe it's like not sales, it's just like trust building. You're trying to understand customers, trying to solve their problems. So what have you. What's been the biggest learnings you've had over the past 21. I was gonna say 21 years, 21 months since you. Since you wrote the first line of code and started onboarding customers.
- [41:04]
B
Yeah, I think for. And we're definitely in founder led sales mode too long. We're at 15 billion of assets on platform. That's probably a little too long. And it's just been, it's been something I've held onto just given how critical and customer trust is and how that interacts with like product and eng on that side. But for me, I've really tried to transition from how do I get our first 5, 10, 15 customers into a position of like, how do I make sure that these people can become raving fans? Which I think is like very different philosophy. And like all the worst parts about sales in general of like, I'm just trying to get them like some sales guy with commission. Obviously I'm a founder with no commission. And so like, you know what I think about is like, if our number One goal in 2026 is every customer is a raving fan. That is very, very hard in our industry. That's like the craziest thing ever. Right. And so with how unhappy most customers are at their current providers. And so my goal is that how do we set and manage expectations prior to signing any contract to ensure that they can be successful in their first hundred days plus. And so it's a lot of been like, hey, we've proven we can do it with your peers, with your counterparts. Here's five other customers that are exactly like you guys that we can service. How do we make sure that you're a raving fan in 12 months.
- [42:20]
A
You mentioned it was different getting the first five to 10 customers and making people raving fans. How did you get the first couple people on board? Because you had built this general ledger from scratch. You had no customers, and then suddenly you're like, hey, trust us to manage your fund.
- [42:38]
B
So I gotta give a lot of credit. I'm gonna give a shout out to Chad at suse, founder of Suse Pratousche, Kenny, who's their cfo. I love you, Kenny. You're literally like, he was our. They were our first customer. And so I literally was like, hey, we're doing this. You're our first investor. They didn't want to move over everything to start. That's a crazy thing to be like, hey, move over all of your funds to an unknown provider called Hanover park that you invested in a seed round for the most important thing for your firm, which is all of your LP relationships. And they were literally, like, it took some convincing, it took some trust building, but they ended up doing it. And that was obviously a critical kind of first customer. But the people after that, it was like, hey, I will literally do whatever it takes to ensure that this is successful. I don't care if I need to sleep at your office. I don't care if I need to book the entries myself. It's just all about, hey, we're taking this journey together. Here's why this can be a super compelling future. But look me in the eyes and say, I will deliver for you. And that's how we got the first five or 10.
- [43:45]
A
And you had this concept of. I think it's called polite persistence. Is that the phrasing?
- [43:49]
B
Yeah.
- [43:51]
A
So was there a lot of that? You had to continue to be getting in front of people, Continuing to. What was that process like?
- [43:58]
B
I mean, text call, carrier pigeon, email, LinkedIn, DM, Twitter. It was really anything. And, like, I kind of see, like, in the earliest days and even now, it's like, whatever it takes to win do. And I think, like, people don't take that seriously enough of, like, I think any company, it's like, you should have a level of obsession and desperation where it's like, I will literally do whatever physically is possible to make this happen. And so we've, like, I took that very literally, like, 10 texting, calling, voicemails, whatever. And, like, because the reason why I did that is, like, I know that this is the right future that you should be moving to. I know this is scary, but, like, we got you. We're gonna execute well for you and we're gonna make this happen. And so that was a lot of the early like trust building plus just like obsessive play persistence.
- [44:46]
A
How do you avoid being annoying in that process though? Because when I have somebody that's constantly like, hey, did you see this message? Like, hey, I'm just following up, like I usually kind of start to tune that out.
- [44:57]
B
Yep.
- [44:57]
A
Like, so how do you, how do you not do that?
- [44:58]
B
A lot of jokes. Yeah, yeah. Like if someone's like calling you, being like, hey, me calling you, hey, it's me randomly calling you Turner, I'm sure you're really excited to hear from me right now. There's a little bit of humor and fun to it of, hey, it comes off as very authentic if you actually believe in what you're building and selling versus some random sales guy who's sending friendly follow up 58 times which no one cares about. And so that's been a lot of the focus, which is like, how do I build trust while also being persistent?
- [45:29]
A
And so now you're making this transition to making people raving fans. How do you be a raving fan as a cfo? What are you happy about? What are you telling your friends in the CFO group chat of Hannover park is so great.
- [45:43]
B
There's the three elements to a raving fan that I think about. One is amazing onboarding, deployment, migration. That's the one click migration thing we talked about earlier, which is like, how do we make this experience where literally you sign a contract, you give us data access and you put your feet up on the table and never think about this again. That is incredibly challenging. Right. And we've done this now for customers and people have been like, you told me migration wasn't going to be bad. It's amazing. Right. So that's the first piece. The second piece is taking the fund admin services from reactive to proactive. And so how do we use AI to supercharge services delivery? By saying, no, I don't need to wait days or weeks or months to see this action happening. I can see things in almost real time. Right. So that's the second piece. And then the third piece is jaw dropping AI native product experiences. And so it's not good enough to just deliver fund admin or the core service delivery. It's how do we unlock and build something magical on top of that data that no one else could offer. Right. And so that's been the three elements and hitting those are things that I like care deeply about. Tracking and monitoring and focusing on was
- [46:51]
A
There a time when you kind of knew things were kind of working, like you were just getting the scale, sort of tipping towards more positive feedback and momentum versus not.
- [47:02]
B
Yeah, I think after 5 billion of assets, now we're almost 15 billion. After 5, things started moving downhill. Ecosystem started to pick up of people being like, have you heard of this Hanover park thing? Despite us doing not a ton of marketing aside from me tweeting and posting on LinkedIn. Right. And so we started to get this like, positive momentum in ecosystem of like, oh my God, this could be the future. The idea of vertically integrating the core accounting system and building all these magical moments on top could be possible. And so that's when things started to kind of snowball. And then now it's just been like, let's make sure we can catch the snowball rolling down the hill and kind
- [47:37]
A
of hitting on the. You're the content that you post online. You are probably one of the. If somebody were to say, who's a founder that's doing founder led content? Well, I'd probably send them your profiles and just check out what Chris is doing, follow his stuff. What's been sort of your process for thinking about things and then maybe even you started making content online before you even started Hanover Park. So what's that kind of whole journey for you in like.
- [48:02]
B
Yeah, so the quick primer and background on it is. Was a college kid at Yale, literally was like, okay. I was reading it and before Sam Altman was cool, in 2020, he wrote this blog post, like, how to pre.
- [48:13]
A
Pre. Chatgpt.
- [48:13]
B
Pre chatgpt. Pre. He was cool. He wrote this blog post, how to be successful. And I like obsessively read that and was like, this is insanely cool. And I was like, okay, this startup thing might be interesting, but like, my dad sells commercial insurance, had no background, no ecosystem, nothing. And I was like, okay, there's really two ways you add value in early stage. Writing code or selling code at the early stages wasn't a good eng. So I wanted to figure out distribution sales and said like, how do I like write compelling content on the Internet that like people would actually click on, watch, listen to. And so I did this whole interview series where I interviewed Emmett Shear at Twitch and you know, Michael Seibel at YC and you know Kevin Ryan who founded MongoDB. And I turned all that into Twitter content that went super viral and so built the following to a few hundred thousand people over the past few years. And but like, when I started Hanover Park, I was like, I Actually don't care about virality, which is a little bit contrarian. Like it doesn't matter if Elon retweets me, which he did one time, which got me like 50 million views or something. That doesn't matter. It's actually like, if I'm trying to use this as a way in which CFOs find us, I need to write for them, which is obviously a much more niche audience than some random hustle.
- [49:21]
A
Tweet about whatever you're tweeting about the accrual based accounting method closing faster. The average person reads has to block you.
- [49:30]
B
Please block me? Yeah. They're like, block Chris. And it's really the problems that a CFO faces of. You're up at 2 in the morning, your LP calls you and says like, this number's wrong. Do you ever want that problem? No, you don't. Right. So it's a lot about that in terms of like how I think about the positioning and how I think about what we're doing. And so like one of our largest customers came inbound off a LinkedIn post that had 10 likes.
- [49:51]
A
So it's really not about going viral. Like going viral is not how you do founder led sales. It's resonating with the problem that your customer is facing.
- [49:59]
B
It's really just obsessive. Like all I do all day is talk to CFOs, they tell me their problems, they tell me some of the things that they're having issues with and then we try to invent the future for them.
- [50:08]
A
Do you then take that feedback? So you take that feedback put in the product and you also. I feel like a decent amount of your content is like, I just talked to a CFO at a billion dollar private equity firm. They said this and that's the content.
- [50:19]
B
Yeah, I kind of think about it as like any conversation that I'm having could turn into content. So like the frame I have on this is with all the AI slop out there, you should only be writing and creating content of things that no one else could create. And a lot of that is like personal conversations. And so like I talked to the CFO about xyz, here's what I learned. No one else had that conversation that day. Right. So it's a lot about like, how do I. In a world of abundance of content, how do we have something scarce?
- [50:45]
A
Do you keep like some sort of document or note where you'll like dump ideas in and you come back and visit it? Do you like plan it out Sunday night, write some Content for the week.
- [50:53]
B
What's your process like in real time? I'll like jot down things as we're, as we're like, as I'm having phone calls, conversations, etc. And like that will be like the fodder for the week's content.
- [51:02]
A
And so I think we maybe hit on this a little bit earlier. I actually don't even remember if it was before we started recording or not. But you talked about, there's a lot of the advice you kind of got or read about and heard about starting a company and building a company. I think you said like 99% of it just ended up being wrong. What's kind of the advice that you found is most wrong?
- [51:25]
B
So I think yeah, my take on this is I think almost all advice, like 99% of advice on scaling a company is incorrect right now. And so the traditional advice is like, oh my God, delegate everything. You know, hire this massive team, hire like VPs to do different actions and whatever. And I'm like a lot of that is noise and basically creates this like hierarchical political system by which like people do well by figuring out ways to take credit. My goal is like how do we do the anti that? And I took a lot of inspiration from, from Elon on this of like be at the bare metal as much as possible. Like literally like don't talk to like three levels of whoever. It's like talk to the engineer writing the code on this like AI email agent and how this works, right? And like figure that out. Because the problem that creates like if you don't do that, you create frustration for your best performers. The best performers like want a hard problem, they want the room to run and like go cook on that problem. Right? And so we've like really been anti this like hierarchical system by which like information is filtered in different ways and say like, let's just cut to the source and go direct.
- [52:32]
A
Isn't there an argument though that you kind of like quote unquote need like a grown up or like quote unquote needs someone who's kind of done it before and knows the playbook. If you don't, if you don't have like the VP that's you know, done this before and can like share the knowledge with the team or knows what it looks like, do you miss out
- [52:49]
B
on that or I think what's changing a lot now with like what is it mean to build a company in the AI era, which is very different than I think the SaaS era of the 2000 and tens which is like the playbooks are being rewritten. What's possible is different. It used to be you have a massive sales and marketing team, now you have inference cost and that's your sales and marketing team. And so a lot of this is I think changing of like instead of being an army of gtm, you have like the product does the talking. Right. I think it's changed a lot. And so you look at companies like Cursor that have scaled crazy with a very small go to market and sales team. And so I think a lot of the playbooks are changing, which means someone who's reusing a playbook from the last era is probably going to be not effective. However, that doesn't mean we have multiple people that have been at companies that have exited before. They've been senior engineers. There. There is some level of how do we counterbalance the hacker culture of the 20 year old who drops out of Harvard to you know what I call like the experience. Like I've seen all these infrastructure problems at scale on the engineering side and then obviously on the fund accounting team, like we are obsessively focused on bringing in expertise at the, for like the Navy Seals of fund accounting. With like that obviously requires a different level of experience in terms of how situations have been adopted over time.
- [54:04]
A
Are there any things that you try to do based on, you know, someone said this is how I've done this in the past and it went horribly wrong. That you feel like hopefully people can maybe learn from. Specifically with the way that building companies have changed over the past couple years with these AI native businesses.
- [54:20]
B
Yeah. I think honestly one of the things that we preach every single day is this idea of one way doors versus two way doors. Jeff Bezos invented this where it's like a one way door is like if you make a decision in this way, you literally can't go back. It's impossible. So an example would be the investors you have on your cap table. You can't get rid of them, right? They're one way door, they're here for the life of the company. The two way door is hey, we can make a decision, it's easy to go back at any time. And those are almost all decisions in a startup. And so what we've done is like drop your ego to the ground, be intellectually honest about truth seeking of like what's the right answer to the company and make a fast decision because you can always revert back really easily at any point in time. And so like empowering the team to say make really fast two way doors without bogging it down in process to create a committee to figure out if that makes sense to make a decision. It's better to have iterated five times before the committee even gets out of bed.
- [55:13]
A
How do you know if something's like a one or two way door? Like is there a gut check on like hey, we know this is reversible or won't blow up the product or customer trust or something like that.
- [55:24]
B
Examples would be like shipping an internal accounting update for our fund accounting team is very two way door. If it doesn't work in five seconds, we can update it and nothing changes.
- [55:34]
A
Right?
- [55:34]
B
Where it's like, you know, one way door is like a massive change for LP Portal, right? Which is like what the massive endowments and banks in the world log into every day across our 10,000 different limited partners. And so I think it's more like that's on the product decisioning side of like okay great. You know that is still a two way door because you can revert quickly but it's something that we'll take a little bit more seriously.
- [55:52]
A
And so you started initially you kind of mentioned SUSE Ventures was the first
- [55:57]
B
customer one shout out, shout out to
- [55:59]
A
Chad and Pratush and Kenny and Kenny.
- [56:01]
B
Kenny's a legend. He's the one with all the credit.
- [56:03]
A
Nice. I've never met Kenny before. Next time, next time I'm near the office, I should try to do it, try to meet all of them or try to meet Kenny. And so how did you kind of expand customer base over time because you first couple customers were all VC firms. You seem like you kind of have like been like laddering up almost. I guess I don't know how to describe this. Like what's the process been like of expanding?
- [56:24]
B
Part of our goal is like we want to build for complexity which is like the most complex firms in the world have blockers and splitters and aggregators and triple parallel funds and UK subsidiaries and different currencies. There's all this noise, right? If you were just built for a $10 million venture fund, obviously you are not the right partner and customer for them or customer fit. So what we've done is we said okay, we need to solve this cold start problem. We need to get our first 10 customers. We're going to do that in venture capital. But we've quickly expanded into other asset classes like private equity and soon private credit as well as where we knew the needs are much more sophisticated. And we built for that future and now has been like Kind of a great opportunity to expand in these different types of asset classes. And so we're launched, we launched a product recently, breaking news on AI native waterfall modeling. And so in natural language, I can run my deal by deal waterfall if I'm a cfo, which would take hours and hours and days and wrong and it's not correct. And it's like seven different system exports that we've made instantaneous in natural language to run these scenarios. And so that would be a product that a private equity firm would fall in love with.
- [57:27]
A
So how do you know that something like that is accurate?
- [57:29]
B
Yeah, great question.
- [57:31]
A
Because I fuck it up even when I make it manually in Excel. Like I'll like forget to drag a formula and I'll notice it like later like, you know, error checking everything. Yeah.
- [57:41]
B
One of the key product principles of the company is what I call like trust but verify. And so it's like, it's not like if you just give someone a number, assume every single cfo, they're the most skeptical people on the planet, they're going to assume it's wrong. You need to be able to have them click into it, export, run their own calculations to like verify the accuracy of a number. And so you know, the trust but verify approach on the waterfall modeling plus the explainability, like the beautiful thing is like AI can tell you where the work's coming from. It can say like, hey, we went through these three different tiers of our waterfall and here's exactly what happened. Right? And so that plus the auditability and explainability has been a critical kind of pillar.
- [58:16]
A
And it's all you. When you export to Excel, it comes with like linked formulas and everything. Am I remembering this right?
- [58:23]
B
Yeah, I mean this is actually really fun. I think there's been two different approaches in the market when it comes to this. One is, hey, it's a bunch of manual like humans running around with like really big Excel files. That's one. The problem with that approach is it's very error prone and manual and slow, but it gives you some auditability because it has formulas. The other approach, which is like a very 2018 SaaS approach was like, hey, I'm going to give you just a ui. Great. It's at least something, but it's just hard coded export randomly with no connectivity. We don't think either of those are the right solution. So we actually built an Excel replacement in the browser. Similar to ramp sheets or try shortcut. There's these tools that do this. Like generally we built this specific for our industry for fund CFOs, which enables us to instantly generate all the financial reporting without having to go into this crazy offline process. And so we think we've kind of married, like, best of both worlds when we think about the reporting aspect, with the auditability of, like, formulas across the different Excel replacement that we built.
- [59:21]
A
Can you still export it to Excel?
- [59:23]
B
Always. Yeah, everything's exportable.
- [59:24]
A
I was going to say, like, I just don't think if you told a CFO everything we've just described about Hanover park, but you can't use Excel anymore, It's over. Yeah, like, that's. That's even. Even harder than the migration of a whole provider is, like, getting them off Excel. Like, the industry runs on Excel. And you, I think you have a nickname with your friends. They call you Chip.
- [59:46]
B
Oh, boy. What's going on? This is coming up. This is coming up. So my friends will shout out Raj and my friends. But, like, when I started the company, everyone was like, you're crazy. What are you doing? You just left this job and previously left Goldman Sachs. And, like, this is insane. What are you working on? What are you doing? And I basically had this thing where I had this massive chip on my shoulder. I love this quote from Josh Wolfe at Lux Capital, which is, chips on shoulders. Put chips in pockets. And now that Peter and Lux have invested, it's kind of entertaining for it to be full circle, which is like, everyone started calling me Chip because they were like, wow, he has this massive chip on his shoulder. Because everyone doubted that this would be successful. We still have a lot of work to prove it, though.
- [60:30]
A
Yeah. I think one thing that's been kind of interesting is despite you have, like, this chip on your shoulder, you really want to be successful. There's been times that you've turned down customers, like, somebody. You don't think that you can take them on and, like, give them the right kind of service. How do you know when to do that?
- [60:47]
B
Yeah, I think, like, ideal customer profile, which is like a common term, has become, like, insanely important for us. Like, I am deathly afraid of disappointment. Right. Which is disappointing. A customer that is really excited about Hanover park, that we can't deliver what we need to deliver for them. And a lot of the problems in that is, like, you take on too many customers that are not the right profile, that have different needs from who you're focusing on. And so you don't end up building for them, you end up with a bunch of people that are asking for things that don't match Right. And that's a massive problem. So I'm turning away customers left and right to ensure the people we do partner with have the a raving fan experience that we want to deliver. And so that's kind of been the focus of like it sounds crazy but like we'll turn away customers all the time to ensure that the customer base we have can become raving fans in 2026.
- [61:34]
A
But don't you want to grow super fast? Like that's kind of like the point of, of, of hypergrowth startup, right? Is grow as fast as possible. Isn't that what they say?
- [61:43]
B
I think grow as fast as possible with like, you know, the right constraints of who you're building for. And so obviously there's a massive market right, of like opportunity. And we've just focused, I would say on like mid market enterprise, which are like larger firms with finance teams, more sophisticated CFOs than some of the kind of the smaller firms. That doesn't mean in the future we won't go there. I just think like it is not a near term, it might be a long term as we are able to like democratize the like services delivery that we have and make it, and make it scalable.
- [62:13]
A
Talking about longer term, what is kind of like a longer term, like 10 years from now. I don't know if we're going to do this every single year, every year
- [62:20]
B
for the next decade.
- [62:21]
A
Yeah, but like, I mean talking about 10 years from now, whatever, whatever the long term is like I'm reading the S1 for Hanover park, you're like spilling it, spilling it all out there. Like, yeah, what am I going to be reading about?
- [62:32]
B
Yeah, well, I think was pretty exciting, pretty awesome. Is that when Jake and Emergence led our Series A, they wrote this memo and they said like this if executed incredibly well, we have a lot of work to do. Is a viva, like opportunity. Viva is the largest vertical software business in the world right now. It's around 50 billion market cap, which is like. But what's funny about Veeva is they started as a CRM for life sciences. That is the most niche boring thing of all time. Now they're the board level vendor for Moderna and Pfizer and like all these different things, right? Level, board level, meaning they're the most important vendor for like Moderna and Pfizer. Like Moderna and Pfizer pay them like tens of millions of dollars a year. Right. And so our goal is to do that in finance.
- [63:15]
A
Right.
- [63:15]
B
And so it's like, okay, we want to become the Most important vendor for Blackstone and KKR and Vista Private Equity and pick your name of really important investment firms and not just do one siloed specific thing that they're used to. We want to own the core back office, own the middle office and own all the software tool spend for the investment firm and along the way have the opportunity to bundle all these additional products and service offerings around it. And so and then in the super long term, if now all this data that used to be in 50 different random tools is now in one centralized system of record, why can't we help people make better decisions and unlock alpha and do that for the investment firm? And so that's the super long term.
- [63:57]
A
So I have one more thing I want to ask you. You're kind of like personal AI stack. Like what you use personally as like Chris. So I think a year ago you told me you were using Claude artifacts and you were also using something called Hemingway for writing. Yep. What's it called?
- [64:13]
B
Still using those number one tool right now, Granola. It's just like AI call, you know, call. So like what we do is a lot of our internal calls is like we'll basically record any meeting and then we have this like transcript repository that you can query and do a bunch of analysis on. And so like that really helps with like context sharing across teams, especially as we've scaled the team really quickly. And so that's been one. The other is like I am obsessed with Claude coworkers. Claude Cowork has changed everything. Claude cowork is my chatgpt moment.
- [64:42]
A
Like actually so not even chatgpt like Claude cowork was yours.
- [64:47]
B
Claude cowork is like 10 times better than for chatgpt than me. It's crazy. Like what it's basically done is I used to be an investment banker. I used to have to put PowerPoints together, I used to put financial models together. I am now like I did this massively important presentation for a trillion dollars of assets. And legitimately, Claude Cowork took call transcripts, notes, all this stuff. And I was like, here's the format of a different deck. Build me this 10 slide thing from scratch with all these graphs. It one shotted it. I made like an hour of modifications of something that would have taken me 10 hours and I was done. And so it's been transformational. When I think about all the data analysis stuff as well as building presentations.
- [65:28]
A
You said you built this kind of central to do list thing. I remember you were texting about like what is it exactly?
- [65:36]
B
Oh, yeah.
- [65:36]
A
Do you use it or just like a fun thing you try to do or so.
- [65:39]
B
So I've literally like as like the non technical CEO that wants to be closer to the bare metal, I was like AI coding tools are so much better. So I literally whipped up Claude code this past weekend. I was like I'm gonna vibe code a like CEO command center basically to make decisions and it was like pulling in all of Slack, all of email, all of Google Calendar, all of my granola notes, all of these different sources to build a dashboard to help me be like what are the decisions that I need to action on right now? And then like a self updating to do list that sync with my email and other things. And so it's been pretty fun. It's still like super experimental. Like I did it for two hours on a Saturday, but it's been pretty fun to play around with.
- [66:16]
A
Is it like you get like a feed that's updating every minute, like synced with Slack and you're like typing in and hitting enter to like make it do things? Like how does it actually work?
- [66:25]
B
Yeah, it's pretty crazy.
- [66:26]
A
It is.
- [66:27]
B
So it's updating like I think it's like every hour or something pulled together from like any activity, over slack, over email, over Calendar, over anything linear is another one. Like we pull in like our product issues and stuff like that. And so all the activity feeds in and then if I want to like update the dashboard, it's like I'm just connecting to a bunch of MCP servers and I'm literally prompting Claude code to do things and so it'll just auto update like say it's like, hey, you need to respond to this email. It's super critical about this deal. Once I respond to the email, it
- [66:57]
A
just auto updates in the dashboard. Yeah, yeah. Because it's the thing that I've always had, the issue I've had with these to do lists is like you make your to do list and then you can do the thing and you go and change the to do list.
- [67:07]
B
It's like what's going on?
- [67:09]
A
Yeah, so I've always had super simple to do lists that are basically like high level bang out this hour thing and then you like maybe it's worth updating. But like some people make these like super elaborate very minute to do lists. It's like you're spending half your time on your to do list.
- [67:27]
B
I mean I think it's like this like you know, productivity optimization sometimes is procrastination I think is like the, the Piece of it of like, if you're doing too much, like the simplest execution should be like, I'm doing this thing today and here's the most important problem to solve and everything else is noise.
- [67:41]
A
And you just announced, I think you mentioned earlier, the Hanover mcp. So what is that and what can you do with it if you're a customer?
- [67:50]
B
So breaking news, Hanover Park MCP is live. Now what this enables us to do is mcp think about it as API for AI. And so instead of having many different disconnected data sources, the really cool thing about Hanover park is because we are doing your core accounting execution. We have all of your system of record data. That's what gets audited, that's what gets sent to your limited partners. That's you get your financials on top of that data. We built some magical things. Like now we have all your LP data organized, we have all your portfolio data extracted, we have all your KPIs collected, all this stuff. Now with our MCP it can be like, I don't even need my GP to log into Hanover Park. I can just tag it right into Claude alongside our CRM from Adeo and I can just query the full context of my Data and generate PDFs on the fly. And so it's been a pretty magical opportunity for customers and excited to see where it goes.
- [68:42]
A
You mentioned attio. Did you switch over to Addio?
- [68:44]
B
I didn't. I'm a HubSpot, Stan. Look at me, old school. Use HubSpot for CM right now. But I'm thinking about new things like Monaco and others. Oh, nice shout out, Sam Blonde.
- [68:56]
A
Yeah, he actually, I actually need to respond to my dm and I was like, hey, want to come on the podcast, talk about Monaco, Everything you've learned about sales and growth? And he's like, yeah, let's do it. I think we're going to do it in a couple weeks. So if you're listening to this, look out for that episode. I think we have a couple. Let's see. I think it's either right before this or right after. We have one with my friend Chathan at Benchmark. We're talking all about software. We have an episode with Scott Stevenson at Spellbook. It's like the fastest growing AI company in Canada. We think that that's a true statement based on, we think based on what he's heard from. Yeah, it's sort of like cursor for contracts. So if you're a lawyer, a lot of the work you're doing is like with contracts. It's essentially like a Microsoft Word plugin where you can sort of edit contracts like you would code essentially. And if you're a lawyer, a lot of your job is just writing legal documents and editing legal documents. It just helps you do it faster. And they have a couple other. It's almost like Claude cowork for doing legal things. So you can say, hey, write me this document based on these things and just go and do it. It's pretty interesting trying to think of who else we have. We have Mike and Nikhil at Footwork. I don't know if you ever met them throughout the course of fundraising, but Nikhil was a seed investor in Canva Farmer's Dog. Probably missing a couple multibillion dollar companies. And then Mike was the COO of Stitch Fix. Zero to a billion in revenue ran Walmart.com was in charge of all that. Thousands of employees. Walmart.com is pretty big now. So anyways, a lot of good conversations coming up on the podcast. People should continue listening to.
- [70:39]
B
Love it.
- [70:40]
A
Subscribe to the show. Subscribe to the newsletter. I might not even have to do an outro now. We can just do the outro right now. Also thanks to Numerl and Flex for sponsoring the show. Check out numerl.com for sales tax. Do you guys have sales tax you have to collect? Are you using numerl?
- [70:56]
B
We're not using Numerl yet. What are you talking.
- [70:58]
A
You should use numeral.
- [70:59]
B
Oh, whoa, whoa. That's good.
- [71:01]
A
And then other sponsor is Flex, which I use for the fund. If you check out the link in the description, sign up for the waitlist. You'll get the Flex Elite personal card. It's like business and personal banking all in one.
- [71:14]
B
Let's go.
- [71:14]
A
And they give you credit. So there's a lot of guys out there that'll say, oh, we'll give you a credit card just based on your your bank account and what kind of cash will give you a percentage of it. Flex actually gives you like a credit card under underrates it like Amex. So worth checking all those out.
- [71:29]
B
Let's go.
- [71:29]
A
Thanks for listening.
- [71:31]
B
See you guys next time.
- [71:32]
A
See you soon.