The Exchanges

Q Are there like, do you have to go after different approaches for those industries? I'm sure because you mentioned, and I know this too, but like, because venture is such a wonky asset class, internally it, they act like startups. Private equity is more institutional. So do you adapt your approach for servicing these companies throughout that, or is the product pretty linear?

A It, the product is not that different. Uh, what's really different is, uh, the go to market motion. We started with a sales team that sold, you know, 6000 dollar cap tables to 24 year old founders in hoodies, uh, you know, in Soma. And, and now we're selling million dollar accounting solutions to middle aged, uh, CFOs in midtown. Like it's just a very different, uh, sales motion. So that's been the biggest probably challenge for us to, to adapt to, to a new industry. Uh, another way of thinking about our business is we're very much a network business. Uh, and, uh, we try, we try to build networks, uh, directly into the product. And so obviously our, our first network was cap table to investor. Our second network is, uh, investor to LP or fund LP. What makes venture unique as an asset class for us is that it has what I'll call a global topology. You know, you bring a company on to Carta because all the investors are minority holders. They bring a bunch of investors. They bring 20 investors. And then those 20 investors hopefully recommend some startups, which bring more investors. And you get this very complex web of a global topology. In private equity, it's different. A KKR portfolio company that buys Carta cap table software doesn't help us with a Carlyle. Uh, portfolio company. They're just completely separate. A KKR portfolio company that we sell helps us get another KKR por…

AI assessment note: “the product is not that different. Uh, what's really different is, uh, the go to market motion.”

Q I think because Carta has scaled so large, people might forget that you guys were once a startup. I want to know who are some of your investors and what kind of funding have you reached to date?

A So we've raised shockingly about a billion bucks, uh, in total across, I think, seven rounds. Uh, so Union Square Ventures did our, our, um, Series A, Spark Capital did our B, uh, uh, Menlo did our C, uh, Meritech did our D, Tribe did our, uh, uh, E with, uh, Andreessen Horowitz, um, Lightspeed did the next one, and Silver Lake, uh, Premier did our last one. So We just, as we, as we keep moving further up into the, um, uh, the stack of, of private capital, we went from small seed funds to large, uh, venture funds to gross equity funds, and then most recently, um, private equity. We've got a board of seven. We've got people from like Will from Lightspeed. We've got Matt from Menlo, Mark, uh, from Andreessen Horowitz, um, Joe from, from Silver Lake, um, Barbara, who, who is the, um, Uh, first, uh, female vice chair at Lehman and then, uh, RBS. Uh, so we got a, a great board. It's been a, a fantastic, um, you know, the evolution of a board over a company's growth, um, is something I, you know, I learned you don't get to do very often. Uh, and it's pretty amazing when you look at the board at an early stage and the board at late stage and pre IPO, it's, it's a very different, uh, dynamic. It's a different group of people to work with. Um, and it has been fantastic. I've learned so much from, from this, uh, generation of the board.

AI assessment note: “we've raised shockingly about a billion bucks, uh, in total across, I think, seven rounds.”

Q And you've expanded now into private equity, private credit credit. Those categories might've not been served before, but now you're serving them a product. Why did you get so excited about the opportunity there?

A I would say CART is good at, uh, two things. One is, uh, entering services industries and turning them into software industries. We, CapTables was a service industry before we got into it. Four and nine A was a service industry. Fund administration was a service industry. We're, we're, we've turned them all into software industries. So we love doing that. The second is we love doing things that people today do in spreadsheets that they shouldn't be doing. And if you look, CapTables is a spreadsheet problem. Value at four and nine A was a spreadsheet problem. Fund accounting is a spreadsheet problem. Private credit is a spreadsheet problem. Private equity is a spreadsheet problem. Uh, and all we do is we take those spreadsheets and we move them into the cloud. And so when we saw these other problem sets that they were seeing in private equity and private credit, we're like service industries dominated with spreadsheets. That's like perfect for us. We, we are the best in the world, uh, at taking on those, those kinds of problems. And what's really exciting is the market size of private equity is six to eight times the size of venture. And then it's another three or four times private equity and private credit. And then you can go to infrastructure and real estate. You just start knocking down these dominoes. Uh, it, it's really interesting. Uh, in my small market to concentricall…

AI assessment note: “what's really exciting is the market size of private equity is six to eight times”

Q A lot of people want AI right now. How are you thinking about involving AI with Carta?

A We're all in. I actually just came from two internal AI meetings. AI is interesting. Um, what does it mean to be an AI company? Uh, and some people think of it as, oh, you're building AI products. So you're building a product that does AI or uses AI or some, some AI enablement product. Uh, another is you could be an AI company building traditional non AI products, but your internal stacks all AI. You are, you are building a new type of company based on, on AI. Uh, we're both. So today I spend half my time on product and the other half on AI projects at Carta and all the AI projects come in two forms. One is how do we use AI to build differentiated user experiences for our customers? So it's all in the product side. And then how do we use AI internally to be a better, faster, smarter organization? Uh, and I, I split time on both. Um, and so much of the AI stuff I'm learning, uh, It's, it's like programming. Like, it's like being, being an engineer, but instead of programming using Python, you're programming using the English language, but most people aren't trained programmers. And so much of, uh, changing the culture of Carta to be an AI first company, uh, is, uh, teaching people to think differently, just to think about, like, I was just in a meeting where a team was manipulated. We, Do a lot of spreadsheet work. We have a lot of spreadsheet lists at Carta, a bunch of Excel pe…

AI assessment note: “today I spend half my time on product and the other half on AI projects”

Q How do you use it in your workflow?

A I use it for a lot of kind of the basic stuff of like reading stuff, transcribing stuff for me, especially I can, I can dictate really quickly and turn it into, to written stuff. So there's like all these like little kind of productivity, uh, uh, hacks that are helpful. Where I find it most useful though, um, uh, is actually for other teams, uh, because I don't do a lot of things that are repetitive. I don't do a lot of things at scale. You know, I, most of my day is eight hours of listening and then I make one or two decisions at the end of the day. Whereas other people that are actually producing things, you know, they're producing reports, they're writing code, they're, Creating spreadsheets like the people that are actually doing production at scale. That's where I think it's been super helpful. Uh, and so I spend most of my time actually helping them learn to use AI to do their jobs better. Uh, and that's, that's been incredibly high leverage for us.

AI assessment note: “I use it for a lot of kind of the basic stuff of like reading stuff, transcribing”

Q Are there any kind of instances or examples that you've seen throughout your time as CEO of other companies doing that and focusing on the wrong things like outputs?

A We see it all the time. I see it in other companies and other, other startups. Um, but I'll, I'll speak more to us. We make the mistake all the time, you know, cause it's super easy to get excited about the, uh, the outputs. We call it, uh, alpha versus beta. So We talk a lot. Alpha is what we consider things that we have control over, and beta is things that we don't. So beta is like market. You know, if we lose a customer because they're going out of business or, you know, the market's down, that's beta. You know, it affects our outputs, but it's not something we can control. But if a customer leaves because they're unhappy or we made a mistake, that's alpha. You know, if we sell a customer and convince them to come to Carta, that's alpha. We're doing something that wouldn't have happened if we didn't put in the effort. And so all of our, where we get into, uh, a lot of mistakes, uh, is when we start thinking, um, about beta. We're like, oh, we had a good quarter. Uh, was it alpha or beta, right? Did, do we have a good quarter? Cause the market had a good quarter or do we have a good quarter? Cause we did the work. And sometimes the inverse is true. We had a bad quarter. Well, maybe we had a bad quarter in the, in the vanity metrics, uh, because the market was down. But, but if you actually look at the stuff we had control over, we did a really good job. And having that disci…

AI assessment note: “I see it in other companies... but I'll, I'll speak more to us.”