Hello everyone. If anyone wants to come listen to this last one, it's going to be the best one. So please come on down to the front. We are rounding the corner to the end. But last but not least, we have Eric here from Ramp. Eric, will you give us a quick introduction yourself? Ramp. What does Ramp do?
Yeah. Great to see everybody. I'm Eric Lyman. I'm a tourist. No, I'm kidding. Co-founder and CEO of Ramp. You can think of us as smarter financial infrastructure to run your business. We're most known for issuing smart corporate cards, but we manage payments of all kinds. Actually, the majority of our payments are non-card. We help automate expenses and even automate accounting. We're used by well over 50,000 businesses and almost 1% of all the corporate payments in the US are powered by Ramp.
That's awesome. I've heard that you guys are just past 7 years old or as I think you say 255 or so days old. Why do you count in days?
Well, it's originally I don't think we've ever really told the story. It was kind of a happy accident if there's any Bob Ross fans out there. It was like our first board meeting and we had an outside director and I was like we don't have any revenue. We're only 133 days old and we just like put it on the cover and like did it and moved on. But it was one of these things where two months later we had the next one and I was like, 'Oh, I better like make a new deck.' So I copied and pasted the deck. I updated from the back to the front and the very end. And I switched it from like 133 to 199 cuz I just was like updating everything. And I just remember like, whoa, it's been 66 days. Do we get the same amount done as the previous 66? Did we get more done? Did we get less done? And we were like seven people. We were competing against companies that had 70,000 employees. We could not outwork them. And we realized there were certain hours that really mattered. We got 10x done. You know, informed the strategy, had far better sales meetings and we're like we want to do more hours like that. And in order to do it we would have to measure time and actually say no more often to things that are less important. So it's really more about setting tempo and I think ultimately for a lot of people running companies like that's the job. It's setting the pace.
Cool. I like it. All right. So, this is a room full of a bunch of both fintech founders and then also like some really big companies and folks kind of all over the fintech ecosystem. But we can talk about kind of anything. I want to go back to the very beginning. And like how did you think about some of the mistakes that you made early on? Like was it just come up with the idea for Ramp? Oh my gosh, this thing just grows like crazy or tell me about the early journey, some of the speed bumps you had.
Oh my, we had a lot of those. Look, I think in the very early days we had the kernel of an idea which has endured which is whether it's us or someone else it feels strange that many financial service leaders and providers are structurally misaligned with their customers. To make it more straightforward like in the credit card space the dominant model was there were businesses working really hard to convince you to buy things to earn more points and there was multipliers so the more you spent the more you got and if you got this there's a 4x this or that or whatever it's fine and then there was other people in these businesses working really hard to convince you the 4x was a lot and then they would devalue the points constantly maybe people have heard of that and I remember doing research with, I don't know, regular people, trying to convince them my job was to sell more cards at the time. And I'd ask them, 'Do you want like points or cash back? What would motivate you?' And if you really listen, people would say, 'I just want more in my bank account.' Go figure. And if you just, you know, you see a lot of subscriptions every month, it turns out if you help people not spend $100 on some subscription they're no longer using, that is $99 more in their account than if they got a dollar back on that purchase. Why isn't there a card in software that is aligned with the end customer? You can compete on the basis of value not on the basis of price and compete very differently and so the initial I think enduring mission was very very good and is still consistent of we exist to save our customers money and have aligned incentives. There was a lot of things I really missed and if you kind of study the early board decks one of the words you won't find for about a year to show up is the word time. We completely miss the importance of actually going and saving people time and for companies time quite literally is money. Everyone has an hourly rate if you care to calculate it. And an hour not spent doing expenses is an hour you could be selling your next customer, working on the next product and moving forward looking at. So there were things we missed. I think that there was a lot of things we could not have predicted which I think many people in this room dealt with. The pandemic was not on the road map. Failures of different banks which put us and others at risk. I think was gnarly to deal with. And I think even now like I think the extent to which AI has upended not just every business model but even the way that people operate as an organization and what it means to run a company has changed and so those are a few.
That's great. Thank you. So as the folks from Plaid who are here will know I am basically allergic to corporate bullshitisms. And they happen a lot. But today we've talked a lot about this concept of intelligent finance which we had to like really think a lot about to make sure that it passed the corporate bullshitism filter. And it does. Intelligent finance, important new field basically think of it as like AI plus really complex machine learning on top of finance. Eric you published an essay called 532 years which talks about the history of accounting. And in it you talk a lot about programmable money. So tell us what is programmable money and how is programmable money not just another corporate bullshitism.
So glad we're talking about this. I think it's this really interesting question right and like part of how we got onto this was two reasons. One, it's a little bit interesting right that fundamentally the way we calculate I don't know keep books for companies and manage ledgers is literally medieval math. It's good math but it really hasn't changed and over the years I if you just look part of why I was so interested in this topic is like if you look at a lot of the financial processes and tools that people use especially in a corporate context, it kind of makes no sense, right? Like for example, just to deviate for a minute, like everyone accepts as normal that if you're going to go take a client to dinner or come travel to an event like this, you're going to use like two different systems, right? Like there's some company somewhere that issues you like a card and your policy doesn't drive if the thing actually works. And then, you know, you get a receipt and then you're going to go into some other company's database and you're going to manually enter all the data even though the whole transaction was digital in the first place. And then someone in a center of excellence somewhere is going to go review this thing. And there's like eight people involved in one purchase which was digital in the first place. And it's like you would never design it this way. It's sort of nuts, right? And so a lot of what Ramp has been doing is trying to look on first principles and ask like the systems we're building, are they designed for the capabilities of today's world? And when I think a lot about how modern and digital accounting expense management processes built and bolted onto this are fundamentally taking old processes and saying let's put it in a database, let's put it in the cloud. And you end up with these litany of point solutions. And so a lot of it is first trying to question of like why do we do things the way we do is kind of the first piece of it. Second is getting at this notion of like I think a lot of people maybe not in this room but most people in this world misunderstand what money is right? People you ask people what's money and they're like well the dollar bill is money or a coin and it's like no that is like a token that is a representation of value money is information right? The original kind of records of money were kind of the first records of writing were receipts right? If you're getting paid it's not like there's a check that moves it's like 40 characters, right, from one database to another, instructing to move a ledger item from here or there, right? And so you move funds, but actually like if you think about designing modern whether it's financial tools or systems to do work, you need to kind of step back and ask like what is money, what is information and so when you kind of ladder on to like intelligent financial products, right? I think an example that we try to think about and ultimately ladder towards is like you know take something as simple again as an expense report like you could say oh it's intelligent I built OCR and I get a piece of information and I'm doing your reimbursement. I think more intelligent finance is actually asking like why does this thing even exist and how do you actually start to go do the work and I guess it relates back to even your previous question. My misunderstanding and I had spent years in and around this industry was I thought fintech was just about money and saving people money and increasingly if you're interpreting and you're understanding that like actually like money is information fintech is increasingly about doing work and saving people time and executing and I think intelligent finance is starting to act on this next bit of intent. I don't know if that correlates to that.
That makes total sense. I'm going to shift gears. We could talk about this for a while. Shifting gears a little bit. Let's talk about AI. We've been talking about AI a lot today. You all are one of the more I would say like AI like cracked AI companies for a like midsize company. And it seems like you got on board with building with AI and embedding in AI quite early as things started to change. What was the moment when you said, 'Oh, this is going to be a thing and we need to change how the company works.' And then how did you go from that realization to the reality of where you are now?
Helps to be small, you know, and to be told that you're small at the time that you make that decision. Yeah, not so far anymore cuz it forces you to like, you know, try to rub two nickels together and get a quarter kind of a thing, right? And, you know, we were told we were like two or three years late to the market. We thought we were like 175 years late to our market, but neither here nor there, right? Where we really got onto this stuff actually came not from product development, but from the sales world. There was like a sales development rep, which for folks who maybe haven't worked in B2B, like the job is like you just show up at a company and your job is go book meetings. It's really hard, right? And maybe you email people or you cold call people and like that's the job. And we there was someone on their team who was excellent, like really great at doing it. But we couldn't figure out how to get him more than 24 hours in a day. And we didn't know how to find other people like him. We weren't so good at hiring. But we had some engineers and we just said, you know, what is this person doing? And we looked back to the day thing to their calendar. And we'd see, okay, he wakes up in the morning, he shows up at the office and he spends his first hour going and checking who raised money today, what companies were formed. He goes on LinkedIn and he sees who moved from one job to another, right? Then he tries to guess at their email. Then he's going and writing up copy to go and send a note that hopefully will convince someone to go take a meeting for you know what half of his day is gone just going and preparing to do the thing and then he starts sending notes and then kind of only that last third like such a low yield of his day is actually the thing that generates money. And we thought, well, what if we had some engineers? These kind of sound like structured processes an algorithm could do. You know, let's just programmatically pull who raised funds. Let's guess the email. Let's run some AB tests. And around that time, GPT3 had come out. This was a few months before the ChatGPT moment. And we started trying it to go use this as a way to write better copy for emails or take kind of unstructured data and turn it into good emails. And before you knew it, suddenly like we were like there was writing copy that kind of made sense and worked. And to make a long story short, it was integrated in a process that within a year he was booking I mean for him he was so I think he was booking eight times as many meetings per day as he was just a year prior. And you flash forward to today like the quota for a salesperson at Ramp and SDR is like we think it's four to five times our next closest competitor. And so a lot of it was thinking about the lens of not of how do I adopt AI, it's like how do I make people better at their job? How do I make them more productive? And we've used that and try to apply it to what are the bottlenecks in engineering, what are the bottlenecks in marketing, what are the bottlenecks and take a function and try to go apply it. And so that I think if you think less about like what is the cost to ring out, it's more of like what are people doing with your day, you start to find really interesting uses for AI.
