SaaS Interviews with CEOs, Startups, Founders
He Lost $50/User to Build a $30M ARR AI Empire (Fathom)
21 May 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What is the main topic discussed in this episode?
There is a multi-billion dollar war happening in the world of AI note takers. I'm sure you've seen them in your Zoom meetings. Fireflies did a tender offer at $1 billion last year in 2025 and says they've been profitable since 2023. And Otter says it ended 2025 at a $100 million run rate. Zoom, Google, and Microsoft are also launching their own AI native note takers.
And then there's Richard White. He's building Fathom.
We basically went 0 to 1, 1 to 10, and 10 to 30 in the first three years of monetization.
He is by far the most capital efficient of all the notetaker CEOs, having raised just $30 million to grow well past $30 million of annual revenue. But how does he manage his cash?
Yeah, probably never more than a million in the bank. Yeah, 1.5 to 2, 1 to 2 million constantly.
But how did he grow so quickly when he raised such a small amount? Well, he gave the product away for free, which was shocking because of this.
That gave us the confidence to say, we can give this away for free and actually lose a lot of money. We were losing like $50 a user per month in the first couple years of Fathom.
Then he hired salespeople before there was anything to sell. Why would he do this?
I'd hired three of my best salespeople from UserVoice. And I said, I've got nothing for you to sell today. But one day I will.
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Chapter 2: How did Richard White grow Fathom while losing money on every user?
So I think a lot of people like they launch and they're trying to monetize and get acquisition and prove retention. And I'm a big fan of like, okay, let's take those five kind of metrics and take them one at a time.
And number three, the top growth channel Richard and Fathom used to grow from 1 million to 30 million of revenue very quickly. Let's jump in. Hey folks, my guest today is Richard White. He's the founder and CEO of Fathom, an AI meeting assistant he launched in 2020 after running UserVoice for over a decade.
He's raised about 17 million bucks, including a recent Series A, scaled to millions of revenue and built one of the fastest growing AI productivity tools with thousands of companies using it daily. Richard, you ready to take us to the top? Let's do it. All right. I was just thinking, like, what could I share on my screen so that people see how a bit of a power user I am?
But there's a bunch of customer information that I probably can't share. But you can look in your database. We are a daily user of Fathom at Founder Path. And I think to give the audience context on why I wanted Richard on. There's a lot of noise in the space right now. He has competitors that are sort of very loud and out there.
He sort of built this in a very sort of a way that we like to teach on the podcast, which is capital efficient, distribution oriented and user focused. So Richard, on that note, I mean, maybe that's a good place to start. One of your recent rounds here. First off, let me just take a step back for people that don't know what the product is. Why don't you give the product pitch?
Sure. Yeah. So Fathom is a free AI meeting assistant. We take notes on your Zoom, Google Meet, Microsoft Teams calls. As you mentioned, we've been around a couple of years. I think we are not the loudest person in our space, but we really pride ourselves on two things. One is the quality of the output. Highest quality transcript, the highest quality summaries.
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Chapter 3: What is the 5-step framework for sequencing risk in startups?
And now we pride ourselves a lot on being the thing that plugs in to all the other tools you're using. So we're about to launch an MCP server. We have our API and all that stuff is available for free. And so we really hang our hat on quality and giving a lot away for free, frankly. That's part of our distribution kind of story, if you will.
Well, so let's jump into that. I mean, I think one of the early investors you brought in was, was Zoom's fund. I mean, clearly trying to go deeper on an integration there. Does that turn off all the other providers in terms of them wanting to give you access when they know Zoom's in your, sort of on your cap table?
No, I think, you know, I think for the most part, the interesting thing about building this business is they're not really APIs. They're all kind of undocumented. Like these, you know, historically we captured stuff with, with bots. And I think we'll talk about how we were going to have some not bot options here coming up soon. But they're kind of undocumented APIs.
It's not really much any of the platforms can do. And candidly, I think Zoom for a while has been the leader in this space, certainly for the people we're going after, which are customer facing teams and organizations. You know, a lot of them are Zoom first. Right. So, no, it's not.
You know, I think something we did earlier on in this journey and it really paid dividends being, you know, we were one of the first apps on the Zoom app marketplace. You know, Zoom invested, Zoom heavily promoted us and they've been a fantastic partner.
Yeah. I found an example guys, just so you can see why we ended up, I'll actually, I'll give this analogy. We use, cause there's, everyone's using different call recorders, right? We use fathom. Fathom is like our favorite pair of jeans, right? We wear them six times a week. It's pretty much always open. We use it the most.
a tool like, uh, you know, granola, obviously also in this space, we use them as like, if we want to put on and do like a very special sort of thing, it's like a, think of it like a SWAT thing.
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Chapter 4: What strategies helped Fathom achieve $100k MRR in 30 days?
We put on our army uniform, we maybe do it once a month and like, we'll, we'll do that. Right. So no bot in the experience, it's off to the side, it's a transcript happening. Then there's the others, which I would describe like Addio, for example. ATTIO started off as a CRM. I would view them as sort of like socks, right?
You sort of have to have them, but they're not making any sort of style statements like my jeans would. And, you know, they record the calls, but when you go into the CRM, they don't have, like, I'm going to show you guys here what Fathom does. I found a call I can actually share here because there's no information.
Like, they just make it so easy inside of here to get the key takeaways topics instantly. Like, the second the call stops, this basically pops out, which is valuable. So very tight feedback loop.
The transcript is very easy to copy and paste, which Richard, I don't know if you can track how much your users do this, but all these foundation models where you can upload project files to teach it a brain. So much of that is us copying.
It's me interviewing my here, my database team and putting it into cloud project and saying, help me understand how to code on get lack of using conductor based off what my engineering team taught me on fathom. Are you seeing that a use case a ton?
A hundred percent. And so we're, we're kind of, we're about to do this really big launch next week. And basically, Part of it's a whole new redesign desktop experience. Part of that is making this process so much easier. So we're actually going to have first class direct integrations with quad and chat GPT and MCP server for anything else you might use.
And we're also looking at adding in kind of like support for people running kind of local bots as well. Local agents where we're going to start admitting all of your meeting data, like the summary you see here, the transcript directly to your file system so that you can just immediately, you know, you don't have to make any API calls sort of thing. So, yeah, we see that a lot and we want
We want to encourage that. We want to make that as easy as possible. We want Fathom to be the easiest meeting platform to get your data out of it because it's your data.
But that's not what you just said is not standard. I mean, Adio doesn't even have a copy transcript button in their interface.
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Chapter 5: Why did Richard hire salespeople before building the product?
It drives me insane. So I don't use them because it's like it's a walled garden. It's an Apple approach. In this space, why did you make the decision that the best way to win is to be the opposite of a walled garden?
I mean, I think it's a little contrarian. I think, you know, going back to kind of the fundraising strategy, I think a lot of our competitors have now raised a lot of money and I think it's forcing them to monetize at the individual level. We have kind of two products. We have a product that we were kind of giving away for free to individuals.
And then we have another product that sits on top of that for people that are running teams that helps them kind of understand what's happening across all those meetings their team is having. And we kind of can monetize there, which allows us to be really generous to individuals, even if you never joined a team. And it's kind of our strategy.
And so frankly, I look at this as like, we're happy to give away the data because we're always upstream from any use case there. And so like over time, there's always things we can first party in, right?
I'm not, you know, I want to support the salesperson that's building their own CRM and cloud code today because we can learn a lot from that person about what things we can build into the product in the future, right?
This makes a lot of sense. I want to get the growth story. Before I do that, though, I don't even know what we pay you guys, but it's never come up because I just know we get so much more value relative to what we're paying. But what is the average customer paying you today?
Average customer. So we price pretty aggressively. I tell our team we never want to always on price. We price ourselves even on parity with people that we think have much lower quality transcription and summaries. But the average user is about $25. If you'll get across all our plans of it, $25 per seat. Uh, and then we probably average, I think around eight to 10 seats is our average.
Interesting. Interesting. Okay. So, I mean, can I take, what is that? Eight times 25 means the average company on your platform might be like, what is that?
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Chapter 6: How does Fathom gamify fundraising to include users?
A hundred, 200 bucks a month, something like that. Yeah. Something like that. That's right. Interesting. And is that, do you see yourself trending more towards how do we go get the enterprise with a thousand seats or no, let's go get every new vibe coder using a $25 one seat plan on, on Fathom.
I mean, we generally monetize kind of teams, not individuals. I don't think we're at the place where we're seeing enterprise. We certainly see that it's a wide distribution. If that average is 10, it ranges from two seats up to 200 seats sort of thing.
I think the enterprise itself, you know, I hesitate to say I don't think we do much with the enterprise today by the more traditional definition of like thousands and thousands of employee companies. I don't think those companies in general are like yet digesting tools like this. Right.
I think there's there's still a lot that they're still figuring out their AI strategies or still figuring out their data governance strategies around this. But what we have seen consistently over the last three years is like every year we keep seeing larger and larger companies, you know, Three years ago, I saw nothing but 10-person companies, 20-person companies.
Two years ago, 50-person companies. We just see this kind of melt up. And I think that works really well because I think one of the biggest risks to doing a startup is you try to jump to enterprise and you abandon what's working with kind of small and medium-sized businesses. The enterprise, as you know, they need a ton of features that smaller companies do not.
I think it's easy to sometimes convince yourself, if I add this one feature, we'll be enterprise-ready. And it's like, no, no, no. There's 50 other things after you add that one thing. So we've done a really good, I'm really proud of our discipline on this, like not chasing those big deals, but consistently getting better and better about servicing large companies every week. Interesting.
Guys, remember, I am not just a YouTuber. I'm investing in my third fund. We've deployed $250 million into 550 software companies so far. Again, at founderpath.com. If you're interested in capital, I would love to cut you a check because I know you're investing in your education.
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Chapter 7: What are the trends in SaaS models replacing walled gardens?
You watch my show. So sign up at founderpath.com. And when you get the onboarding email, I reply and I see all those. Just reply and say, Nathan, I found you through YouTube and I'll make sure to prioritize you. I would love to cut you a check. Check out founderpath.com. Tell me more about the backstory here in terms of your own journey.
I know you are, this is a long, anytime I see someone 18 years at a startup, I go respect. This is a guy or a gal that doesn't, that does not quit. What was user voice and was this bootstrap that you raised? What'd you learn there?
Yeah. So a quick story on my journey, like, so my background is computer science. I was an engineer by trade. Early in my career, I kind of said, Hey, okay, coder, but I'm actually a better designer. And I actually found a way to kind of like push myself onto a team that happened to be in the first batch of Y Combinator, which at the time didn't mean anything now, obviously means.
And so I worked with Justin Kahn and Emmett Shear who went on to do Twitch on this thing that was basically a Google calendar for Google calendar and. One of our big challenges there was like gathering customer feedback at scale. Pico started in the same room as Reddit. So user voice, you could think of as really as Reddit for customer feedback.
And so we were trying to use crowdsourcing basically to like organize feedback at scale. And it was a fun business. It was like, you know, I call it my finishing school for startups because I was there for about 12 years. It started off as like a PLG company before we, you know, called things PLG.
It ended up as like an enterprise business that we were selling to like Yahoo and Microsoft and Netflix and Meta and stuff like that.
and honestly fathom then kind of came out of some things like every startup i've done it's come out of problems i ran into at the previous one and so user voice came out of my challenge of getting feedback at kiko and fathom came out of my challenges of just taking notes and doing user research at user voice and so it was like early 2020 on a ton of zoom calls like a lot of us were at that point i was actually researching some other products and i was just like gosh i went back to back meetings and me trying to talk to people and be a stenographer at the same time and pack out some notes and clean up those notes afterwards like this is
An insane way to live. And so we really kind of in 2020 developed a core hypothesis that like, why doesn't this exist today? Why isn't there a note taker for everyone?
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Chapter 8: How did Richard White scale Fathom to $30M ARR?
And tools like Gong existed at that point, which are like sales specific versions of this that were very expensive. And we looked at like, why is it only for sales? Well, the answer in 2020 was transcription was exceptionally expensive and there wasn't AI. It's hard to remember this, but like the first generation of AI tools was really mediocre.
And so we kind of bet Fathom on two things happening. One, we thought your subscription cost was going to zero and we thought it was kind of a commodity. And that gave us the confidence to say, we can give this away for free and actually lose a lot of money. We were losing like $50 a user per month in the first couple of years of Fathom.
I have to drill deeper on that now. What was the biggest month of losses? Do you remember in the early years? Are we talking like a million net burn in one month?
No. No, thankfully it was like one of those things like we were still small enough that like, you know, it never was, you know, it's kind of funny. Transcription costs dropped to near zero right around the time. If they didn't, we would have been screwed. It was one of these things where we're directionally correct.
If transcription engines or like whisper and things come out a year later, we're probably dead. And so, yeah, so it was like this fun little game of chicken we were playing. Right.
And I go deep on fathom, but close the user voice story first. What was the best year of revenue when you were there and how did you transition out? There's a lot of founders right now in a business where they raised 9 million of capital like you did. Going, I really want to go to this other thing, but I don't know how to tell my investors. I don't know how to tell my team.
How do I transition out?
Yeah, we got to about 10 million in revenue with that company. It was pretty steady growth over the, you know, I think we monetized about two years in. So over 10 years, that $10 million amount. I asked myself two questions at the end of every year. One is, am I uniquely qualified to run this business? And is this business uniquely qualified to teach me something?
And in 2019, for the first time, I said no to both of those questions. And once I kind of had that clarity, I was ready to move on. What I actually did was I kind of took a group of people in the org and I started working on other projects. Like I kind of moved myself into a quasi PM position because that's kind of my role. And I elevated who I was planning to be CEO to like a president position.
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