ElevenLabs Hits $200M ARR: The Untold Story of Europe's Fastest Growing AI Startup

In Poland, it’s a very different, much smaller world. For growing up, I was in a very lucky position where I was in the suburbs of Warsaw, then went to high school in Warsaw, then kind of started seeing more of that world, which was, of course, incredible because that kind of opens your eyes of, like, what’s possible, that there’s so much world beyond what you’ve seen in the smaller cities. And I think in a similar way as you think about building ElevenLabs now, it’s the scale of what we don’t know is still ahead of us, and this is, what’s exciting, that we know that if we climb those traditional hills, the traditional mountains, they will see increasingly more.

And I think the second thing was I saw the transition where in the suburbs of Warsaw, it’s like a public school, so school where you would have just any kids that would live in the area. And in high school and where I met my co founder, you would have a slightly different crowd of people that would win competitions, need to go through a few steps together.

And suddenly that density of talent was the most motivating factor to like explore more, learn more and do more, which now we are trying to, of course, replicate that at ElevenLabs where, and any other company I’m sure too, is like you try to keep that density as high as possible because at the end of the day, that’s what’s most motivating, being part of this incredible set of people.

Definitely, it was, you know, the combination of family, my older brother, all kind of trailblazed going abroad to study, then motivated us to like, you need to do the same. This is really helpful. And then the second, it was really this community of people in high school. Meeting my co founder was extremely smart, meeting some of our close friends, kind of going through this cycle of motivating each other. It’s like, yes, we want to study at the best university. Yes, we want to go deeper and crush this exam.

And I think this was a huge, huge element for all of us just going after it and knowing that maybe it’s possible. At the time, everything felt distant, it’s still, you know, many of the things do. But I think without that that kind of motivation through the people, which would be not possible.

It truly was. There was two things that coincided for us starting Eleven Labs. One was through the years prior, he worked at Google. I worked at Palantir. We would meet for a hack weekend project together. So we would try to explore a new technology. One was in a recommendation space. One, during the crypto height, we built a crypto risk analyzer, which wasn’t very easy and it didn’t work very well. And then once we did the project in audio, the idea was can it analyze how you speak and gives you tips on how to improve speaking.

And that kind of opened our eyes what’s possible in the technology space there. And then fast forward later that year, the moment hit from Poland, which is, wow. All movies are still dubbed where you have all the voices from the original, whether it’s male or female voice, narrated with one single character. So you have one voice narrating all the characters in a flat, no emotional way. So it’s like a audiobook reading of a movie, a terrible experience. And something that we knew combining the experience from working on audio and now knowing this is a problem that, okay, this will change.

A few years from now, as you imagine that kind of advancement, all the voices will have original emotions, intonation, sound incredible. And that kind of kickstarted this idea. And of course, then it expanded too. Okay, we need to fix the research layer to actually make it happen. Then we started with a lot of our creative platform work around ElevenLabs and then expanded to agentic platform work, how now the interaction is shifting where voice is this big interface for the technology around us. Well, you know, was very dubbing specific originally.

It kind of expanded through to everything voice today.

We first tried to, like, do two things in parallel. My cofounder was, okay. Can we use existing technology, stitch it together, and create a dub of a movie in a better way? And it quickly transpired that you get a good effect, but it wasn’t brilliant. So to actually fix it, let’s take a step back and fix one of those components and make it great. At the same time, when he was doing research, my mission was does anybody actually want that dubbing product? So I was emailing all the YouTubers, getting the the the emails, scraping them, and trying to message them, Hey, if we had a dubbing product to make your movies available in all languages, would you be interested in that?

Roughly, it was like 15% reply rate initially from the first batches that we sent. All were personalized. I mean, we sent thousands of them. The interest was like lackluster. All of them were like, oh, I don’t fully believe this is possible. Can you send us a sample? It would be great, but how will I operationalize this? YouTube doesn’t support it. So it was like, it was somewhat of an excitement, but not like a burning problem I need to solve it. But then the second thing happened.

So we started sending the samples. We started speaking more with the YouTubers, it quickly came that what they actually want help with is much simpler. They want to post produce and correct if somebody said something incorrectly. They want to understand how the script will sound before they need to produce it. They might not want to speak at all, and they want to voice over over the movie. So a super simple problem, which didn’t include anything with language changing. And of course, my co founder, as he dived into research, realized that you can actually build completely new text to speech model, which will be a lot more emotional, intuitive, that will make that narration a lot better.

So let’s put a dubbing problem aside. And as we see, there’s this huge other problem with with a lot of the creators. Let’s solve this problem first and bring that research just on the text to speech layer. And that’s only possible

Quick answer is yes. All the models at the time just you could tell immediately it’s like uncanny valley, not very good. You cannot replicate the voices. Dude, how

Well, I think the answer will definitely change now to, like, twenty twenty two. So that was the year where nobody yet kind of was thinking about AI. This was still kind of downfall of Meta various crypto days. The attention to the models was like none in the public eye. ChatGPT happened beginning of twenty twenty three. That’s where it all started spiking across. At the time, you didn’t really have a choice. Like, knew as a user, as an investor, that what existed out in the market just wasn’t very good.

And then there was more of a question, will this team be able to solve and create something better?

I think still a current question is, to what extent you continue on that kind of single modality space, where at the time it was mostly you train a dedicated model for speech or dedicated model for image, video, etcetera, over what is now more of a theme where you kind of train a more of a multimodal approach where you combine the reasoning and speech together to create even better speech experience. That’s our most recent generation is effectively that, the 11 v three. If we had that then, I think we would have probably skipped few steps, and our experience would have been even even better.

In voice, I think there’s a little bit of, like, it depends it depends on the use case. But to make it more concrete, there are use cases like narration. In narration, we think it’s plateauing. The new model generations will not make narration of an audiobook drastically different. It will still be in a similar quality. But I think in general, the point is right where if you just do research, eventually it will commoditize, and eventually that advantage you can deliver from research isn’t enough, so you really need to build product.

And as you think about Eleven, we combine both together.

In a biased way, I feel like the progression is still, like, just scratching the surface where it’s it’s just the moment of, like, still seeing that kind of escape curve of AI getting adopted everywhere is just getting started while scaling laws continue in the same way. So

I think, you know, it’s probably a different answer on LLM space and different answer in in the voice space. I think in voice space, you are still not a slower rate. And then there’s an interesting variation of, like, as they all combine, what does that mean for the world? Like, a slightly deeper understanding of everything around you. But I think in voice, you still will see pretty quick curve. On the lamps, I agree it’s probably a little bit flattening to to some extent. I spoke to Andrew

They definitely will do something, but I think they, you know, they lack the genius that I’m happy my co founder and the team has. But I think the true longer answer is, one is focus. I think in the early days, especially, you know, when we spoke then, there was just so many different things you could do in AI space. And I think we took this bet that we want to really own and win in the voice AI research and product space. All our work is directly tied to voice.

Then the second thing is I actually think the number of researchers in the world working on voice and being exceptional is super small, probably like 50 to 100 people at, like, the top level. So Piotr was able to assemble one of the best teams in this space. I think we have five to 10 people that are in the top 100. Like, there is, a mighty team, which I’m kind of time and time again surprised how incredible they are. And to make it specific, I mean, text to speech was one that kind of have blown everything out of the water.

Then speech to text is beating OpenAI, Gemini on benchmarks. Now music, which is, again, something that no big company has yet been able to crack or do. It’s an incredibly mighty team. And then even if I think if OpenAI does, you know, actually do something on research and I think they are trying, then that product layer is where you really need that big advantage of. If you are in a creative space, if you do narration, if you do voiceover, if you adopt, you go through so many additional steps to really make it perfect.

We do that well. If you’re building a voice agent or conversational agent, you need to bring knowledge base, integrations, functions. You need to then deploy, test, evaluate, monitor. All of these pieces are coming together in a platform, and I think OpenAI is, you know, not not investing as much time. They could, but they aren’t. So combination of mighty research team, speed of execution, and then actually focusing on on the use case, I think, in a deeper way.

No. Of course. I think the talent, especially on the research side, is out of the scale across any of those companies, especially in the early days. Of course, to some extent, as you as I think about Meta and others, they are, of course, paying for the know how as much as they are paying for the Rhode Island two, where getting those early people gets you some insight into the models and architecture that you can then bring across and accelerate. So in the early days, it’s more valuable than late.

But I think in our case, the reason I think it’s still valuable is, one, the upside for Eleven is just getting started. So I hope we’ll be able to compete with any of those companies in the future at the same scale. Two, what you do have, which I think is important as I think about any of those companies, is how close you are from developing research to actually deploying research. And at Eleven Labs, you are actually creating new models, they get to production and are some of the most important things that our products work on almost immediately.

So that gap is super quick. When, you know, bigger companies, go for their usual corporate red tape to get any of that work done. And then three, I think we now have like a very small MIT team that can learn from each other and move pretty quickly. I don’t think there is a guarantee you’ll get that in some of the other companies. I think they are optimizing for a lot of people, but not necessarily the right people.

How did the pre seed fundraise go? Pre seed was tough. It was, you know, similar question that you asked. It was like, how will we fix research? The second question, which was very interesting, we think the market is very small for what you are solving, which at the time was like, you know, it’s like a combination of AI voice. Like nobody was thinking about that. So that was surprising to us, which we were very disagreeable. And third was defensibility. Will it actually be better than what incumbents from the FA and G companies will actually solve?

Or like, how will the ad compete on long term? So these are the three. So it was tough. I think we spoke with a good amount of investors between 30 to 50, and it was double hard at the time because we, early twenty twenty two, we got an offer from one of the accelerators in The US, not YC. And we were thinking like, should we take it or not? And we decided, no, we are rejecting. We think we can create something more valuable and we don’t need that help at the time.

So we decided to go independent. And this triggered this more stressful time where suddenly now you need to raise money. We started spending a little bit more on GPUs. We hired the first few people. It’s like all of that was going from our savings, we are lucky to have from Google and Palantir. But I was like, Okay, now it’s actually getting a little bit more risky and we want to double down. We want to invest even more. So we need money. Much did you We raise

the pre raised 2,000,000. 2,000,000. Do you remember the price? 9,000,000. 9,000,000 post. 9,000,000 post. The amount was exactly 11% of equity that the first investor was buying and then the other ones were layered in. So it’s like just over 1,000,000. And this was 2023?

Yeah. It was only 4 years ago, which, you know, in the end, we found we had Credo concept here in The UK, Credo from ZE. We had one of our friends, a few others from Oxford, Peter Chaban, invested, was a co founder of Polkadot, which is the cryptocurrency. So we had, a good set of early believers, but to get there, it took us a bit longer. So you raised the 2,000,000

The main reason we raised was to accelerate what we would want to do. First one was building a small data center, so we built one. And back then, it was, I think, in Poland that we’ve invested a few, and then quickly after, moved and started buying some in The US. And then team. We started hiring not many, but it felt like a lot of the time. It was like additional two people, I think. Okay.

We actually raised the round in Q3 of twenty twenty two, but we announced it in Q1 of twenty twenty three, and we do that all the time, is that we don’t want to announce a round just for the sake of announcing a round. Our philosophy was always the round should have another purpose, which is bring the product out and help you get the product into the users, celebrate a set of customers to show that you arrived in a specific sector, bring a new research model into play.

So every round that we would do would always tie into a product announcement. So we actually hold on for announcement for a few months until we had our beta release and then we triggered, which was January 2023. But to your question, initially, when we worked on dubbing in the first early days and we were like emailing, we didn’t have product market fit. It was like very clear that people were so allowed to reply. Then we sent samples. They weren’t engaging. So we didn’t through the 2022 period.

And then when we shifted from dubbing into narration, voiceovers, then the product market signal started to hit. Maybe it’s there. I remember this thing. There were three things that happened. First, we did a blog post around the first AI that can laugh, and we sent samples that got picked up by newsletters, and people were like, wow, this is incredible. The next day we had like 1,000 people on our waiting list. And the second thing happened. We invited the first 100 or so users to Eleven Labs to test it out, and we had this audiobook author who joined the platform.

Our platform is like this small text box where you can type in text, tweet length, and narrate it. And he would copy paste his entire book 500 times, download it, stitch it together, then he released it. He released it on the platform at the time AI was banned. It passed through as a human content, and then it started getting reviews that is great. And then he came back saying, I want my other book author friends to do it too. So was like, okay, we are onto something.

And then we launched in January 2023 publicly. We knew we started getting more of that signal that creators, narrators love the work. And to be honest, I think from that moment onwards, we saw like a clear momentum. Then there was like, you know, more events after the media picked it up, then more creators picked it up. But the moment of release, we knew that it’s valuable.

And then maybe last thing on that, it’s like the product market fit concept For us, it never like fully, I think, know what this actually means where we knew users loved our product at the time, but I wouldn’t call it at the time we had product market fit as we were thinking of like, okay, how do we make sure it’s providing value for the next five to ten years? Then we’ll decide. This will be, like, something we would call, okay. This is clear product market fit.

We think this is, like, self sustaining for as long as we go into the future. So we wouldn’t go by that definition. I think we are now closer to that, but we are still know we can

so much more value.

So that’s the first one. 100%, like, for us, making announcement close to something big you want to announce from the product, from the user, from hiring perspective, tie it with that. I don’t think celebrating the number itself is the right way. I mean, in a way, it’s like you’re giving away the company. What are you doing it for? And you want to show as much of that as possible. The second thing would be we really want to focus on how you actually get the users rather than just the media PR element.

I don’t think the latter is actually as valuable as it seems to a first time founder. For us, I remember when we did the beta, we were speaking with some of the bigger publications, and one rejected us. The other one accepted us, and we felt like it’s a big deal. Then we did all the prep for the interview. We did the actual news, and then it was posted. We hold it, like, everything around this post that they told us the deadline for, and it had no impact.

I think it I mean, it’s like probably a few more people read about us from the investor scene, but we didn’t really care about it all the time. We were, like, all about users. What actually worked was working with the newsletters that were talking about AI, working with our friends from YouTube community that then posted on Discord that we are opening this up. Our Discord community was one of the most valuable. Reddit, those people picked it up quicker than anyone else. Hacker News posting there. Like, all of those were immensely more valuable, we, since then, always spend a lot more time on any of the actual forms where our users are rather than where they are not.

What has frequently happened if the launch goes well is you will get more interest. And I think you’ll get interest from investors, from events, from media. To a large extent, this is like the time you should really focus on getting the product and kind of all of that is like a distraction to a large extent. Like, you know, the first time we launched that kind of happened, we started getting so much of that. And I’m sure I did the mistake then of picking up a lot of those and doing more events than we should, where the best course of action would have been to just spend even more time with users.

And then early enterprises started getting interested, so more of enterprises. I think on the investor side, I think you want to line up investors. You do want to tell them like, Okay, I’m not racing now. I’m going to reconsider whether we need more capital in Q3 or Q2, whatever is the time period of time. And then when you actually need the money, then is the best time to actually re engage with them. But I would not I think it’s a waste of time to kind of be in this, like, continuous fundraising mode.

It’s, you know, distractive. You need to have conversations. It’s not useful.

Today, Les, at the time, we do have a few investors that we think would be valuable that we might not have today in the space. Through the time, we would have few investors that we wouldn’t try to proactively reach out, but if they reached out through any of the conversations, we would try to engage. But the engagement there wouldn’t be like, hey, we might be racing. It would be much more of like, hey, can you help me with introduction to x? Hey, can you help me with this hiring problem?

And this has worked tremendously well for the work where the investors are genuinely keen to help if you find the right person and you have a very clear problem and you don’t try to, like, overuse their time too. Like, you come up with one, two things that are concrete, useful, and then they know as well that if you are growing as a company, it’s good for them to show the help too. So we’ve done that.

Before it’s like kind of the second thing where you do get the interest from investors, I think this is the best time to actually test whether they can be helpful. And before you accept any term sheet and money, it’s like, now can you help me with angels that you want on cup table? Do you want the introduction then? That’s the best time.

I think the way we approach it is like, do they have domain expertise that we don’t have? That’s one category. Second, can they help us validate ourselves in specific circles we might not have access to? So like if you are an AI founder, it may be valuable to have a set of AI founders in there so you are part of the same events, the same conversations. And then, of course, in our case, it was can we have some of the go to market expertise where we had a lot of self serve, some Palantir experience, the sales led, how can we bring that in place as well?

Yeah.

Yeah. The NFTG. Now I feel like it’s a good name, but I was pitching that on changing that to, like, a different name for a while. Maybe it’s not possible anymore, but the So it was, like, the interest started around kind of March 2023. We had a lot of the investors that were in close conversation in the past, like, reapproach us. We effectively would be a little bit more in the waiting mode. Like, let’s see how we get through and let’s optimize for their partners that we truly want.

And what we truly wanted was a combination of making sure that people globally in a SaaStr trust and know that we have arrived, like we are a company that can be trusted, is building something ambitious. And then, of course, people that we would admire to be able to work with that created something special. And that was definitely in that category. In the latter category, it was a very fun thing because he approached us. Does he just DM you? How does he just approach you? He emailed us, but then I met him here in London.

He flew in, and it was like a weird setup where he emailed me, but it wasn’t clear whether it will happen, and it happened the last time. And then I see him in London in one of the hotels where he was staying. And the first thing he was saying was, which is the only investor ever to do that was, so I tested your APIs, and this thing doesn’t work. This works. Voice here wasn’t good. The stability wasn’t very clear parameter.

So he was the only person that tested our APIs, decided that it was actually valuable what we are doing, gave me feedback on, like, what we should change, and then told me, like, and I’m keen to invest, which, of course, triggered a conversation of what’s the vision, what we are after. And what’s special about Nat is that you can tell him very little, and he kind of has this beautiful ability of infilling all the context around it, comparing that to any of the past experiences and bringing any of those experiences that then might be relevant to you, but he gets immediately.

From the first conversation, he knew kind of exactly what we are after and challenged us with the right questions from the start. And then he moved very quickly. He was very keen to partner with us. We are keen to partner with him. We are trying not to show it too much, but we were. And then at the same time, we know that Nat and Daniel were more perceived as the angels. While we admired them from their GitHub and Xamarin days, that was still like an angel category for many of the externals.

So we knew this is our chance to bring a huge investor to actually position us as a top company. And we spoke with all the classic tier, tier one funds, and a16z was just one of So you the spoke most passionate all the

We spoke with few funds in London. Yes. And then Brian flew to London? And Brian flew to London. So Brian I mean, a16z was phenomenal. They did exactly what we spoke about, which was they’ve shown us that they cared before they invested. They introduced us to incredible people, to some celebrities to work on the voice licensing. So they were, like, on it for two weeks prior or, like, week prior already to help out in any way they could. And then Brian flew to London, met with us, then we signed a preliminary time sheet, which was interesting.

He flew in. We’re negotiating. I was on my phone call to Piotr, to co founders, like, hey, what about these terms? Can we accept this? And Piotr would give guidance on what is the hard line, what we can do. And then on speaker, we would sign together and finalize.

Oh, yeah. Speed is like for us, even from investor, from product perspective, it’s like you need to, especially now, the speed of execution, speed of investing is the only thing you have. This is what pisses me off.

A lot of great companies get built on ElevenLabs, so I get to be in the conversations now more frequently where they would raise money from our investors. Recently, we had a company raise a Series A that has built a healthcare voice bot which would effectively help patients calm them through their conversations in an incredible way. Then there’s like another company building for healthcare customer support. Quite a few. And now I’m in the conversations of them raising the money, is an interesting one. And then usually it’s clear that some of the people don’t know fully what they are actually optimizing for.

And it’s good to talk about are they optimizing for the valuation? Are they optimizing for dilution? Are they optimizing for the right brand name to help them out? Is it the network of people that this brand name has? Is it the specific partner? Is it something different? And I think it’s like pretty distributed. So when I speak usually with founders or our investors ask me to speak with the founders, it’s usually that question. Like, what is it actually that you care about for the thing? What do you miss?

And then it transpires pretty quickly whether they are going after just the roadshow that’s there to bump it up because they think the value that they the time sheet they got is just not valuable, or is it that they actually want someone else but they don’t want to they wanna keep the optionality of having the first one while while running the process.

Well, but it’s, you know, the truth is the other way is is true where a lot of the investors want to give the term sheet, but that is before any show of partnership. So how do you know that this is a good partner? How do you know whether they are giving you good terms? Especially you’re a FaceTime founder. You never run this. You don’t know how much you are valued. You need to have some relative comparison, and this can happen through conversations with other companies, other founders, or comparing yourself to other companies in the field or running some form of a process.

Roadshow probably sounds pretty bad because it sounds like a lot. You probably like the way we approach fundraising was always, especially in the early days, like queue investors we really care about and first speak with maybe one or two that maybe aren’t a priority so we understand whether the messaging that we want to put across makes sense. If it does, move straight to the the top ones. How do you feel about exploding term sheets? I don’t like them, but we got a few. We had a few through Do you understand them?

At the time, I didn’t, but I do. It’s like I don’t like them still, but I won’t name the people. But so one example was a let’s say a smaller font. They felt that if they get us the term sheet, we’ll use that to bump other term sheets. Very often happens. And that does happen. So I got it. It was like, you know and and they came from the approach of, like, if it goes too high, they won’t be able to invest, and they didn’t want to be part of that.

So that happened. Very often,

That’s what I I don’t like founders that are trying to do that too much. Like, if they are trying to get the first time sheet to bump the other ones, think it’s a wrong approach. Okay. If it’s, like, order of magnitude off, it’s probably wrong. Or it’s, you know, 5x, then yes. But if it’s like plusminus 20%, that’s like a wrong optimization. There’s just so much more value that investors, partners can give than the money itself that I think should be optimized for.

We love our partners. I mean, we have and and recent team is so so incredible, their network. I mean, now Sequoia with Andrew is just another level two, iconic team, also crazy help. NEA2 is just, like, bringing it all to US. They are all US, so I think they are playing a different game. I think the, you know, they are all, from our experience so far, a lot more keen to take the risk. Even our conversations are always like, how do we bet bigger rather than, like, optimize for the negatives?

The one check I always try to do with Piotr for any of the partners that we bring beyond the capital network brand is always for the person you partner with or the person you partner with, how will they behave if it’s not going well? So we usually try to get any of the back references for how did they behave if the company was failing. All of the ones that we had are very positive. Like they actually were really on the side of the founder, helpful when it was not going well, even more so than when it was going well.

And I was doing the same check with some of the checks with other companies, maybe this is like getting used to that. Like, you know, in US, the kind of the set of companies that went up and down is so high. But in some of the investors we spoke in Europe, that check didn’t yield the good results.

No, exactly. Yeah, Brian was one of our checks came up strongly. Jennifer too. It’s sick. All of them, it’s just a crazy ho.

I think the first piece is that more people frequently doesn’t fix the problem. It’s like you don’t need that many people to do something special. That’s the first thing. Second is by keeping and as an organization today, we are, you know, we’re two fifty people, but really it’s more like 20 teams going to market of, like, five to 10 people that are just executing on specific projects where they have higher ownership, they can move extremely quickly, they see the results in iterative reality a lot quicker to improve that, and I think this just works in such a beautiful, beautiful way.

Of course, there are other challenges with this, but Are those 20 teams organized by

A little bit depends in the product by, like, a product area. So we have a team working on our studio interface, team that will be responsible for all the core experience when you log in, team responsible for the entire voice agent suite. Within that, there’s a team working on some of the more enterprise components, another team working on some of the self serve elements. So all of the teams will be organized there on the product area. And then the other parts, we try to shard it pretty quickly.

We will have a separate team for talent, of course, then the team for people. And they will have a high degree independence when they actually execute, which helps.

You know, there was, like, moments where I could feel this kind of tension between the go to market research engineering and this is like a specific story where in 2023, late twenty twenty three, so we did a text to speech. We then did voices so we could recreate a voice. Then we create, like, a basic way for speech to text internally. So we had all the components that we originally were speaking about to create dubbing. And we haven’t done dubbing yet publicly, and we gave all the components to some of our customers so they could use text to speech, their voices.

And then there was like a lot of pressure that it’s a valuable technology we can give to our enterprise clients. One of the enterprise clients, we told them that we are planning to launch our dubbing solution combining those components later in that month. And they took the components and released dubbing two weeks before we did. And that was one of, like, the low moments for me, for my cofounder, for the entire team because dubbing was our story. We told that to everyone. We knew that this is the thing we want to solve first.

Had all the components to be able to do it. We’re just waiting to optimize it to make it perfect. And then suddenly this partner released it and got all the attention. All the media, Twitter, all the users were like, wow, this is the most incredible thing that has happened. How amazing that you can speak in another language and still sound the same. You could feel the morale in the company was low. People were like, we spoke about this. We knew for like almost two years that this is something we want to solve.

And did it happen that the customer had this and solved this first? So research engineering wasn’t happy. Like how did they do it before with the components we gave them? The go to market wasn’t happy because like how did we sell this to the customer? And now we are like all the potential clients we could have had isn’t good. And of course, me and Piotr were like, hey, this was our idea. Like, why would you do any of the partnerships if all of that is, like, kind of given to another company?

Who was the Palantir? Don’t know if I can mention. And to their credit, I don’t think that we told them it was actually a factor. I think they were just trying to do something quick. We had a lot of calls with them those days because we were thinking, like, what do we do? Does the contract give us flexibility to not continue? So we spoke through them of, hey, why did you launch? I don’t think it was dictated by our timeline, but the timeline was very close to each other.

And they told us that they thought it’s a good hack weekend idea, so they gave it to their intern. The intern has built that project, and then it exploded. But it was it did it did give them, like, in tens of millions of revenue over that period of time, so it was significant.

I don’t think the first reaction should be that, like, hey. Everything is fine. I think you should be authentic and tell the team what you are feeling, like, how has this happened? Go through, like, what have we done wrong? And, you know, that frustration was clear. I don’t think we I think it was valuable for us to talk to, like, we are angry at ourselves. This is wrong. And then as we move from that stage, like, yes, we are angry. What are we actually going to do about this?

And move to that second stage very quickly. But I think I’ve done a mistake sometimes. Was just going to the second stage. It’s not a problem. Let’s just go through and solve it. I think it’s actually super valuable to talk through what has happened. But then, you know, you need to go into the second thing, and then in the long term, that will work out. Know, it’s then you can the relentless execution will prove itself out and show it to the world. And the worst if you repeat the mistake, then someone needs to feel the repercussions.

But if you’ve learned from that and haven’t repeated the mistake, it’s fine.

I think it’s both. I think it’s, you know, the way we approach this in the company is we have research product and the ecosystem that we built, which is a combination of distribution and brand. But research for us is a head start. We are investing in research. We’ll continue investing in research. We want to be the best across the voice technologies. But all this gives to us is advantage over the competition for the next year, two, maybe three. How far ahead are you compared to the competition, do you think?

I think it depends on the use case, but six to twelve months, I would say. It’s depending on the space that we are in.

I think that’s a lot. So that research piece of six to twelve months is enough for us to then do the second thing well, which we do in parallel from the start, is build phenomenal product experience. What percent of

revenue do you

So we’ve built our own data centers. Why

So we did the math. In our case, it was if we assume we continue training the models that the way we want to, so very continuously a lot of those models. Then second, for the data transfers and as we think about continuously bringing more data, we will likely on a two year horizon break even for having our own and not renting. Assuming, of course, you you need to assume some improvement in the GPU infrastructure, but assuming that wasn’t too high of an improvement, we would have been successful.

And we were. I think it kind of the ROI made sense there. And now it pays dividends because we can just do more experiments quicker. And this can still be wrong. At some point, there might be innovation that kind of breaks that equation. But for the current time, it just makes more sense, more control.

The unit economics in most of those cases that you mentioned is pretty poor, but I think the strategy is that, yes, one, the models will optimize in cost, and then two, they will be the brands that customers trust, and then they can actually use a lot of the signal back. And I think to ElevenLabs’ example too, I think our unit economics is much healthier than most of those companies. We control our research, our product and distribution. But it’s still, if we had a new model that we need to release ourselves, we would optimize less for the cost structure so we can get that magic out quicker than other competitions even can think about creating their own model.

Well, it’s a risky business where, you know, like, there will be a winner. I love what Lovable is doing with Anthen, but Replit, v0, BOLT are all incredible companies too or products too that are doing some great work. I do think at least one, maybe more than one, will create something special. The market is so big that all of them can create something special. But yes, there will be definitely a loser and not mix too, and that company and the margins that they are carrying does just not make long term sense.

And probably the same for coding apps. But I think it’s a cool bet. I think it’s not even, like, cool from the sense of, like, it’s, you know, it’s a nice application, but it’s, like, it’s an ambitious bet that they are trying to win with the biggest companies in the world that are trying will try or are trying, and their lovables of the world are winning. Anthon is a phenomenal marketing person too, like, founder led way he’s doing it. Is amazing.

I think if you’re launching something very new, very different, and you don’t yet fully know a subset of customer base but you know that there is a bigger one, I think horizontal is is completely fine. If you know and you have domain expertise and this is the category you’re trying to win, I think go go vertical.

There are some incredible companies that, of course, did similar, Stripe being one one example. But in our case, it was especially then, super small team. So we have a team of five. A lot of people people join, and what we wanted to optimize for is, like, one, the main thing that matters is the impact. You can join and you can be the most impactful person from day zero in any of those teams. So the title shouldn’t define what is your level of decisions. Second thing with the small teams that happens is that you have a lot of those small teams.

So if you start looking at who gets the title or not, it just becomes a distraction given that teams are, like, the small units that just keep keep keep executing. So So that’s the second thing. And the third thing we wanted to, like, also make it very clear in that mix and still do. If you are joining ElevenLabs today, you can transition to being a leader of any team of any function super quickly. And titles felt limiting to that. We felt like people joining in and seeing that kind of the wider set of organization already having set of roles defined for them would make this a little bit harder.

You can have a lower tenure and be a manager of people with much longer tenure if you are the right person. Titles, we felt, were taking away from that. While at the same time, we have a good structure internally within the sub teams, like who is the current lead of that team that will make the decision if people cannot agree on what’s the right path. But that person can and and it’s not guaranteed that the person will remain a lead for forever. And the titles in a way, when you give a title, it stays stays usually forever in any other company.

We want to grow talent here. We match a lot of our current talent with the advisers from our network of US investors, and the goal is to grow people. We love growing people. Like, our approach is almost, if we can, we want to take a bet on the person growing rather than than bring them externally.

I think it is. I think it is building on hard mode. But there is some great advantages too.

I think the first one is the talent here is incredible, and I think you just need to know how to get it. What do people get wrong then? There is a good subset of people that really want to work hard and create something special, And they just don’t have that opportunity because there’s no us ambitious European companies trying to do that. So the only way they can do that is work for US companies. And I think now there’s like you mentioned, 11. I think they are showing that ambition too.

There’s like just so many more. Like, Gora recently in Sweden that rates around. We spoke about Synthesia. So there’s quite a few companies that are ambitious. They want to show. And I think that the people joining want to be part of the ambitious company that is competing on a global scale. And maybe in the early days, was, like, even worried to a large extent. I think you want to be able to build from Europe but not build only for Europe. And I think those two get conflated where sometimes building from Europe meant, okay, you are building for European ecosystem, which isn’t the right thing.

You still want the global aspiration. So even now, when I think about describing ElevenLabs, I think about us as a global company. We are a global company with we want to win in US, we want to win in Europe, we want to build in Asia. We have the best team and most of the team in Europe because the talent is incredible. So you

I think you can find people that want to work harder. And we’ve had it actually at some point in the team where we hired some people from West Coast Of US and our people where we have quite a few from Central And Eastern Europe were like, yeah, they don’t work actually that hard as we do. I mean, we have such a, you know, to credit to the team, it’s like the true missionaries that are there on the weekend all the time and really care. They really care about the success of the company.

Beyond just working hard, I think they are and they feel part of the company, which is true. So I do think you can find the people in Europe that are phenomenal.

It’s an interesting one because we, you know, in the early days, we didn’t have much inbound. So all of that was outbound. And it was easier in a way to find people that we felt were right because you didn’t have to filter through the noise. And now we have just so much where so many people are going because the AI buzzword or, you know, we now are at scale. That makes sense. But no, I think it’s, you know, it’s fine. Like, not everybody is the risk taker at the same amount, so I’m not in any way discarding

I think the, you know, this is probably a traditional one, but as I think about kind of bringing people in and growing them into the company as like the full hiring process, you hire a person, you of course have very little time frequently to assess how they are, but then as they are in the company, have a little bit more of the signal. I would have taken some decisions quicker than I would have with separating with people. If you are not unsure in the interview, but let’s say you are bringing them giving them a chance and you are not sure in the first weeks or months, you should separate straight away rather than keep giving giving the chance.

I think that’s the the few times I’ve think I’ve done that.

Researchers.

So we interview everyone and I help you You

Yes, we do. We hope to interview that as long as possible because it’s a good signal of who we bring into the company. We get to meet them, but of course, still think the company is, like, still shifting in terms of how we are approaching that. One is now even more we are optimizing for, like, engineering technical skill set in all parts of the company than we would have six to twelve months ago. So it’s even increasing in some aspects. But I hope we’ll interview to, a thousand people.

The thing isn’t so much hard, you know, when to be involved in the interview. It’s more how many people you are trying to hire within a specific period of time. So if I try to hire a thousand people in a month, it’s impossible because it would be more than the time we have. In a year, how many people will you have? We’ll have 400 by end of the year. By the end of this year? By end of this year.

We have 50 offers or so are, like, joining. So twelve fifty now, roughly 30 to 50 people that are already scheduled to join, and I think we’ll get an additional 100.

150 in three to four months. Still small and still mighty, but we have a pretty global team now where we are trying to bring a lot of our go to market and engineering in every location we are at. So we think we can parallelize that, building Brazil and Japan and India and Mexico. So we are really going to that local new ones too, where we are building small outposts everywhere. And I think we can make it work. Do you care about revenue per head? In the long term, yes.

Like, we want to be an efficient company. I think now we are we have a very good metric for revenue per head. You know, it’s a good show, like, are you an efficient company? But if we think there is a path for us to get there over time, we take easily the new hires that can help us. You know it extremely well as an investor, but of course, one of the key metrics is retention or like how you think about NRR for any of the clients.

So me bringing people now, helping us get the distribution before competition does, might decrease my set of revenue I get. But if the NRR keeps growing and I don’t hire more people in the next five years, that metric, of course, will change.

we crossed 200,000,000

35,000,000. 35,000,000. You went from beta launch in January. To 35. We did so we did twenty months to 100, and then Twenty months to a 100,000,000. Yes. I think so. Like that. And then around ten months to 200, a bit longer. Fifteen months, maybe. Just crying. Is that right? He’s dumbass.

the thing is that, of course, you know, if it goes quickly, it can also go quickly down.

I think it’s relatively sticky. You

biggest part of the business now and where we’re obsessing is building effectively conversational agent platform. Like, the biggest customers are But building

Our biggest contract is around 2,000,000, and they are mostly in a call center, customer support, personal assistance base. All of those companies are orchestrating combination of the research, so speech to text, analytics to speech, and then bringing a lot of those integrations that now we create. So that’s on the enterprise side, whether it’s Cisco, these are not the the contracts there, but Cisco, Twilio, recently working with Epic Games. These are some of our biggest the biggest deployments of the work. And then, of course, on the we are in a lucky position that we still have a huge self serve distribution of creators and developers building all the time.

Ten months to

We would love to break break if it’s a healthy revenue and we are creating good work, we would love to break the record.

somewhere between 100 and 120, I think.

We announced it January 25, and then we did that towards end of twenty twenty

So we did the round in October ’24, so we were probably at 80 when we got the docs and then it was signed then. Did you need the money? So the way we approached any of the fundraisers, it’s can we bring some of the bets forward? In that case, it was even more, spend on models, expand it to multimodal. Can we bring our work internationally, so expand into other regions, and then double down on Agentic platform? So start building even more of the true enterprise functionality, whether it’s the reliability you need, whether it’s integration with Salesforce, ServiceNow, SIP trunking.

So, like, investing in those, those was the most important. But at the time, it was 30x current revenue, so pretty good then.

I think that the kind of the variation of this is, like, can you paralyze a new effort without distracting the core work? And that’s roughly why we are trying to approach this. Like, can we bring our work to a new place? Can we create a new product experience without affecting the core thing that’s actually important for our users? If we can, then we’ll likely invest, bring the people into it. If it’s distracting, then it becomes a question of, like, is worth upside?

It’s it’s interesting because it’s on the on the relative basis. I think the our agents’ work is already huge, but I think it’s just scratching the surface. I think it’s going to if we play it right, it’s like a multibillion dollar revenue generating business just from huge, of course, creating voice agents and going deeper. So I think this one is on, like, on the relatively And these are

And then you can go deeper. You can, of course, expand from voice into conversational agents. And by that, I mean you start building omnichannel solution with email integration, WhatsApp integration, which is kind of that, you know, more classic customer support. Would

Today, so we have a public partnership with Decagon, so we do. But of course, as you start going deeper, it depends a little bit where Decagon goes and where we go. Are they going to verticalize or they will continue horizontal and go down? Well, we verticalize more. So there might be some areas where we overlap a little bit more. But today, given we have a very partner horizontal approach, we treat all of them as good partners.

We do. But the the way we’ve seen this, like, kind of transition happen now is where you will have more specialized humans, where the agents are taking more of the manual parts that nobody really wanted to do or didn’t require domain expertise. So like a good example is like if you’re taking appointment scheduling, if you are doing a refund, all of those, of course, assuming you have the safeguards and authentication in place, are pretty easily done with AI. But then suddenly, if you need to help that patient navigate the outbound flow after going from hospital or understand analysis, That cannot be done with AI.

There’s too much at stake, and you need a deep domain expertise. So we’ve seen, like, kind of the transition where that side of people helping in that kind of last mile is even more valuable. Well, of course, AI can help with those easier tasks across. And I think this will continue. Of course, the percentages will shift where you will have even more automation as it goes deeper and then even more value assigned to the people doing that domain expertise because, ultimately, it will help automate the task at hand.

You know, like, I think so so our first round was with a 16 z, it did meaningfully move the needle for us. Like, it was very clear that people

And then Sequoia came in in Series B, and that’s kind of doubled down that perception where it’s like, okay, a16z and Sequoia are part of company. It’s also very rare to have both of these investors in any of the companies. So it did help, like, where a lot of clients would be respecting that. And now Iconic on top of that is just incredible mix. And NFTG2. I think NFTG2 is like clients will usually not have that perception, but the Investors do.

investors do. And some of our engineers or users really, really admire and trust Nat, and I do too. So he’s great.

We always will do, like, the basic diligence and let our investors know that it’s, you know, that we had this. You What was the largest one? Well, the largest one didn’t have money, so but the ones that we went, it was like an interesting conversation because we would frequently try to, like, go into with the strategic partnership and then they would be like, Oh, can we consider, are we open to M and A activity? Was it tempting? It was tiny bit tempting, but in a way where in the first one or two examples.

So the first one was when we were doing Series A. It was going really well. And then, of course, we like were unclear how this will continue. It was like a very beginning of the curve. And the first one was like, Okay, this is first time we ever are doing this. Let’s understand what they are offering. But we were more interested into like seeing whether more about the process itself, like how it happens rather than actually giving the company. Then it was clear, okay, they actually want to acquire us.

This is what we understand and we need to be part of the company. So we were a flat no. And since then, for any of the conversation now that we know that this is even approaching this M and A. Did you do secondaries? We did secondary. And that helps. So we do almost every round we can. We do secondary and a tender offer for all employees that have vested stock so they can sell the stock. So they all feel that there’s actually liquidity to the company.

And I think it’s valuable because we are betting for something huge, and you want to know that you can take the risk to bet on some big outcome, which, of course, you know, like, think it’s very easy to say financial imperative is not important, and I think it isn’t, but there’s, like, this basic layer that people want to I think is.

like, it’s not the goal in itself, but you want to have, like, this bottom set of good life that’s covered, which we are extremely lucky as a company to have and to be able to offer. But then, like, now the kind of the aspiration is much bigger, especially now that this basic layer is covered. The thing I

I think it does help with, like, the perception where, you know, there’s like you can, to some extent, I think you can put away, like, any of the greediness that comes with money just by taking some of the risk risk equation away.

That you can build a company from Europe at a global scale.

I think you are helping, and I think many of the people in our ecosystem are, but I don’t think most people do. Maybe another one which is not that specific to company building, but I do think voice will be the interface to the technology around us. It will be the primary interface for all of technology around us.

Well, I don’t know if I like this question. The Antoine answered it.

Okay. Let’s keep it at a positive. I would buy OpenAI. But I love Anthropic. Like, you know, if I was on the coding side, I think I would be buying Do you mandate Cursor? No. We don’t mandate. It’s like you you use what you what you think is most valuable to What

Most people do use Cursor. Some people use Cloud Code, but still more Cursor. I think it’s shifting a little bit. I’m also, you know, to your other question, I remember who was the investor, but they did say, which I think I would also, like, as I think about that decision is I would be happily investing in a lot of the products I use, and I do use ChatGPT very often. Every so often, will use Anthropic for, like, testing where we are with the space, but I think they are investing more in coding rather than cloud the consumer, and OpenAI is clearly investing a lot in ChatGPT, the consumer solution.

That we previously would not do any of the product innovation if we knew that we are doing any research initiative ourselves. And I think now it’s shifted that we will sometimes explore product with outside research even if we don’t have we we don’t build it internally.

Depends on time horizon. But but in general, yes, I think speed of ARR growth doesn’t doesn’t matter.

I really like Eight Sleep. I don’t know if it’s a consumer brand, but I do like Eight Sleep recently as as as as as like, changed quite significantly. I am a huge user of of Google Google Maps and love Google Maps. Lovable, I really like, from consumer ish applications.

I’ll choose Google or OpenAI. I would know the know how of some of the incredible model. I think more Google. I would say Google. Genie, v of free models, incredible innovations, and then at the same time, just the, you know, the scale of operation would be interesting. You’re super bullish on Google. People question them with the

Yeah. They didn’t give me Google in the previous question.

Yeah. Would invest in Ambeth for $300 with Google, but that’s not an option. But you’re super

No. No. It’s, like, super bullish. Definitely not super bullish, but I I think Google is I would still put a lot that Google has a good future. And especially recently, they are catching up in many places. They are definitely in the race.

My word goes into law immediately. Yeah. I would proxy a lot of AI law to US law. I know this has a huge set of repercussions, but I would try to follow exactly how US is approaching a lot of AI related regulation and just implement the same. Or let’s create another state in European Union and Europe that people can opt in that follows that law to not, like, make it too hard given given

My answer here would be I don’t know because in in many ways, as we thought about the ElevenLabs, especially in early days, it’s the people that build the company are the people that build the company. And in some ways, they kind of could still don’t know to what extent, like, having some people that are very much out there, like, let’s say I’m now in this podcast, takes away from that. And we want to make it complementary because the reason we are successful I think is to a large extent because we’ve created incredible research.

The engineers are just grinding and creating the best product experience. The go to market team is inventing new ways to combine self serve and sales. So it’s like all those parts and then supplemented by operations scaling the company from less than 100 to now two fifty in a span of seven months while keeping culture intact. You know, these are like all so hard things. With hypergrowth, there’s less time to be able to appreciate all those individuals than you would otherwise. And I sometimes worry by having that kind of, you know, too much of the founder brand kind of takes away from that.

But my mind is changing a little bit. I think like maybe you can elevate that by having a a founder brand out there.

Well, the I don’t it’s not most often. So in the in the recent times, I I like what what Peter Thiel said about the biggest risk is not taking the risk and, like, kind of staying, kind of not taking a decision or staying What risk did

It’s shifting because if you ask me that, should have taken that risk. So I don’t usually I usually try to to, like, take a quick action on on top of that. But one that that is we are considering is an acquisition of another company now, which is a big company. And that company, you know, is in hundreds of millions of dollars. It will be a huge risk for bringing them in. And we think we can do better internally, so I think we won’t take that risk.

Thank you, Harry. It’s a pleasure pleasure to be finally able to speak together.