The Future of Voice AI: Agents, Dubbing, and Real-Time Translation with ElevenLabs Co-Founder Mati Staniszewski

0:05Hi, listeners. Welcome back to KnowPriors. Today, I'm here with Maddy Stenzuzzi, the co-founder and CEO of 11Labs, which was founded to change the way we interact with each other and with computers with voice. Over three short years, they've skyrocketed to more than 300 million in RunRay. Madi and I talk about the future of voice, education, customer experience, and the other applications of this voice, as well as how to build a multi-segment from self-serve to enterprise and combined research and product company. Welcome, Madi. Sarah, thanks for having me. And thank you for doing this at seven in the morning.

0:40Our pleasure. Thank you for doing that at seven in the morning. It's great we got to finally do this together. I think a lot of our listeners will have used or played with Eleven at some point, but for everybody else, can you just reintroduce the company? Definitely. At Eleven Labs, we are solving how humans and technology interact, how you can create seamlessly with that technology. What this means in practice is we build foundational audio models. So models in a space to help you create speech that sounds human, understand speech in a much better way, or orchestrate all those components to make it interactive.

1:13And then build products on top of that foundational models. And you have our creative product, which is a platform for helping you with narrations, for audiobooks, for voiceovers, for ads or movies, or dubs of those movies to other languages. and our agents platform product, which is effectively an offering to help you elevate customer experience, build an agent for personal AI, education, new ways of immersive media. But all is kind of under light with that mission of solving how we can interact with technology on our terms in a better way. You started the company in 2022. That's right. And you've had amazing like rocket ship growth since then.

1:51I'm sure it's felt up and down different ways. I want to ask you about that. Can you give a sense of what the scale of the company is today? So we've grown to 350 people globally. We started from Europe. We started as a remote company and are still remote first, but have hubs around the world with London being the biggest, New York being second biggest, Warsaw, San Francisco, and now Tokyo and one in Brazil. We are at 300 million in ARR, which is roughly 50-50 between self-serve. So a lot of subscription and creators using our creative platform and then approaching 50 % on the enterprise side using our agents platform work.

2:30And that's on the sales led, classic sales led side. And we serve more than 5 million monthly actives on that creative side of the work. And then on the enterprise side, we have a few thousand customers from Fortune 500 to some of the fastest AI growing startups. I think this is such a you're an amazing founder, but I also think it's such an interesting company because it is very unintuitive to I think many people and investors in particular. I don't know if you face this at the beginning, but I remember there in 2022, there's a there's a class of companies that allow creation in some way. And when we look at your like first business beyond the research itself, and I would put Eleven and Mid Journey and Suno and Haitian in this category.

3:14And I think there's like this overall sense of like, who really wants to do this? What was your initial read of like how many people want to make voices or what made you believe that was going to be much broader than like if I look at dubbing, for example, it's not a huge market. I think first piece was, which is, as you mentioned, there is like a very, it's very tricky to do both the product and the research. I'm in a lucky position that my co-founder and I know each other for 15 years. I think he's the smartest person I know and has been able to create a lot of that research work to be able to create that foundation to then elevate that experience.

3:51But both of us are from Poland originally. And the original belief came from Poland. It's a very peculiar thing. But if you watch a movie in Polish language, a foreign movie in Polish language, all the voices, whether it's a male voice or a female voice, are narrated with one single character. So you have like a flat delivery for everything in a movie. A terrible experience. It is a terrible experience. And it's still like if you grow up, as soon as you learn English, you like switch out and you don't want to watch content in this way. And it's crazy that it still happens until today in this way for majority of content.

4:24Combining that and I worked with Palantir, my co-founder worked at Google. We knew that that will change in the future and that all the information will be available globally. And then as we started digging further, we realized. In every language, in a high quality way. Exactly. That was kind of the starting point. And the big thing was like, instead of having it just translated, could you have the original voice, original emotions, original intonation carried across? So like, imagine having this podcast, but say people could switch it over to Spanish and they still hear Sarah, they still hear Mati and the same voice, the same delivery, which is kind of exactly what we did with Lex back when he interviewed Narendra Modi.

5:05And you could kind of immerse yourself in that story a lot better. so that was the original uh kind of insight and um and we we then started digging further which is that just so much of the technology we interact with will will change whether this is how you create it's still relatively tricky to bring voice alive you you you you would you would need to go through the expensive process of hiring a voice talent having a studio space having expensive tooling to then actually adjust it the tooling isn't intuitive to be able to do this so like all that creation process will and should change to make it easier for new people with keenness to bring that alive, then a lot of the technology wasn't possible for you to be able to recreate a specific voice or be able to create that in that high quality way.

5:53And then of course, as we dived into further and shifted away from the static piece, the whole interactive piece is still crazy in the way it functions where most of us have seen this technological evolution over the last over the last decades, but you still will spend most of your time on the keyboard. You will look at the screen and that interface feels broken. It should be where you can communicate with the devices through speech, for the most natural interface there is, one that can have started when the humanity started. And we realized we want to solve that. And I think now fast forward from 2022, I feel like many people will carry that belief too that voice is the interface of the future.

6:33As you think about the devices around us, whether it's smartphones, whether it's computers, whether it's robots, speech will be one of the key ones. But I think 2022, it wasn't. And as you think about the market for the creative side or for that interactive side, it was like very clear it will be a huge, huge, huge one. So even when you think about just the research part of your business and then you have products for at least two different markets and then you have this larger mission, a lot has changed in the last five or 10 years. But it used to be like a very strongly held traditional belief of like one must do one thing well in a startup and there's no other path.

7:11Like you're treating this like an interaction company, a platform company. How did you think about sequencing like the research and the product effort? Does that make sense? Or like thinking about new markets? And maybe wrapped up in that question, too, is just like, well, where are we in quality on voice as well? Because if I would sort of claim like if the models are not good enough for certain use cases at all, like it kind of makes sense. Do product? And I think that's right. It's almost exactly like when we started. Originally, what we did was try to actually use existing models that were in the market and kind of optimize them for our first use case was actually starting with a combination of narration and dubbing.

7:51And then on that creative side, and we realized pretty quickly that the models that existed just produced such a robotic and not good speech that people didn't want to listen to it. And that's where my co-founder's genius came in, where he was able to assemble the team and do a lot of the research himself to actually create new version of creating that work. But like to your question, I think that the way we are kind of organized internally and how we think about sequencing a lot of that was looking at the first problem and then creating effectively a lab around that problem, which is like a combination of mighty researchers, engineers, operators to go after that problem.

8:28And the first problem was the problem of voice. So how can we recreate the voice? And like you say, it needs to have that research expertise to be able to do that well. So we started with effectively a voice lab, which was that mission of can we narrate the work in a better way? There was a combination of roughly five people that were that we're doing that work and then sequence the research first and then build a simple layer on top of that work to allow people to use that work and then kind of expand it from there with a holistic suite for creating a full audiobook and then creating a full movie narration, a movie dub.

9:04And then we move to the next problem, which is realization that, okay, we have solved the voice, great for making content sound human, the first problem. For that to be useful for us to interact with the technology, you need to solve how you bring the knowledge on demand into that. So we effectively started then the second team, which was a second lab, an agent lab effectively, which was a team that would combine researchers, engineers, and operators once more, which would try to fix, okay, we have text to speech. How do they now combine this with LLAMS and speech to text and orchestrate all those components together while integrating that with other systems to make it easier?

9:42And then similarly, you know, You kind of expand from looking just at the voice layer into how those systems work together. And here too, you need a research expertise to do that in a low latency way, efficient way, accurate way. But at the same time, there's that product layer that starts forming that it's not only the orchestration that matters. It's also the integrations of how you link up to the legacy systems, how you build functions around it, or how you deploy that in production and test, monitor, evaluate over time. Do you feel like you were creating new use cases when you built the tools?

10:15Do people know that they wanted to do this already? Because one argument like that I remember hearing was like, ah, like, you know, enterprises don't know what to do with voice, how many people really want to do it? And then you're serving essentially like, perhaps the like creator publisher side of your business. Yeah. it's definitely a combination of like initiatives that we believe will happen in the world and then like response to a lot of that like as i think back we you know of course voice the internal voice lab or agents lab then kind of that kick-started so many of the other labs in response to the problems we started a music lab because people wanted to create music with 11 labs so it's a fully licensed model where people wanted to use and create speech but they wanted to add music in a simple way.

10:58We wanted to deliver that. And then, of course, that kind of came together through how do we combine music, audio, sounds. We are now integrating partner models from image and video into that suite. How could you combine all of that in one? And all of that was in response to the market saying, hey, we would love this. And then you will have completely different use cases, even in that space. Let's say dabbing. Dabbing is a use case that we didn't feel there was like a big push for that. But we knew that in the ideal world in the future, you will be able to have that content delivered naturally around the languages, still carrying that.

11:33And I still think actually this market will be immense because it's not going to be only the static delivery in movies. But if you travel around the world and want to communicate in real time, like the full bubble fish idea from Hedgehiker's Guide to Galaxy, this will happen. It will be like the biggest, like the whole breaking down language barriers that are the barriers to communication, to creation, like all of that will break. And that will be like the foundational real-time dubbing concept. So super excited about that part. And similarly, on the agent side, you are like some obvious things that, of course, customers that we work with or partners will want to integrate, which is we want integrations with XYZ systems.

12:13But then there are like other parts that might not be as easy to predict of as you interact with technology, of course, want to understand what's happening, but you also want to understand how the things are being said and bring that into default, which would be something we try to prioritize on our side. So then the people, when they actually interact with the technology, they realize, oh, expressive thing is actually so much more enjoyable and beneficial and helpful. So I want to ask you a question about this, which relates to quality. You know, I work with a series of companies where we're selling a product to the buyers are generally not machine learning scientists, right?

12:49And even the scientific community does not have the like full suite of evals and benchmarks to understand every domain well. There's a well-known problem. But I imagine for a lot of your customers, it's not like they like know how to choose good voice. So how do you deal with that problem? Like, is it like, hey, I make a clone and like that sounds like me and I believe it. I'm going to try all of these different options or, you know, actually, are you teaching people to do eval? It's a great question because I think there are like two big problems. One is like, how do you benchmark the general space in audio where, like you say, it's like so dependent on the specific voice, let alone like if you are training into interactive, then it's like even more tricky.

13:31And then the second piece, which is as you are working on a specific use case, how you select a voice. So I'll take the second one first, which is we have like a voice sommelier, effectively with us we work with with enterprises we we deploy that person to work with them and help them navigate that person is like a voice coach has an incredible voice themselves and uh and now we have like a team under that person that like will partner to help you find what's the right branding yeah and now you have like the celebrity marketplace and now we have a celebrity marketplace to like help you even get the iconic talent in there like sir michael kane that piece was important because of course their voice will depend on the use case that you are trying to build the language all of that will will have an impact of what's the right voice for your customer base so we have effectively a a voice person helping those companies and some companies will be very opinionated on one day one so they will sometimes select it themselves sometimes give us a brief of hey we want a voice that sounds professional neutral is coming we recently had a company, one of the biggest European companies that wanted, that gave us a brief, which is very original, that they wanted as robotic voice as possible.

14:42Okay. Which was counterintuitive. Yeah. And you're like, we can't do that anymore. Almost. But we were like trying to go backwards of like, how do we do that? But I think we got a good result. But recently we had a company in Japan where, Japan and Korea, where they wanted to serve different voices depending on the customer that's calling in they have a older population and very younger population the younger one they wanted like one of the famous voices in the market that's very excitable and happy uh and for the older one they wanted like a calm slow speaking one we help a lot with that so that's on the voice piece and i do think it's going to be a big it's like a personalized choice and then it can even be dynamic customer yes okay exactly exactly and then maybe in the future it's like going to be like fully depending on your interaction you will have a voice created as we understand the preferences of what people want so you know like let's say you are in the evening and you are tired and you want a slightly different or maybe not maybe that's like the best uh a focus time that you have like a voice that's that's giving that energy and probably it's a different when you wake up and gives you the morning news of what's happening or what's the weather so like all of those could be different yesterday we had a we had a dinner with some of our our partners uh and one of them the first thing they said is like hey I have a new request for you.

16:00I want a New York voice with a Long Island accent, which I never knew is a thing. And it's supposedly a thing. So we have that. And then on the first piece, I think it's unsolved problem still, where I think you have a good benchmark. Of course, in LMS, I think in image space, they are pretty good. In voice space, you have, of course, the speech quality, but then so much of whether you like or not the speech depends on the voice that just if you compare model A to model B, and you serve them different voices, even if the quality is very different, the voice itself can just make that so different.

16:36We've seen this, I don't know if you know, artificial analysis, benchmarks. I think they're pretty good. Just switching the voice makes such a big impact. That's so interesting. Yeah. And I wonder if, as you said, this is the most dominant interaction mode we'd had for millennia of all of human history, right? I'm biased in self-serving, but I think so. We're just very sensitive to it. And I think people are going to be very sensitive to their own personalization as well. 100%. I think there's also a third piece, which maybe is not directly to your node, but we've also realized that you have the benchmarks, you have like, how do I find the right voice for my audience?

17:14But even the understanding of how you describe audio data is still lagging in the industry. Like when we initially started, we of course went into the traditional players for them to help us label not only what was said, so like transcription, but also how it was said, like what are the motions used, accent. And most people just weren't able to do that work effectively because you kind of need to hear and have like a little bit of a skill set of like, how would I describe this specific delivery? So we needed to create that ourselves. So I think there is that piece as well. Like how do you effectively interpret the data of audio in a more qualitative basis?

17:51That's, yeah, trickier. Can you talk about what's happening on the agent platform side? Like what is challenging for, you know, businesses or even creators that are trying to build agents and what the maybe what the surprising or high traction use cases are? I think everybody's kind of aware of the idea of like agent based customer support, but I imagine you're doing many things beyond that. Yeah, so that exactly. Customer support is probably the one that's like kicking off the quickest. And that's the one that like we see overtaken so many use cases. whether it's where I work with Cisco or Twilio or Tels Digital, all of them are kind of elevating that to a high extent.

18:29I think the second exciting piece within that domain, which is happening, is the shift from effectively a reactive customer support. I have a problem. I'm reaching out the customer support into more of like a proactive part of the experience customer support. So to make it explicit, we work with the biggest e-commerce shop in India, Misho, where they started working on the customer support side, where I want a refund, I want to see the tracking of the package to actually having an agent be a front part of the experience. So if you go to the website, you have the widget, you can engage it through voice and you can ask it, hey, can you help me navigate to item X, item Y, or can you explain what's the right thing for me to give up for a gift for this period of time?

19:17And then it will actually help you based on your questions, based on what is on the offer, show you those items, navigate to the right parts of the piece, maybe go all the way through the checkout. And I think this will be a phenomenal thing of like elevating the full experience where that's more of an assistant across the whole thing. We got kicked off our work with Square that enables all the businesses to do that work. Exactly the same pattern. Started with voice ordering. How can now this be part of the full discovery experience too, where you get items shown to you, you can have a lot more explanation, which I think will be a phenomenal piece where it's effectively from the beginning to the end.

19:51That's one category. The second one is the wider shift from static to immersive media, where there's just so much incredible stories in IP that today exist in effectively one way of delivery. And now you'll be able to interact with that content in a completely new way. I think one of the incredible use cases was working with Epic Games. We worked with them on bringing the voice of Darth Vader and Darth Vader into Fortnite. where millions of players could interact with Darth Vader life in the game where you had like a full experience of Darth Vader in a new way. And I think this will be a theme across whether it's talking to a book, talking to the character that you like to the whole space shifting.

20:37And then I think the one that I'm most excited about for the world and for the shift is going to be education where you will just be able to have effectively a personal tutor on your headphone. It could actually study something in an amazing way. I'll give you two quick examples. One is we recently worked with chess.com. I'm a huge fan of chess. I'm a huge chess fan. Okay, great. So you can learn chess, but you can have Hikaru Nakamura or Magnus Carlsen be your teacher of how you deliver that, which is amazing. Or even Botte Sisters. It's like all the plethora of different players that engaged with that, which I think is great.

21:19And then maybe a last one, which is a masterclass we worked with to shift from, you can of course have the content go through step by step, but you can also have like an interactive experience. And the best example of that was working with Chris Voss, the FBI negotiator, one of the top negotiators, who has a masterclass lesson. But then you can actually call him and have a practice negotiation, which is crazy. Yeah, got to get that hostage out. We'll definitely try it. Yeah. Can I add one more? I think the one last one, which combines all of them together, which I realized just recently is, which was crazy.

21:54So recently I went to Ukraine where we are working with Ministry of Transformation where they are effectively creating a first agentic government. And the crazy thing is they have all of those - Agentic government. Agentic government. Okay. So they want to like re-change of how they run all the ministries. Okay. And it sounds like a big ambitious goal and lofty. No, I think the baseline is like here. So actually I'm by that immediately. Yeah. And the crazy thing is, I think they are like so ahead in actually doing that. And I think they are like two concrete things there. One, they kind of combine all those use cases.

22:31So we are looking into how they can have effectively customer support of government, whether it's asking about benefits or employment, about process of how you leave the country. All of that be run through effectively a digital app. Then two, how we can have proactive way of informing citizens of things that might be happening. But then having education system that also run through like this personal tutoring experience. And all of that is happening. So that was incredible to see. And the second amazing thing was that the way they've done it, so they have the digital transformation piece, but they have engineering leaders in each of the ministries that lead those efforts and then bring them back to that one central piece.

23:09So that is like incredible to see and also proud to be able to be working with them on that shift. But despite everything that's happening, they're like so leading it. That's amazing. That's really encouraging. Can I ask a business model question here? Because looking at the strategic landscape, actually, I have many questions here. One of the observations I'd have is if I look at one of these rich voice and action agent experiences, it's a lot of, let's say, Fortune 500 Global 2000 leaders who listen to the pod. They, I think a lot of them are going to buy the idea of like, I want this amazing, automatic, like real time available 24 seven, every language experience for my customer.

23:54That's consistent and high quality. The ways I might get there include working with a Palantir or a large consulting firm, working with 11 or a like platform technology company or like an open AI or something. Right. Let's talk about that. Or working with a sort of more use case oriented company like Sierra. Right. How do you think about how people are making that decision or how they should make that decision? So my past is also in Palantir. So I started exactly from that side. And we do blend a lot of the forward deployed engineering inside of the company too. As I think about the kind of our offering and the customers making that choice, if you're looking just like one pointed solution and only that one, then likely we aren't the best choice.

24:45If you are looking to deploy that across a plethora of different experiences, so be it customer support, but then you also want internal training And you might want to elevate your sales part and actually increase the top line with new experiences of how you engage customers beyond that kind of reactive piece. Then it's a great platform to build. And then we effectively, as we engage with customers, combine that platform work with our engineering resources to help those companies deploy on that. or which we also see increasingly in Fortune 500s, G2000s, where they will want to build parts of the things themselves because they already have a lot of the investments in that platform while then engage us on some of the new ones and combine those.

25:28And I think that our model and the way it's different to a lot of the use case specific ones is that our platform is relatively open where you can use pieces of that platform and not all of them for those different use cases. Because Palantir, of course, or some of the consulting companies will have a lot more resources to go in the wider digital transformation journey. In our case, it's like very specific conversational agents. Like if you are looking for new interface with customers, that's the best way. And companies like Sierra, phenomenal, of course, on how they are thinking about the specific pointed use case.

26:04And maybe the other piece is like a sweeping about our work, depending on what you are optimizing for. So we have a lot of international partners. If you have like a wider geographic user base, great. That's what we optimize for. Our voices, our languages, our support for integrations internationally are just so much broader. There's frequently a piece that you will look into. Depending on your exact scope, this will be a big factor. but I would summarize that if you are looking for a solution across a set of different use cases that you want our engineering help and deploy that then we are the right solution and probably the best solution.

26:43I want to talk a little bit about maybe like OpenAI and the foundation LM foundation model companies. One of the reasons a lot and I call this podcast no priors is because we're like okay people are making a lot of assumptions all the time about how the market is going to work and lo and behold like many of those assumptions end up being nonsense actually. And you can't, you have to very much decide your own narrative at this point in time. I think, correct me if I'm wrong, like in 2022 and 23, you probably heard a lot of people say like, Google can do this and OpenAI can do this. And like, why do you get to persist working on voice anyway as a general capability?