ElevenLabs just hit $6.6B, but its CEO says the real money isn't in voice anymore

Ready to ship AI that works? Start building at mongodb.com/build. Hello, and welcome back to Equity, TechCrunch's flagship podcast about the business of startups. I'm Rebecca Balan, and this is the episode where we bring on industry experts to help us explore a trend in the tech world and dive deep. Eleven Labs has made a name for itself building realistic AI voices. What started as two Polish engineers annoyed by terrible movie dubbing is now a $6,000,000,000 company that's not only profitable, but also going toe to toe against OpenAI to power everything from Fortnite characters to customer service bots. Today, we're bringing you a conversation with ElevenLabs CEO, Mady Stanashevsky, from this year's disrupt, where he made a surprising admission. He thinks voice models will be commoditized in just a couple of years. So what's ElevenLabs' plan when everyone else catches up? Let's take a listen. Thank you everyone for being here. I'm joined today by Matty Stanishevsky, the ElevenLabs cofounder and CEO. Matty, thank you for being here. Thanks for having me here. Hi, everyone. We're gonna get right into it. ElevenLabs makes AI audio models, AI voice models, and there were a lot of startups training AI foundation models a few years ago, and now there are far fewer. But ElevenLabs has managed to stick it out and actually grow quite a bit in the last few years. You have a lot of products right now. There's a lot of things that you guys do. I wanna get into them. But what's your biggest focus today? As a company, one thing that we are aiming to solve is how humans and technology interact. So a lot of the work that we do underpins that common mission. And effectively, as you think about a lot of the problems that we solved across the history, it always started, what's the problem? Can we solve it? What's the next problem that we came across the scene? So like you said, we started with voice. So one of the key things that came when we were starting the company is that a lot of the technology around us just didn't sound human. You had a lot of the knowledge information that just wasn't accessible, and we tried to solve this for creating our own text to speech model and our own voice models to make it sound human. And then the next thing came about which is to be able to create a lot of that incredible work, you need a lot of more than that. You need sounds. You need music. You need understanding of speech for speech to text. So we time and time again started building that across and built effectively our creative platform offering for creatives in the space. And then more recently, and I think that's the the biggest focus across the company over the last two years, we realized that there is a big shift from static information into dynamic information where finally you …