The Future of Voice AI: Agents, Dubbing, and Real-Time Translation with ElevenLabs Co-Founder Mati Staniszewski
Episode
41 min
Read time
2 min
Topics
Productivity, Startups, Fundraising & VC
AI-Generated Summary
Key Takeaways
- ✓Multi-segment business model: ElevenLabs splits revenue 50-50 between self-serve creator subscriptions and enterprise sales-led agents platform, serving both individual audiobook narrators and Fortune 500 customer support systems with the same foundational voice models underneath both product lines.
- ✓Voice quality differentiation: Audio AI requires architectural breakthroughs over compute scale. ElevenLabs employs roughly 10 of the estimated 50-100 top audio researchers globally, focusing on controllability and emotional expression rather than just transcription accuracy to beat larger labs on benchmarks.
- ✓Research-product sequencing: Teams get three months to ship product solutions before waiting for research breakthroughs. This parallel approach prevents product roadmaps from stalling on uncertain research timelines while allowing engineering to build integrations and workflows that capture value when models improve.
- ✓Cascaded versus fused architectures: Enterprise conversational agents require cascaded speech-to-text plus text-to-speech systems for reliability and tool-calling capabilities today. Fused speech-to-speech models enable more expressive consumer experiences but lack the structured control enterprises need for production deployment over the next year.
What It Covers
ElevenLabs co-founder Mati Staniszewski discusses building a voice AI company from zero to $300M ARR in three years, spanning creative dubbing tools and conversational agent platforms serving 5M monthly users across enterprise and self-serve segments.
Key Questions Answered
- •Multi-segment business model: ElevenLabs splits revenue 50-50 between self-serve creator subscriptions and enterprise sales-led agents platform, serving both individual audiobook narrators and Fortune 500 customer support systems with the same foundational voice models underneath both product lines.
- •Voice quality differentiation: Audio AI requires architectural breakthroughs over compute scale. ElevenLabs employs roughly 10 of the estimated 50-100 top audio researchers globally, focusing on controllability and emotional expression rather than just transcription accuracy to beat larger labs on benchmarks.
- •Research-product sequencing: Teams get three months to ship product solutions before waiting for research breakthroughs. This parallel approach prevents product roadmaps from stalling on uncertain research timelines while allowing engineering to build integrations and workflows that capture value when models improve.
- •Cascaded versus fused architectures: Enterprise conversational agents require cascaded speech-to-text plus text-to-speech systems for reliability and tool-calling capabilities today. Fused speech-to-speech models enable more expressive consumer experiences but lack the structured control enterprises need for production deployment over the next year.
Notable Moment
Staniszewski describes Ukraine building the first agentic government, deploying voice AI across all ministries for citizen services, benefits inquiries, and personalized education tutoring, with engineering leaders embedded in each department coordinating the digital transformation despite ongoing conflict.
Episode Transcript
Hi, listeners. Welcome back to No Priors. Today, I'm here with Mahdi Saines, the cofounder and CEO of Eleven Labs, which is 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 300,000,000 in run rate. Mahdi 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, Mahdi. Sara, thanks for having me. And And thank you for doing this at seven in the morning. Our pleasure. Thank you for doing that at seven in the morning. It's great we we we 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. We, 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, and then build products on top of that foundational models. And we have our creative product, which is a platform for helping you with narrations for audiobooks, for voiceovers, for ads, or movies, or dabs 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 underlied 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. I'm sure it's fell to up and down different ways. I wanna 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 from Europe. We started as a remote company and are still first remote first, but have hubs around the world with London being the biggest, New York being second biggest, Warsaw with San Francisco, and now Tokyo, and one in Brazil. We are at, dollars 300,000,000 in ARR, which is, roughly fiftyfifty between self serve. So a lot of subscription and creators using our creative platform. And then approaching 50, percent on the enterprise side using our agents platform, at work, and that's on the sales led classic sales led side. And we serve more than 5,000,000 monthly actives on that on that on that creative, side of the work. And then on the enterprise side, we have few thousand customers from Fortune five hundreds to some of …
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