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

Podcast: Equity

Published: 2025-12-10

Duration: 24 min

Summary

Mati Staniszewski, CEO of Eleven Labs, discusses the company's rapid growth and future direction, emphasizing that voice technology will soon be commoditized. Eleven Labs is shifting focus towards developing dynamic conversational agents to enhance human-technology interaction.

What Happened

In this episode of Equity, host Rebecca Balan interviews Mati Staniszewski, the co-founder and CEO of Eleven Labs, a company that has emerged as a leader in AI voice technology with a valuation of $6.6 billion. Staniszewski reflects on the company's origins, which stemmed from two Polish engineers frustrated with poor movie dubbing. He explains how Eleven Labs has expanded its offerings to include not just realistic AI voices but also a creative platform that combines audio with dynamic information systems, addressing how humans interact with technology.

A significant revelation from Staniszewski is his belief that voice models will soon be commoditized, suggesting a shift in the industry landscape. He highlights that while Eleven Labs initially focused on building proprietary voice models, the future lies in enhancing conversational agents that can integrate and interact with existing systems like Google and Salesforce. The conversation dives into the complexities of deploying these agents, particularly in sectors like healthcare, where automation can significantly improve patient interactions.

Staniszewski also discusses the competitive landscape, acknowledging overlaps with companies like OpenAI and Adobe. However, he emphasizes Eleven Labs' unique position due to its focus on audio and the intricate application processes that accompany it. He foresees that while the audio model architecture will remain critical in the coming years, the uniqueness of Eleven Labs will lie in how effectively they can deploy these models in real-world applications, especially as the market evolves.

Key Insights

• The commoditization of voice models is expected within a few years, prompting Eleven Labs to pivot its focus.
• Eleven Labs aims to enhance human-technology interaction through dynamic conversational agents rather than just voice technology.
• The company’s unique selling point is its ability to build its own models and integrate them into complex applications.
• Healthcare applications demonstrate the potential of AI to automate and improve user interactions significantly.

Key Questions Answered

What is Eleven Labs' current focus?

Mati Staniszewski outlines that Eleven Labs' primary goal is to enhance how humans interact with technology. The company aims to solve various problems by integrating audio technology into dynamic systems, allowing for more natural interactions between devices and users.

How does Eleven Labs differentiate itself in the AI space?

The uniqueness of Eleven Labs lies in its ability to build proprietary models, unlike many competitors who opt to partner for model creation. Staniszewski emphasizes that the application side of deploying conversational agents is complex, and Eleven Labs is focused on solving these intricate challenges.

What challenges does Eleven Labs face with commoditization?

While Staniszewski acknowledges that voice models will commoditize over the next few years, he believes it is crucial to develop robust applications in the interim. The challenge will be to maintain a competitive edge by enhancing the model architecture and integrating advanced features into their offerings.

What role does AI play in healthcare according to Staniszewski?

Staniszewski shares a case study of Hippocratic, a healthcare company working with Eleven Labs to automate appointment scheduling through voice agents. This showcases how AI can streamline patient interactions and improve the efficiency of healthcare services.

How does Eleven Labs plan to adapt to future trends in AI?

Looking ahead, Staniszewski emphasizes the need for continuous innovation and adaptation, suggesting that while voice models may become ubiquitous, the focus will shift to integrating more sophisticated features and capabilities within conversational agents.