The Twenty Minute VC (20VC) | September 8, 2025

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

Guest: Mati Staniszewski, Co-founder and CEO, ElevenLabs

Host: Harry Stebbings

Episode Overview

This episode features Mati Staniszewski, co-founder of ElevenLabs, reflecting on the meteoric rise of his AI voice startup, which recently surpassed $200 million in annual recurring revenue (ARR), making it one of Europe’s fastest-growing AI companies. Mati discusses the origins of ElevenLabs, the challenges of building world-class AI infrastructure in Europe, talent wars, fundraising stories, and why US VCs play in a different league. The show also covers the evolving role of AI foundation models, product-market fit, European tech culture, and Mati’s philosophy on team and company culture.

Key Themes and Discussion Points

1. Origins and Early Motivation (04:20–08:30)

• Growing up in Poland: Mati credits the unique advantages and limitations of his upbringing in suburban Warsaw for shaping his ambition and perspective on global scale.
  • “The density of talent was the most motivating factor… that’s what’s most motivating, being part of this incredible set of people.” [05:29 – Mati]
• Partnering with co-founder Piotr: Met in high school, stayed connected through hack projects.
• Origin of ElevenLabs: Inspired by terrible movie dubbing practices in Poland and Poland’s “audiobook” approach to film translation.
  • “All movies are still dubbed… narrated with one single character… a terrible experience and something that we knew needed to change.” [07:03 – Mati]

2. From Idea to First Product (08:30–12:51)

• Initial attempts focused on movie dubbing; feedback from YouTubers was lukewarm.
• Pivoted to text-to-speech after noting unmet demand for flexible, emotion-rich narration and voiceover tools among creators.
  • “They want to post-produce… voiceover over a movie. A super simple problem which didn’t include anything with language changing.” [09:23 – Mati]
• Built proprietary models after finding existing ones inadequate.
• Reflections on the rapid evolution of AI architectures and multimodal models.

3. Product Development, Plateauing, and Differentiation (11:59–15:55)

• Voice AI is not plateauing: While some AI fields are slowing, Mati argues voice AI still has a steep adoption curve.
  • “In narration, we think it’s plateauing… but if you just do research, eventually it will commoditize…” [12:22 – Mati]
• Why OpenAI (and others) can’t just do it: Focus, talent density, and product-oriented execution are critical.
  • “The true longer answer is… focus. We want to really own and win in the voice AI research and product space.” [14:13 – Mati]
  • “Exceptional voice researchers: probably like 50 to 100 people at this top level globally. Piotr was able to assemble one of the best teams in the space.” [14:36 – Mati]

4. Fundraising Stories and Advice for Founders (17:17–26:53)

• Pre-seed fundraising was hard: Spoke to 30–50 investors, facing skepticism about market size and defensibility.
  • “Pre-seed was tough… the market is very small for what you are solving… surprised to even be asked.” [17:35 – Mati]
• Raised $2M at a $9M post-money valuation (2022).
• Beta Launch and Product-Market Fit:
  • Pivot to narration resulted in positive user feedback (e.g., a user producing a full audiobook with ElevenLabs).
  • “It started getting reviews that it’s great… I was like, okay, we are onto something.” [21:00 – Mati]
• Smart fundraising: Announced rounds only when tied to product or research milestones.
  • “Our philosophy was always the round should have another purpose… every round that we would do would always tie into product announcement.” [20:18 – Mati]

Fundraising Tactics and Roadshows

• Reluctance to overvalue traditional PR; grassroots/user-focused channels perform better (Discord, Reddit, newsletters).
• On investor engagement: Use between-rounds periods to test helpfulness, not just chat.
  • “It’s also a good litmus test… see if they genuinely are interested in being there or if it’s just platitudes.” [26:53 – Harry]

Angel Selection

• Advisors and angels chosen for domain expertise, validation in new circles, or go-to-market savvy.

5. The Transformative $19M and $350M+ Funding Rounds (27:52–37:05)

• US VCs (a16z, Nat Friedman & Daniel Gross) led the next stage—Nat Friedman personally tested ElevenLabs’ APIs before investing.
  • “He was the only person that tested our APIs, decided it was actually valuable, gave me feedback…” [29:14 – Mati]
• Andreessen Horowitz founder involvement: proactive, introduced ElevenLabs to celebrities for voice licensing before investing.
• Differentiation between US and European VCs: US funds more risk-tolerant, networked, and supportive in tough times.
  • “They are all more keen to take the risk. Conversations are always like, how do we bet bigger rather than optimize for negatives.” [36:29 – Mati]
• Importance of reference checks on investors (especially how they behave in tough times).

6. Team Building, Small Teams, and Culture (37:13–48:57)

• Emphasis on “small, mighty” teams: 250 employees organized into ~20 autonomous teams.
  • “More people frequently doesn’t fix the problem… you don’t need that many people to do something special.” [37:33 – Mati]
• Teams organized by product area.
• Culture Challenges: The fallout when a partner launched ElevenLabs’ dubbing before they did; open communication is key to recovery.
  • “I don’t think the first reaction should be, hey, everything is fine. You should be authentic…” [41:39 – Mati]
• Hiring: Still interviews every hire at 250+ headcount. Fast decision-making is better than drawn-out “wait and see.”
• Titles: Eschewed traditional titles to keep teams nimble and empower up-and-comers.
  • “The main thing that matters is the impact. …Titles felt limiting to that.” [47:08 – Mati]
• European Talent: Values growing talent internally, paired with US advisors as needed.

7. Scaling, Revenue, and Run Rate (54:00–55:32)

• $200M in ARR:
  • “So we crossed 200 million now… We did 20 months to 100 and then around 10 months to 200.” [54:40 & 55:02 – Mati]
  • “Our biggest contract is around 2 million.” [55:46 – Mati]
• Largest customers are enterprise, often in customer support/call centers and creative verticals.
• Aiming for rapid doubling of headcount (from 250 to 400).
• Cautious about revenue per head, but sees staffing as an investment in distribution.

8. The Economics and Infrastructure of AI (43:26–46:11)

• Built proprietary data centers—found it more cost-effective than “core weave” or generic cloud.
  • “If we assume we continue training the models… on a two-year horizon break even for having our own and not renting. …It pays dividends because we can just do more experiments quicker.” [43:38 – Mati]
• On AI application unit economics: Early margins are bad but expected to improve.
  • “The unit economics in most of those cases… is pretty poor. But I think the strategy is that… the models will optimize in cost… they’ll be the brands that customers trust.” [44:42 – Mati]
  • “Our unit economics is much healthier than most of those companies.” [45:08 – Mati]

9. AI Adoption, Agents, and the Future of Work (58:50–61:14)

• Agents will be a huge line of business: Customer support, omnichannel solutions, and deeper AI integration are immense growth opportunities.
  • “Our agents’ work is already huge. But it’s just scratching the surface… a multi-billion dollar revenue generating business.” [58:50 – Mati]
• Automated agents increasingly replacing rote tasks, but humans remain critical for specialized expertise.

10. On Acquisition Offers, Secondary, and Founder Brand (62:06–69:37)

• Acquisition offers: Evaluated for diligence but “flat no” in ambition.
• Employee liquidity: Offers 10-day secondary windows for vested employees at nearly every round.
  • “We do almost every round we can… so they all feel that there’s actually liquidity.” [63:28 – Mati]
• Founder brand: Some ambivalence, but recognizes it can elevate the company, not just distract.
  • “I sometimes worry… too much of the founder brand kind of takes away from that. But my mind is changing.” [69:33 – Mati]

Notable Quotes & Memorable Moments

• “We crossed $200 million now. So we did 20 months to 100 and then around 10 months to 200.”
  — Mati [54:40]
• “It truly was… all movies are dubbed… a terrible experience and something we knew needed to change.”
  — Mati, on inspiration for ElevenLabs [07:03]
• “Pre-seed was tough. We spoke with a good amount of investors between 30 to 50, and it was double hard…”
  — Mati [17:35]
• “He was the only person that tested our APIs, decided it was actually valuable… gave me feedback… then told me, I’m keen to invest.”
  — Mati, on Nat Friedman [29:14]
• “The number of researchers in the world working on voice and being exceptional is super small. Probably like 50 to 100 people at this top level.”
  — Mati [14:36]
• “Speed of execution is the only, only thing you have.”
  — Mati [31:37]
• “More people frequently doesn’t fix the problem. You don’t need that many people to do something special.”
  — Mati [37:33]
• “Our agents’ work is already huge, but it’s just scratching the surface.”
  — Mati [58:50]
• “I don’t think the first reaction should be, hey everything is fine… you should be authentic and tell the team what you are feeling.”
  — Mati [41:39]

Important Timestamps

• [04:20–08:30] — Early life, motivation, origins of ElevenLabs
• [08:43–12:51] — From idea to pivot; creator feedback and text-to-speech innovation
• [15:55–16:47] — Talent retention and “war for talent”
• [17:17–26:53] — Pre-seed fundraising stories and advice
• [29:14–37:05] — Why US VCs are different, securing Andreessen/Sequoia/Nat Friedman investment
• [37:13–48:57] — Organizing small, agile teams; company culture moments
• [54:00–55:32] — ARR milestones: $35M to $200M, contract sizes, growth timeline
• [58:50–59:31] — Voice agents and the future of enterprise AI revenue
• [62:06–63:28] — Acquisition interest and the importance of secondary for employees

Final Thoughts

This episode gives a rare, candid look at the journey of one of Europe’s most successful AI companies, with detailed discussion on product pivots, the real-world difficulties of fundraising, talent, culture, and the nuances that set apart Europe’s best from their US counterparts. Mati’s approach emphasizes focus, authenticity, and the principle that speed—and the right small team—trumps bloat and bureaucracy. For founders and operators, it’s a masterclass in the scrappy, ambitious new wave of global AI entrepreneurship.

[Summary by 20VC AI Podcast Summarizer]