Episode summary
The Trillion-Dollar Industries AI Is Disrupting: Voice, Law & the End of the Billable Hour
All-In Podcast
· · Hosts: David Sacks, Jason Calacanis, Chamath Palihapitiya, David Friedberg
Summary
ElevenLabs said its revenue reached $600 million ARR after a rapid product ramp from a 2023 launch, and it now has about 600 employees. The guest argued that the company’s edge comes from combining research and product, embedding engineers across nontechnical teams, and using voice AI across the full customer journey, from marketing and support to sales and operations.
A major theme was how voice interfaces are changing behavior. The guest said users are becoming more comfortable interrupting AI, speaking in short bursts, and giving richer prompts because the software responds faster and more precisely than humans. The episode also covered the company’s safeguards around identity and impersonation, including tracing generated content, moderating voice and text, and blocking commercial abuse or scams.
The second half shifted to legal AI. Another guest said legal services are a roughly $1 trillion market, but only about $40 billion is software, leaving most work manual. He argued that AI is compressing billable-hour workflows, speeding diligence and contract review, and pushing firms toward fixed-fee or success-fee pricing. He also said Legora is building localized legal data and narrow models for specific tasks rather than a general legal intelligence model.
Key takeaways
- ElevenLabs said it hit $600 million ARR in about 40 months, with growth from $100 million to $300 million ARR accelerating sharply before reaching $600 million.
- The guest said ElevenLabs runs with about 600 employees and no PMs, using small cross-functional teams with engineers embedded even in legal and talent functions.
- The guest said voice AI is shifting from reactive call handling toward proactive, personalized interfaces that can pull from past interactions and reduce friction for customers and enterprises.
- The legal-AI guest said the market is still about 96% services and 4% software, which creates a large opening for automation in contracts, diligence, and legal research.
- The legal-AI guest said Legora completed one acquisition in 12 days from LOI to closing using its own tool, showing how AI can compress transaction cycles.
- The legal-AI guest said narrow models beat general legal models for tasks like tabular review, where cost and latency matter more than broad intelligence.
Notable quotes
“Then it took us roughly 20 months to get to the first 100 million in ARR. Roughly 10 months to get to 200, 5 months to get to 300”
“so we are seeing that kind of phenomena all the time where actually using a lot of tooling makes you yourself better in your job overall”
“We don't we don't have any PMs”
“the way to think about the market or at least the way that we like to is you have this enormous bucket of legal services which today is being done manually”
“But the software spend into legal technology is about 40 billion. So it means there's 4% software 96% service which is bananas”
How the episode opens
You're on a bit of a heater, huh? — It's It's the best time to be building — And revenue has surged, but you face really intense competition. Let's go right at that to start. — If you were building a global financial system from First Principles today, you wouldn't build it on 50-year-old legacy rails. You'd build Airwalks, one AI native platform for global accounts, cards, and payments. is designed to make the entire world feel like a local market. Others are bolting AI onto broken infrastructure, but Airwall was built for the intelligent era from day one. Stop paying the legacy tax and start building the future at airwalls.com/allin. Airwalls built for the future.
350 million in what 2 or 3 years and I'm hearing numbers five or 600 million now. Tell us about the revenue ramp of the company from the moment you released the software to today. the the product's been in market for 40 months, 50 months, you tell me.
Spot on. We started company 2022. First year was all about building the the research and the product to really kickstart the work.
We built the first texttospech model that finally could sound human. Released it in 2023, beginning of 2023. Then it took us roughly 20 months to get to the first 100 million in ARR.
Roughly 10 months to get to 200, 5 months to get to 300. Um and um and that's how we closed end of the last year and now we are at 600.
You're at $600 million in revenue. This is just extraordinary. Um how many employees now? Because the company's obviously hit incredible valuations, but you have to fill in that valuation and you you're competing at a very high level for talent. So, so tell us about how many employees you have now and how you maintain the culture of the company when revenue is ripping, investors are throwing money at you, showing up at your doorstep.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- voice ai
- deepfake impersonation
- legal tech and data moats
- ai model competition
- billable hour disruption
Companies and tickers mentioned
- RELX
- ElevenLabs
- OpenAI
- Anthropic
- Legora
- LexisNexis
Watch the episode
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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