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35M Users. $100M ARR. My 10-Year Bet Was Right. | Otter.ai, Sam Liang

EO08:09Added Aug 31, 2026

"Shakespeare never left a voice note. That's the problem Sam Liang has spent 10 years solving."Sam Liang, Co-founder and CEO of Otter.ai, started in 2016 whe...

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Contributed by 刘嘉琪

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Transcript format

  1. Intro

  2. 00:00I was at Harvard University just two days ago and a lot of professors actually don't allow students to use a
  3. 00:07tool like Otter to help them learn. I think that's that's old thinking. The way we do education, the system was
  4. 00:14created at least 100 years ago. They have to allow the students to use whatever AI tools. Although human beings
  5. 00:22have been talking with each other for hundreds, thousands of years, most of the voice knowledge in the history has
  6. 00:29been lost. We never heard from Shakespeare. We never heard from Charles Darvin. That's tremendous loss of human
  7. 00:37knowledge and human intelligence. With those frustration and insight, we thought that in the voice AI will be
  8. 00:45really huge in the future. I'm Sam. I'm co-founder and CEO of a about AI. We started as a a transcription tool, then
  9. 00:54evolve it into a AI meeting assistant and now we're building a meeting centric
  10. 01:02enterprise knowledge base with Agentica workflows on top of it. So far we have over 35 million users. We exceeded $100
  11. 01:11million in ARR. Now enterprises are adopting it to manage their huge meeting content.

  12. The Bet Nobody Believed In

  13. 01:24I did my PhD at Stanford University and I learned a lot from my PhD advisor. His name is David Sherton. He has the vision
  14. 01:33about what will generate a big impact, what will change the world. That's why he actually recognized the talent of
  15. 01:41Larry Page and Sergey when he wrote a $100,000 check to them before they had anything. I learned a lot from him in
  16. 01:49terms of thinking big. I was at Google 2006 to 2010. I was the lead of Google map location platform. Then I quit
  17. 01:58Google in 2010 to start a mobile startup in Palo Alto. We were the first that
  18. 02:05build a location tracking system and also do persistent sensing on mobile devices that understand users mobile
  19. 02:14behaviors so that we can personalize the more mobile services for them. That company was successfully acquired. Then
  20. 02:22in 2016 I was thinking about something new and something bigger. While I was building the first startup, I had a lot
  21. 02:30of meetings with investors, a lot of meetings with our internal team and customers. Really hard for me to
  22. 02:37remember all the meeting content. It's also hard to share that knowledge with all the team members. So, I think there must be a better way to address that.
  23. 02:49Back in 2016, we say we're going to record everything. We're going to enable it to be shared with other team members.
  24. 02:57Both made most people uncomfortable.
  25. 03:01Number one, being recorded is uncomfortable and also share meeting notes with other people. It's uncommon because traditionally people take notes
  26. 03:10on the paper notebook. It's a personal thing. We anticipate that the mindset will change, the culture will change. So
  27. 03:18we build the product that enable that change. You can convince some people.
  28. 03:24You cannot convince everyone. That's okay. You know for any new product it it follows certain adoption curve. For
  29. 03:31people who adopted a product like auto early, they actually get value and benefit sooner. They can become uh more
  30. 03:38effective, more productive and they can show the value to their colleague. You know they can help convince the other
  31. 03:45users as well. So you have to pick something that most people haven't haven't been convinced yet.

  32. Why He Refused to Use Third-Party APIs

  33. 03:56If you want to really go big, you need to have deep technology roots. I came from technology background. I like
  34. 04:04technologies. I like engineering. I also see that a lot of revolutionary companies are built on deep technologies
  35. 04:12like Google. Today there are a lot of APIs you can use to quickly build a meeting note taker. Any college students
  36. 04:21can do that already in 2016 10 years ago. At that time if we were waiting for someone else to create the API you know
  37. 04:29we we would be many years late when we decided to build our own speech recognition technology. We didn't know how long it would take. We know there
  38. 04:38there is a lot of risks. We know that we have a lot less resource, a lot less money, a lot less people than Google or
  39. 04:47Microsoft. What if Google or Microsoft or other people catch up fast? Our choice is to build deep technologies
  40. 04:56which can enable us to create a new revolution in the future. What differentiation can you create? That's the biggest problem for a new startup.
  41. 05:06From day one, we always had that belief that that should be the way that should be the right way because we're we own
  42. 05:13our own technology. So we can keep the cost low. If you use a third party API, you have to pay them a lot of money that
  43. 05:21limit how much free service you can provide. There are still deep problems that require uh AI scientists to work
  44. 05:29on. For example, you know, when we have hundreds of millions of voice data, how do we use that to truly model human
  45. 05:38conversation, how do we model the interactions of multiple speakers talking to each other in the meeting?
  46. 05:44That's still a unsolved problem. To solve that problem, you cannot just rely on third party APIs. You have to build
  47. 05:52your own deep AI tag. If it's too easy for you to build, it's very easy for 100 other people to build as well.

  48. The Next Interface Isn't a Screen

  49. 06:01Behavior always change when you have new technologies. If you look back in the last 50 years, right before internet
  50. 06:10became so common, it feels like we have been having emails forever. But then a new tool like Slack became popular. Then
  51. 06:18people actually send fewer email. They rely on Slack. But then you know with when the voice technology become much
  52. 06:25more mature. We think that voice will become the primary interface for enterprise intelligence. You probably
  53. 06:34don't need to write so much in a few years. People will rarely write anything. They will rarely use keyboard
  54. 06:42to write anything. They can just talk because talk is easier than writing.
  55. 06:46They can just talk and our AI will write everything for you. It's it's start to happen. A lot of people actually use AI
  56. 06:54to write documents, to write emails, to write linking post. It's already happening. It will only accelerate. So
  57. 07:01our view is that voice is becoming the primary interface of business intelligence. Looking forward to the
  58. 07:09next many years, there's still a long way to go. At least 95% or even higher.
  59. 07:14I would say 90 99% of the world hasn't adopted a tool like Otter yet. We have to look at the next 10 years not just
  60. 07:22today. That's how you know this generational companies are built.
  61. 07:28People say building a startup like running a marathon. Actually building a startup is way harder than running a marathon. I've run 11 marathons. I'm going to run another one in 2 months.
  62. 07:39That definitely helped me stay healthy, handle stress, help me push through all the challenges. Most people give up
  63. 07:46pretty fast. If you're building something challenging, the difficulties are as expected. You have to persist and
  64. 07:55and continue pursuing your goal.