Founder’s Lessons: Sam Liang, CEO of Otter.ai
Sam shares his journey and insights on speech recognition and NLP technologies and his experience as a technical founder.
About
Welcome to the twentieth installment of Tsingyuan Ventures’ Lessons from Founders series. Every week, we publish an in-depth founder interview, ranging from early-stage entrepreneurs to successful businesses. Our conversations cover their personal journeys, the lessons that shaped them, their visions for the future, and their failures. We also learn more about their companies and about the challenges they try to solve. These insights and lessons are applicable to any entrepreneur — current or future.
Read past interviews here.
You can also view full transcripts by Otter.ai from our interview with Sam here.
About Otter.ai
Otter.ai provides automatic meeting notes for virtual meetings, remote work, and in-person meetings, to improve collaboration, communication, and productivity. Otter created its proprietary speech recognition and NLP technologies and has processed tens of millions of meetings and served millions of users. The market has recognized Otter’s value. Otter has been extensively covered by the media and won several awards. Recently, Otter raised a $50m series B round and is actively hiring.
Dr. Sam Liang is the founder and CEO of Otter.ai. Before founding Otter, Sam worked at Google where he led the location-based services unit and won an award for the “Bluedot Mobile Location System.” Sam earned his BS degree from Peking University, and received a Ph.D. at Stanford for Internet Distributed Systems, working under Professor David Cheriton who is known for being the first investor in Google.
Why we invested in Otter.ai: Sam Liang is a prototypical “Tsingyuan entrepreneur”: he’s deeply technical, and has been successful as both a serial entrepreneur and as a top-tier software engineer (at Google). He has built a team with a combination of top-notch engineering talent and strong start-up execution capabilities. Tsingyuan’s investment in Otter not only reflects our optimism about the practical value of Otter in daily work, but also about the huge potential of Otter in for smart meetings and enterprise digitalization. In addition to being fans of Otter as investors, Otter’s automated meeting transcripts are core to how we work at Tsingyuan — virtually every meeting we have is transcribed and fully searchable. We believe that it is the future of knowledge storage and retrieval.
Key takeaways
Interview edited for clarity and length.
“Our strategy is to have both the core AI technology, and the best product user experience.”
Why did you found Otter?
When you build a startup, you’re going to think about what problem you are trying to solve. The problem we’re looking at was meetings. Everybody in enterprises knows there are just so many meetings you need to have every day. There’s tons of information being exchanged. How do you make sure everyone gets the notes and stays synchronized? And also, there are a lot of meetings that may not be necessary, and there are always people who cannot join the meetings. So we develop Otter to help people collaborate and communicate better.
There’s a lot of questions about why do we do it now. There are many reasons. Number one is there is big market demand, obviously as described, and now it’s more clear to people. On top of that, we see that this is the future of work in terms of remote collaboration blend of synchronous communication with asynchronous communication.
We see that this is the future of work in terms of remote collaboration blend of synchronous communication with asynchronous communication.
Why did Otter choose to develop its own speech recognition engine?
Speech recognition is not a solved problem yet. Alexa, Google Assistant or Siri already do this but those systems cannot process meeting conversations very well. This is a huge market and there are a lot of interesting things to do.
This is a question we have been asked all the time — did you guys use Google API, Microsoft, or Amazon? No, we build our own engine and you can test it against Google, Microsoft, side by side, you will see that Otter provides much better accuracy and higher performance.
Otter created its proprietary speech recognition and NLP technologies first out of necessity, as there were no good tools available at that time. However, owning its own speech recognition engine has given Otter a significant advantage across multiple dimensions:
- Cost: Using a third-party API can be very expensive.
- Data sharing: You don’t need to send data to Google or other API providers, which is a concern of many enterprises customers
- Control over tech stack: You have no limitation on what you want to do (i.e. Otter can do customer vocabulary, add special terms and names, which are not allowed by third-party APIs)
We build our own engine and you can test it against Google, Microsoft, side by side, you will see that Otter provides much better accuracy and higher performance.
Otter is your second start-up; what feels different this time ‘round?
Otter is my second start-up. A lot of things are different as we learned a lot from the first time in terms of understanding the market, the business side, customer segmentation, team building, resource allocation, and building a good social network. I met his co-founder in the first start-up. After the first startup was acquired, we were thinking about something new. And we came up with this idea and said hey let’s do something even crazier than the first startup — think about all the voice information in the world, how can we capture it, how can we organize it, how can we make it available to everybody. It’s a very audacious plan. When we started, we didn’t have any speech recognition system. Nobody else is able to do it well, so let’s build it ourselves.
A lot of things are different as we learned a lot from the first time in terms of understanding the market, the business side, customer segmentation, team building, resource allocation and building a good social network.
Where is Otter headed?
Otter has seen rapid growth in the last four months, and even before COVID, it was already growing pretty well. I believe that Otter is going to stay strong after the pandemic, as the value is getting stronger and stronger and more visible to people for hybrid meetings, international companies, knowledge sharing, and team collaboration.
Otter is focused on product and end-user experience and wants to create a new collaboration platform on top of it. At this moment, that’s not our priority to open an API service to other companies at this stage.
There are a lot of important work to do in the future vision of Otter
- Good accuracy: it’s never good enough
- Solutions for noise in the back, low voice quality, unstable wifi, and accents
- Contextual intelligence: how to fill in the blank based on the other words
- Post-transcript value-add (e.g. meeting summaries and action items, still an unsolved problem, but is in Otter’s future roadmap)
- Language and translation: currently Otter is English only, but other languages and translations are on the future roadmap.
I believe that Otter is going to stay strong after the pandemic, as the value is getting stronger and stronger and more visible to people for hybrid meetings, international companies, knowledge sharing, and team collaboration.
Horizontal vs. vertical approach
Gong is a great company. As you mentioned, it is a great use case for salespeople. But we decided to take a very different approach. We like to target meetings in general and see the potential market size is huge. They go deeper into the sales vertical but we cover a lot more types of meetings, such as project meetings, interviews, webinars, virtual events, online courses, etc. We see our user base is way bigger. It’s a very different strategy.
How does it feel dancing with elephants regarding partnerships with Zoom and Google?
You have to compete. You just have to assume that people want to crush it. That’s just a reality and we accept that. We need to get comfortable with being uncomfortable. There will always be competitors. You just have to move faster than all of them and be smarter on both the core technology and the product offering. Our strategy is to have both the core AI technology, and the best product user experience. Another thing is that we have a good mobile experience as well — you can get all your meeting notes on your iPhone or Android on the go.
You just have to move faster than all of them and be smarter on both the core technology and the product offering.
How do you make trade offs and make decisions on product features?
We built this service for two reasons. One is that we see that we have the need ourselves. And regarding the product, my thesis at Stanford was on distributed systems. I’m fascinated by any good user experience and user interface myself.
We eat our own dog food in our own company, and we use the product every day. So we get to feel the pain if anything doesn’t work. We discover any bugs we see in the workflow that doesn’t work. I guess this is one advantage. When you have a founder or CEO who is just so obsessive with a product, that’s a good combination.
When you have a founder or CEO who is just so obsessive with a product, that’s a good combination.
How does Otter deal with privacy and data security, and how do you convince customers to give you their trust?
Otter does have a very strict privacy policy. Everything is encrypted and data is all fully owned by the user. Voice is very sensitive information, but essentially it’s not so much different than your email, document, Slack messages, which are essentially the same. There is a common practice in terms of encrypting information.
You have to be very mindful, very rigorous on security and privacy. To convince others from a data privacy and security perspective, you need to get some early adopters, demonstrating that your technology and quality are good. The endorsement from early customers helps a lot (for example, Zoom and TechCrunch are two strong supporters fro Otter in the early days).
Otter is hiring!
The team is very diverse and fun. We just received $50 million funding, and we’re looking for more people to join us — engineers, back end, front end, AI scientists and engineers, and sales and marketing people. If you’re interested in AI, interested in the new collaboration product, check out our career page and reach out to us!
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Tsingyuan Ventures is a $150M seed-stage technology firm. We back technical founders across software, life sciences, and frontier technologies. Learn more about our origin story and our approach here.
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