When Sam Liang founded Otter.ai in 2016, AI was not yet a household word. Over the years, however, the field of writing and taking notes has evolved alongside enabling technology. Today, its built-in chat information engine helps users make sense of their business and personal lives by drawing on their database of meeting recordings. Liang envisions a future where typing—even on a chatbot—is largely obsolete.
“When people use chatbots like ChatGPT or Claude, one of the biggest problems is context,” Liang told the Observer. “It takes a lot of effort to write good information and give all the context, but when you bring AI into the conversation, it has all the context.”
Used by 86 percent of Fortune 500 companies, Otter surpassed $100 million in annual recurring revenue last year. Company $73 million in revenue in business financing in its first five years and surpassed 35 million users late last year. It combines external integrations—such as Google Workspace and Anthropic’s Claude—with internal innovations such as agent chat, which can pull in data and complete tasks. Even large banks with strict compliance requirements are in discussions with Otter about incorporating the technology into their operations, Liang said..
Otter has been able to compete with Big Tech firms like Microsoft and Google. While the note-taking features of Microsoft Teams and Gemini’s Google Workspace benefit from native ecosystems, Otter differentiates itself by working across platforms, including Zoom, Google Meet, Microsoft Teams, and in-person meetings through its mobile app.
Whether college students are trying to understand speeches, employers are analyzing candidates, or CEOs are reviewing missed meetings, AI alone is not enough to solve productivity challenges, Liang said. Instead, he argues that access to full contextual data from past meetings allows agents to perform tasks more effectively.
The Observer spoke with Liang about the state of AI in voice communication, competing with tech giants, and why personal meeting avatars are Otter’s next frontier.
The following discussion is edited for length and clarity.
Otter began primarily as a writer and note taker. When did it become clear that you needed to shift to understanding and conducting conversation? And how did you approach that change in a way that was different from the ways we see in major technology competitors?
This has been our vision since day one, but it has taken us several years to get the transcripts and meeting notes working properly. With large language models and new agent technologies, it makes the information engine possible.
There is another aspect of why we are developing so fast in the information engine now. A change in attitude. It is a desire to look for AI solutions to change the way people work. We are still in the first innings, but it is starting to change.
Business or personal, it seems to require that mindset shift to take full advantage of AI I actually have a smart fridge at home, so I no longer have to manually add anything to my shopping list, but it took me a while to get used to it. Now, as you grow through this evolution you’ve described, how do you measure success against giants like Microsoft and Google, who admittedly have a broader vision, but whose ambitions increasingly overlap with yours?
When you’re building something new, you’re always faced with huge technological competition. Google, Zoom, Microsoft, their biggest advantage is their distribution channel. They have access to companies already, so it’s easy for them to put something together, even for free.
But this may be their biggest problem. Because it’s so easy for them to put things together, they don’t really have a strong incentive to build the best product. Microsoft is not known for creating innovative new products. They are known to copy others. For us, in terms of the conversational information engine, I don’t see them working on that right now.
My prediction is that they don’t care about what we do until we hit $1 billion in revenue. Microsoft copied Slack, but didn’t do it until it was already big. Salesforce acquired Slack when it was introduced $27.7 billionso we still have many years before Microsoft really pays attention.
He said that AI benefits from as much context as possible. For business and personal use, some context is more critical. How do you balance the productivity benefits of voice data and privacy inside and outside the walls of the organization?
There is a common security model already. At Google, Microsoft and Notion, you can control who has access to any content. We built a similar structure in Otter. You can create private Otter channels, but some content may be public to anyone in the company.
Many businesses have information silos, which limit people. Sales teams don’t really know what sales teams or products do, and vice versa. If you share more information between teams, you can speed up the workflow.
From the same lens, the question of authenticity becomes increasingly important. Video AI, for example, faces many questions about authenticity. Aside from the obvious problems with deepfakes, do you see that concern coming from AI-enabled voice technology, or does it take a different form?
I believe that voice communication is actually very authentic, especially when you meet someone in person. However, if it’s written by AI, it doesn’t mean it’s not true. It can still come from people’s opinions that are true.
Voice communication is more likely to be authentic because you are speaking your mind in real time. In the future, we can create an avatar that can talk like you, but hopefully the avatar uses your own brain to talk, so it’s still very authentic.
Do you have plans to tackle a personal meeting photo in the future?
Yes, we plan to do that, but there are still many challenges to make it work really well. We have created an avatar. A Bloomberg a reporter chat with my avatar in a live event. It went well, and finally, I see avatars of busy professionals to represent them in other meetings.
And with that, what are you hearing from your users and industry peers about the risks associated with that type of technology? How do they think about it?
Of course, one danger is fraud. There have already been some cases of people using a relative to scam people into sending money, so that’s the best way to spot that and warn people. There are risks with any new technology.
Looking to the future, what do you think is the next frontier for voice communication in concert with AI, and how do you see Otter shaping up, especially around big tech and these AI giants?
I think most businesses will use a chat information engine. You place all meetings in this system and use it to drive both human and agent workflows, making businesses more productive. There’s always competition from Big Tech, but I’m sure we can innovate quickly.
