The AI meeting assistant that hit $100M ARR with under 200 people
HQ: Mountain View, CA, United States | Founded: 2016 | Employees: Under 200 (>$500K revenue per employee) | Stage: Private; $100M+ ARR (March 2025); ~$70M total raised | Website: https://otter.ai
Otter.ai is an AI meeting assistant: it joins your Zoom, Google Meet or Microsoft Teams calls, transcribes them live, generates summaries and action items, and increasingly acts on them — answering questions during the meeting, drafting emails, and updating your CRM. Its archive turns every conversation into searchable company knowledge.
The company was founded in 2016 by Sam Liang and Yun Fu, both Google alumni. Liang — who previously worked on Google Docs and App Engine and co-invented the mobile 'Blue Dot' location system that won a top Google founder award — started Otter after a decade of watching meetings produce information that went nowhere. Fu built the large-scale ML backend. Their edge at the time was real-time speech recognition that worked well enough to replace human note-takers.
Otter grew through education and business users, riding Zoom's explosion through the pandemic, and stayed capital-light: ~$70M raised across four rounds, with the last reported round a Series B in February 2021. In March 2025 it crossed $100M ARR — with fewer than 200 employees, among the best revenue-per-employee ratios in AI — and 35M+ users.
Since then the product has shifted from transcription to agency: the AI Meeting Agent suite adds live Q&A in meetings, automatic action-item follow-through, CRM sync for sales teams, and an AI avatar that can attend meetings on your behalf. Otter positions itself as the company's conversational memory — the layer where everything said in meetings becomes searchable, actionable knowledge.
Otter.ai is the quiet compounder of the voice-AI boom. While competitors raised giant rounds, Otter grew a transcription app into a $100M-ARR business with under 200 people — more than $500K of revenue per employee, achieved profitably on roughly $70M of lifetime funding. The sequence was classic: nail one painful workflow (meeting notes), own it for years, then ride the AI wave your category created.
The founder pedigree explains the technical depth. Sam Liang was at Google through the eras of Google Docs and App Engine (and holds the Blue Dot location patent lineage); Yun Fu built large-scale ML systems. They started Otter in 2016 to fix a problem everyone had and nobody solved: meetings produce information that dies in the room. A decade later the company claims 35M+ users, a billion meetings transcribed, and an estimated $1.5B in time saved.
The 2025-2026 story is the pivot from note-taker to agent. Otter's AI Meeting Agents join calls, answer questions in real time, draft follow-ups, and — in a flourish that made headlines — can appear as an avatar of you when you can't attend. Enterprise expansion (sales teams, recruiters, executives) is the growth engine, with the company pitching itself as the conversational knowledge base of the company: every meeting searchable, every decision retrievable. The risks are the obvious ones — Zoom, Microsoft and Google ship native transcription, and Fireflies is in a knife-fight for the same seats — but Otter's efficiency, brand and decade of training data make it the incumbent to beat in a category it largely defined.
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