Otter.ai
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Otter.ai is an American artificial intelligence company that builds AI meeting assistants that automatically record, transcribe, summarize, and answer questions about spoken conversations in real time. Founded in 2016 as AISense by Sam Liang and Yun Fu and headquartered in Mountain View, California, Otter.ai surpassed $100 million in annual recurring revenue (ARR) in March 2025 and reported more than 35 million users and over 1 billion meetings transcribed by the end of 2025.[1][2][3] Its core products are the Otter transcription app, the OtterPilot meeting assistant that auto-joins Zoom, Google Meet, and Microsoft Teams calls, Otter AI Chat, and a 2025 suite of voice-activated AI Meeting Agents. In August 2025 the company also became the subject of a closely watched federal class action, Brewer v. Otter.ai, alleging it records participants without all-party consent under California wiretapping law.[4][5]
Otter.ai uses speech recognition, natural language processing, and deep learning to provide real-time meeting transcription, automated summaries, action item tracking, and AI-powered chat. The platform integrates with major video conferencing services including Zoom, Google Meet, and Microsoft Teams. The company reached its $100M ARR milestone with a team of fewer than 200 employees, equating to more than $500,000 in revenue per employee.[1]
Otter.ai was founded in 2016 under the name AISense by Sam Liang (CEO) and Yun Fu (CTO).[6] Both founders brought deep expertise in artificial intelligence and machine learning to the venture.
Sam Liang holds a PhD in electrical engineering from Stanford University, where he studied under David Cheriton, a computer science professor widely known as one of the earliest investors in Google. After completing his doctorate, Liang spent four years at Google, where he led the Google Maps Location Platform and API team and contributed to the development of Google Maps' "blue dot" location feature now used by billions of people worldwide.[6]
In 2010, Liang founded Alohar Mobile, a pioneering company in mobile location context technology. Alohar was acquired by Alibaba in 2013. It was during his time at Alohar that Liang met Yun Fu, who served as head of infrastructure at the company.[6]
The inspiration for Otter came from Liang's own experience in meetings. As a busy executive, Liang found himself attending 30 to 40 meetings per week and struggling to keep track of everything discussed. He recognized that important decisions, action items, and context were regularly lost because no one could take comprehensive notes while also actively participating in the conversation. To solve this problem, Liang and Fu set out to build an AI system that could accurately capture, transcribe, and organize meeting content automatically.
The founding team leveraged their deep expertise in AI and machine learning to build a proprietary speech recognition engine from the ground up, using deep learning techniques for voice recognition and speaker identification. The first Otter app was released later in 2016.
In September 2016, AISense secured a $3 million seed round led by DFJ DragonFund and Draper Associates to fund development of its core transcription engine. The seed funding allowed the team to refine its deep learning models for voice recognition and expand its engineering staff.
In November 2017, the company raised a $10 million Series A round led by Horizons Ventures, the venture capital fund of Li Ka-shing. This funding supported the company's expansion into enterprise markets and allowed it to improve transcription accuracy and add new features.
The early product focused on providing accurate, automated transcription of spoken conversations. Otter distinguished itself from competitors by offering real-time transcription with speaker identification, meaning the system could distinguish between different speakers in a conversation and label their contributions accordingly.
In January 2018, AISense announced a partnership with Zoom Video Communications to transcribe video meetings after they concluded. This integration marked a pivotal moment for the company, positioning Otter as a meeting-focused tool rather than a general-purpose transcription service. The partnership coincided with the early stages of the remote work trend that would later accelerate dramatically.
The company rebranded from AISense to Otter.ai, adopting a consumer-friendly name that better communicated the product's purpose. The Otter brand, with its playful animal mascot, helped the product stand out in a market that had traditionally been dominated by enterprise-focused transcription services.
By July 2019, Otter had transcribed over 10 million meetings and processed more than 250 million minutes of audio. The product gained traction among journalists, students, researchers, and business professionals who needed reliable transcription without the expense of human transcription services, which typically cost $1 to $3 per minute.
The COVID-19 pandemic triggered an enormous surge in video conferencing usage worldwide, and Otter was well positioned to capitalize on this shift. As millions of workers transitioned to remote work, Zoom, Google Meet, and Microsoft Teams meeting volumes skyrocketed, creating massive demand for automated meeting transcription.
Otter experienced explosive growth during this period, with revenue growing more than 800% in 2020 and a 600% increase in product usage from 2020 to 2022.[7] The platform quickly expanded its integrations beyond Zoom to include Google Meet and Microsoft Teams, ensuring compatibility with all three major video conferencing platforms.
In February 2021, Otter.ai raised a $50 million Series B funding round led by Spectrum Equity, with continued participation from Horizons Ventures, Draper Associates, GGV Capital, and Draper Dragon Fund. The round included a $10 million convertible note component. At the time of this raise, Otter had transcribed more than 100 million meetings spanning 3 billion minutes of audio, and the app was used in more than 175 countries.[7]
The Series B funding was directed toward product development, expanding the engineering team, and building out enterprise features to serve larger organizations with more complex security and compliance requirements.
In February 2023, Otter.ai launched OtterPilot, an AI meeting assistant that represented a significant leap forward in the product's capabilities. OtterPilot could automatically join scheduled Zoom, Google Meet, and Microsoft Teams meetings on behalf of the user, even if the user was not present. The assistant would transcribe the meeting in real time, generate summaries of key discussion topics, capture images of slides shared during the meeting, and produce organized meeting notes that could be shared and collaborated on.
By February 2023, Otter had reached the milestone of 1 billion meetings transcribed. The company continued to enhance OtterPilot throughout the year, adding features like automated action item extraction with assigned owners and deadlines.
According to the company, 62% of OtterPilot users reported saving at least four hours per week on meeting-related tasks, a productivity gain that helped justify the subscription cost for both individual users and enterprise teams.
In February 2024, Otter launched Meeting GenAI, a feature that allowed users to query information across all of their past meeting transcripts. Rather than searching through individual meeting notes, users could ask questions and receive AI-generated responses that drew from the full corpus of their meeting history. This transformed Otter from a single-meeting note-taker into an organizational knowledge base built from conversations.
The AI Chat functionality allowed participants to interact with meeting content in real time. During meetings, attendees could ask the AI questions about what had been discussed, generate new action items, and receive clarifications. After meetings, users could continue querying the transcript, with options for both private and shared AI chat sessions.
By February 2024, Otter had processed over 50 billion minutes of transcribed audio, and the platform had grown to over 14 million registered users.
On March 25, 2025, Otter.ai announced that it had surpassed $100 million in annual recurring revenue and simultaneously launched what it called an industry-first suite of voice-activated AI Meeting Agents, a shift from a passive note-taker to active AI participants in conversations.[1] The launch suite comprised three agents:
| Agent | Role | Function |
|---|---|---|
| Otter Meeting Agent | Voice-activated meeting participant | Answers questions using company meeting data, schedules follow-ups, and drafts emails through natural voice interaction |
| Otter Sales Agent | Live sales co-pilot | Provides real-time coaching and objection-handling guidance to sales reps during customer calls |
| Otter SDR Agent | Autonomous outbound agent | A multimodal agent that conducts live product demos with prospects independently, without human intervention |
Sam Liang, co-founder and CEO, framed the milestone in terms of the broader AI agent shift: "Our $100M ARR milestone validates that businesses are ready to embrace AI agents that augment human intelligence in meaningful ways."[1] The company reached the $100M ARR mark, up from roughly $81 million ARR at the end of 2024, with a team of fewer than 200 employees and more than 25 million users at the time of the announcement.[1]
In December 2025, Otter.ai capped the year by reporting more than 35 million users worldwide while maintaining the $100M ARR run rate, and announced enterprise and developer expansion including a public API, a Model Context Protocol (MCP) server for connecting Otter data to external AI agents, advanced admin controls, and a desktop app. The company also added Japanese to its supported transcription languages during 2025.[2][3]
Otter.ai was recognized on the Forbes 2026 list of America's Best Startup Employers, ranking number 14 overall and number 4 in the technology category.
In August 2025, Otter.ai was hit with a proposed federal class action, Brewer v. Otter.ai, filed in the U.S. District Court for the Northern District of California.[4][5] The lead plaintiff, California resident Justin Brewer, was not an Otter account holder; he alleges his conversations were captured because the Otter Notetaker had joined a meeting he attended. The suit accuses Otter of "deceptively and surreptitiously" recording private conversations and using them to train its speech recognition and machine learning models without consent.[4]
The complaint asserts that Otter's service "joins Zoom, Google Meet, and Microsoft Teams meetings as a participant and transmits conversations to Otter in real time for transcription," "records meeting participants' conversations even if they are not Otter accountholders," and "uses those recordings to train Otter's automatic speech recognition (ASR) and machine learning models."[5] At the center of the case is consent: the complaint alleges Otter seeks permission only from meeting hosts, and sometimes not even them, rather than from all participants. That matters because California is an all-party-consent state, where recording a confidential conversation generally requires the agreement of everyone involved.[5]
The lawsuit pleads a mix of federal and California claims:[5]
| Claim | Statute |
|---|---|
| Wiretapping and electronic interception | Electronic Communications Privacy Act (ECPA) |
| Unauthorized computer access | Computer Fraud and Abuse Act (CFAA) |
| State eavesdropping and recording | California Invasion of Privacy Act (CIPA) |
| State computer fraud | California Comprehensive Computer Data Access and Fraud Act |
| Unfair business practices | California Unfair Competition Law (UCL) |
| Privacy and property torts | Common law intrusion upon seclusion and conversion |
Legal commentators have described the case as part of a broader wave of privacy litigation aimed at AI notetakers, and a test of whether always-on transcription bots can satisfy all-party consent requirements and lawfully reuse captured speech as training data.[5] The matter highlights a compliance question that applies to the entire category of generative AI meeting assistants, not just Otter.
Otter's core capability is live, real-time transcription of spoken conversations. During a meeting, Otter records the audio, converts speech to text as it happens, and displays the live transcript to meeting participants. The system uses advanced speech recognition technology with speaker identification to distinguish between different participants and label their contributions. Users can highlight parts of the transcript during the meeting for later reference.
The transcription engine supports English (US and UK variants), Spanish, French, and, as of 2025, Japanese, with multi-language translation available through AI Chat.[2]
OtterPilot is Otter's automated meeting assistant. Key capabilities include:
| Feature | Description |
|---|---|
| Auto-Join | Automatically joins scheduled Zoom, Google Meet, and Microsoft Teams meetings |
| Real-Time Transcription | Provides live, speaker-identified transcripts during meetings |
| Slide Capture | Automatically captures and stores images of slides shared during presentations |
| Meeting Summaries | Generates AI-powered summaries of key discussion topics after meetings |
| Action Items | Extracts and tracks action items with assigned owners and deadlines |
| Meeting Notes | Produces organized, shareable notes from meeting content |
Otter AI Chat enables users to interact with their meeting data through natural language queries. The feature operates in two modes:
Otter Chat supports both private and shared sessions, allowing individuals to explore meeting content privately or collaborate with teammates in shared chat environments. The number of AI Chat queries varies by plan, from 20 per month on the free tier to unlimited on the Enterprise plan.
Meeting GenAI extends the AI Chat concept across all of a user's meeting history. When a user asks a question, the system searches across all accessible meeting transcripts and generates a comprehensive response that draws from multiple conversations. This feature is particularly valuable for tracking the evolution of projects, decisions, and discussions over time. Meeting GenAI works regardless of the platform on which the original meetings were held.
Launched in March 2025, the AI Meeting Agents are voice-activated AI participants that can actively engage in meetings rather than simply transcribe them. The flagship Otter Meeting Agent can answer questions using company-wide meeting data, schedule follow-ups, and draft emails through natural voice interaction, while the Sales Agent and SDR Agent target sales coaching and autonomous product demos respectively.[1] The feature represents Otter's push into the agentic AI paradigm. In late 2025 Otter added a Model Context Protocol (MCP) server, letting external AI agents securely access Otter meeting data.[3]
Available on the Enterprise plan, Sales Insights analyzes sales call transcripts using established sales methodologies including BANT (Budget, Authority, Need, Timeline) and MEDDIC (Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, Champion). The feature integrates with CRM platforms like Salesforce and HubSpot to automatically sync meeting data and insights.
Otter provides several tools for team collaboration:
| Feature | Description |
|---|---|
| Conversation Pages | Centralized pages for each meeting with transcript, highlights, comments, and reactions |
| Channels | Team-based organization of meeting transcripts for group access |
| Highlights and Comments | Ability to mark and annotate important transcript sections |
| Transcript Editing | Manual editing of transcripts to correct errors or add context |
| Speaker Tagging | Assign and manage speaker identities across meetings |
| Bulk Export | Export transcripts in multiple formats for external use |
| Custom Vocabulary | Add industry-specific or company-specific terms to improve transcription accuracy |
Otter.ai has built a broad integration ecosystem:
| Category | Integrations |
|---|---|
| Video Conferencing | Zoom, Google Meet, Microsoft Teams |
| CRM | Salesforce, HubSpot |
| Productivity | Notion, Asana, Atlassian |
| Communication | Slack |
| Storage | Google Drive |
| Automation | Zapier |
| Calendar | Google Calendar, Microsoft Outlook |
| Developer | Public API, Model Context Protocol (MCP) server |
Otter offers specialized features for educational institutions through its Otter for Education program:
| Feature | Description |
|---|---|
| Real-Time Lecture Transcription | Live captions and notes for in-person and virtual lectures |
| Slide Capture | Automatic capture of lecture slides with contextual notes |
| Group Collaboration | Students can create groups and share transcripts for study sessions |
| Accessibility | Supports students with hearing disabilities or learning difficulties through live captions |
| Summary Generation | Automatic lecture summaries for review and study |
Otter for Education is deployed across dozens of universities and community colleges, serving over 100,000 students for remote learning and academic accessibility purposes. Institutions like UC Berkeley's Disabled Students' Program and Amherst College use Otter to support inclusive teaching.
Otter.ai's technology stack is built on a proprietary speech recognition engine that the founders developed from the ground up, leveraging deep learning architectures for acoustic modeling, language modeling, and speaker diarization.
Otter's speech recognition system processes audio in real time, converting spoken language to text with high accuracy. The system handles multiple speakers, varied accents, and different audio quality levels. It supports transcription in English (US and UK variants), Spanish, French, and Japanese.[2] Building the automatic speech recognition (ASR) stack in-house, rather than relying on third-party APIs, gives Otter tighter control over latency and transcription quality, and it is also the data pipeline at the center of the Brewer lawsuit, which alleges captured recordings are reused to train these ASR models.[5]
The platform uses speaker diarization technology to distinguish between different speakers in a conversation. Over time, the system learns to recognize returning speakers, improving identification accuracy across multiple meetings.
Otter employs natural language processing techniques for several post-transcription features, including topic extraction, summary generation, action item identification, and keyword detection. The Meeting GenAI and AI Chat features use large language models to enable conversational interactions with meeting data.
As of 2026, Otter.ai offers four pricing tiers:
| Plan | Monthly Cost | Annual Cost (per month) | Transcription Limit | AI Chat Queries | Key Features |
|---|---|---|---|---|---|
| Basic (Free) | $0 | $0 | 300 min/month | 20/month | Up to 5 teammates, 30 min per conversation |
| Pro | $16.99/month | $8.33/month | 1,200 min/month | 50/month | Advanced search, custom vocabulary, bulk export |
| Business | $30/user/month | $20/user/month | 6,000 min/month | 200/month | Team workspaces, admin controls, live captions |
| Enterprise | Custom | Custom | Unlimited | Unlimited | SSO, SOC 2 compliance, API access, Sales Insights, dedicated support |
Annual billing provides savings of approximately 50% compared to monthly billing for the Pro plan and 33% for the Business plan. Sales teams are charged higher per-seat prices ($32/month vs. $18/month for general users on some plans) due to CRM integration and Sales Insights features.
Otter.ai has raised a total of approximately $73 million across its disclosed funding rounds:[8]
| Round | Date | Amount | Lead Investor | Key Participants |
|---|---|---|---|---|
| Seed | September 2016 | $3 million | DFJ DragonFund, Draper Associates | Early-stage investors |
| Series A | November 2017 | $10 million | Horizons Ventures | Li Ka-shing's venture fund |
| Series B | February 2021 | $50 million | Spectrum Equity | Horizons Ventures, Draper Associates, GGV Capital, Draper Dragon Fund |
| Convertible Note | Included in Series B | $10 million | Various | Bridge financing as part of Series B |
Notable angel investors include David Cheriton, Sam Liang's doctoral advisor at Stanford and one of the earliest investors in Google, as well as investors associated with early-stage investments in Tesla, DeepMind, and Facebook.
| Milestone | Date | Value |
|---|---|---|
| Meetings Transcribed | July 2019 | 10 million |
| Minutes Processed | July 2019 | 250 million |
| Meetings Transcribed | February 2021 | 100 million |
| Minutes Processed | February 2021 | 3 billion |
| Meetings Transcribed | February 2023 | 1 billion |
| Minutes Processed | February 2024 | 50 billion |
| Registered Users | December 2023 | 14+ million |
| Registered Users | March 2025 | 25+ million |
| Registered Users | December 2025 | 35+ million |
| Annual Revenue | End of 2024 | ~$81 million ARR |
| Annual Revenue | March 2025 | $100+ million ARR |
| Employees | 2025 | Fewer than 200 |
| Revenue per Employee | 2025 | $500,000+ |
| Revenue Growth | 2020 | 800%+ |
| Usage Growth | 2020-2022 | 600% |
Sources for the headline figures: $100M ARR and fewer-than-200-person team (March 2025), and 35M+ users with sustained $100M ARR (December 2025).[1][2]
Otter.ai operates in the rapidly growing AI meeting assistant market, which was valued at $1.8 billion in 2022 and is projected to reach $17.3 billion by 2032, representing a 25.6% compound annual growth rate. The broader AI transcription market is expected to grow from $4.5 billion in 2024 to $19.2 billion by 2034.
| Competitor | Founded | Total Funding | Key Differentiator |
|---|---|---|---|
| Fireflies.ai | 2016 | $19 million | HIPAA-compliant; 100+ language support; strong CRM integrations |
| Fathom | 2020 | $21.8 million | Free AI notetaker; highest-rated on G2 (5 stars) |
| Krisp | 2017 | $13.5 million | Bot-free, on-device processing; AI noise cancellation; 100+ languages |
| Supernormal | 2021 | $12 million | Supports 10+ languages vs. Otter's core set; integrations focus |
| Gong | 2015 | $583 million+ | Sales-focused revenue intelligence platform; $7.3 billion valuation |
| Feature | Otter.ai | Fireflies.ai | Krisp |
|---|---|---|---|
| Real-Time Transcription | Yes (live during meeting) | Yes (15-20 min delay for full processing) | Yes |
| Language Support | English, French, Spanish, Japanese | 100+ languages | 100+ languages |
| Meeting Bot | Yes (OtterPilot joins meetings) | Yes (Fireflies bot joins meetings) | No bot (processes on-device) |
| AI Summaries | Yes | Yes | Yes |
| Action Items | Yes (with owners and deadlines) | Yes | Yes |
| Noise Cancellation | No | No | Yes (core feature) |
| Privacy Model | Cloud-based processing | Cloud-based, HIPAA-compliant | On-device processing |
| Free Plan | 300 min/month | Limited free tier | Limited free tier |
| Pricing (Pro) | $8.33/month (annual) | $10/month (annual) | $8/month (annual) |
Otter also faces growing competition from the video conferencing platforms themselves:
In the specialized healthcare transcription market, Otter faces competition from:
Otter's primary competitive strengths include its real-time transcription accuracy (particularly strong in English), its established user base of 35+ million, the depth of its Meeting GenAI cross-conversation search capabilities, and its generous free tier that drives user acquisition. The company's proprietary speech engine, built from the ground up rather than relying on third-party APIs, gives it greater control over transcription quality and latency.
The most significant risk facing Otter is platform competition. As Zoom, Microsoft, and Google embed AI meeting features directly into their conferencing platforms, the need for a separate meeting transcription tool may diminish for many users. Some organizations, including universities and enterprises, have begun directing users from Otter to native platform AI tools due to data security and vendor consolidation preferences. The 2025 Brewer wiretapping class action adds reputational and compliance risk to that picture, since it questions whether Otter's auto-joining bot can lawfully record and reuse conversations under all-party-consent rules.[4][5] Otter's narrower language support (four languages compared to 100+ for Fireflies and Krisp) also restricts its appeal in global markets.
Otter.ai's customer base includes organizations across multiple sectors:
| Sector | Notable Customers |
|---|---|
| Technology | Amazon, IBM |
| Media | NBC |
| Education | UCLA, UC Berkeley, Amherst College, dozens of universities |
| Enterprise | Fortune 500 companies across industries |
The markets addressable by Otter.ai include:
| Market | Size (2023/2024) | Projected Size | Growth Rate |
|---|---|---|---|
| AI Meeting Assistants | $1.8 billion (2022) | $17.3 billion (2032) | 25.6% CAGR |
| AI Transcription | $4.5 billion (2024) | $19.2 billion (2034) | 15.6% CAGR |
| AI in Education | $3.5 billion (2023) | $55.3 billion (2032) | ~35% CAGR |
| AI in Sales/Marketing | $2.1 billion (2023) | $10 billion (2033) | ~17% CAGR |
| Medical Transcription | $24.7 billion | Growing | 6%+ CAGR |