Otter is launching enterprise search across third-party apps, acting as a Model Context Protocol client that can pull data from Gmail, Google Drive, Notion, Jira and Salesforce into its meeting workspace. The notetaker now reports 35 million users, up from 25 million last year, when the company also disclosed $100 million in annual recurring revenue. The move puts Otter in direct competition with Read AI, Fireflies.ai and Fathom, all chasing the same pivot from transcription tool to enterprise productivity layer.
Users can query meeting transcripts alongside outside data inside a single interface, then push outputs back into those tools — drafting a Gmail message or sending a meeting summary to Notion. Microsoft Outlook, Teams, SharePoint and Slack integrations are coming next, Otter said, which would close the gap for customers standardized on the Microsoft stack.
The MCP bet is a notable reversal of a step Otter took last October, when it launched a way for organizations to build custom MCPs that surfaced Otter data inside other tools. That earlier release pushed Otter's data outward. This one pulls outside data in, turning the app into a search and reasoning surface rather than a passive recorder.
Key facts
- 01Otter launched enterprise search as an MCP client connecting Gmail, Google Drive, Notion, Jira and Salesforce.
- 02The platform now has 35 million users, up from 25 million reported last year alongside $100 million in ARR.
- 03Microsoft Outlook, Teams, SharePoint and Slack integrations are coming next, the company said.
- 04Otter brought botless meeting capture to Mac late last year and is now launching a Windows app with the same feature.
- 05Otter built custom MCP support last October to push its data outward; this update reverses the flow.
Otter has also redesigned its AI assistant to sit consistently across the interface, with awareness of the screen context — a specific meeting, a channel — so users can ask questions without re-establishing the topic. That design choice borrows from how Granola and others have framed the assistant as ambient rather than modal.
“Otter's user base climbed to 35 million from 25 million the prior year, when the company also reported $100 million in annual recurring revenue.”— Jaeden Schafer
On the capture side, the company is following the industry shift toward botless recording. Otter brought system-audio capture to its Mac app late last year and is now launching a Windows app with the same capability. The approach records meetings via the device rather than dispatching a bot to join the call.
CEO Sam Liang said enterprise buyers actually prefer the bot. "When we talk to enterprise customers, most of them actually prefer the note taker that joins the Zoom meeting because it provides the transparency. They also prefer the meeting notes to be shared with all the meeting attendees, so that the note is not limited to one person," Liang told TechCrunch. To handle the obvious failure mode — multiple bots from multiple attendees crowding the same call — Otter built a deduplication feature that prevents a swarm of bots from joining simultaneously.
The strategic question is whether notetakers can credibly become workspaces. The category started as a thin wrapper over speech-to-text, and pricing power eroded as transcription quality converged. Adding MCP connectors lets Otter argue it sits at the intersection of meetings and the rest of a knowledge worker's stack — the same pitch Notion, Slack and Salesforce itself are making from their own starting points.
Otter's scale gives it a real shot. Going from 25 million to 35 million users in roughly a year is the kind of growth that makes enterprise procurement teams take a meeting, especially when paired with $100 million in ARR as a 2025 baseline. The company has not provided updated revenue figures alongside the new user count.
The risks are real. MCP is a rapidly adopted standard, but the connectors only matter if the underlying queries return useful answers across messy enterprise data — calendar invites, half-finished Notion pages, stale Salesforce records. If Otter's assistant hallucinates across that surface, the trust deficit will be larger than it was when the product only summarized a call. Competitors with deeper search heritage, including Microsoft inside its own suite, can credibly argue they already do this.
Otter's pivot reflects where the meeting-AI category has to go to survive. Transcription is a feature, not a business, and the companies treating it as a wedge into broader enterprise workflow are the ones likely to justify the valuations they raised on. Whether Otter's 35 million users translate into seats that pay enterprise prices for search and agentic actions is the next number to watch.
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