Otter.ai is pushing beyond transcription to become a platform embedded in enterprise workflows. Its newly announced enterprise suite introduces APIs, agentic AI to shuttle data between transcripts and CRMs or project tools, and a unified repository for organizational conversations. That shift places it in more direct competition with Microsoft, Google, and specialized rivals like Fireflies. But the move comes amid friction: a recently filed class action lawsuit alleges Otter secretly records conversations without full consent and uses them to train its models. The company’s enterprise ambitions may depend on how well it manages legal, privacy, and trust risks while scaling.
Otter began as a transcription tool integrated with Teams, Zoom, and Google Meet. On October 7, 2025, it unveiled a cross-platform enterprise suite designed to extract intelligence from unstructured voice data and assemble a “central repository for conversations” so insights don’t stay siloed. “Without a central repository for conversations, valuable insights go untapped,” the company argues. Sam Liang, co-founder and CEO, told Computerworld, “What started as a consumer app has become an enterprise tool… we wanted to ensure we were building not just a great individual AI tool, but a serious enterprise player.” Liang added that Otter now has “over 25 million global users”.
In a conversation with ITPro, Liang described the bidirectional flow of data: “The data can automatically be put into Otter… or flow out of Otter to whatever system enterprise customers use.” New features include a Model Context Protocol (MCP) server that lets Otter collaborate with external AI models like Claude or ChatGPT. Its agentic AI can extract action items, schedule follow-ups, screenshot slides, and help users “chat” with transcripts in real time. The company also claims HIPAA compliance and offers admins granular controls over meeting permissions and data sharing.
When stacked against Microsoft or Google, Otter faces structural disadvantages. Microsoft (via Teams + Copilot) and Google (via Meet + AI integrations) already control identity, document, calendar, authentication, compliance, and security layers inside most large organizations. Those bundled advantages are difficult for a standalone player to replicate. Enterprise buyers often prefer solutions already embedded in their stack rather than adding third-party layers with new integration and compliance risks. Analysts note that embedding meeting data into workflows requires robust authentication, authorization, data handling, and governance.
Still, Otter has distinct advantages. Its focus on meeting intelligence could yield deeper contextual awareness, better conversational memory, and domain-specific nuance. Its neutrality, spanning Teams, Zoom, and Meet, offers flexibility in mixed enterprise environments. And by automating downstream workflows such as CRM updates and project follow-ups, Otter aims to become more than just a transcription service.
Competition remains fierce. Fireflies, a leading rival, already offers meeting summaries, CRM integrations, conversational queries, topic trackers, and collaboration tools. It supports more languages and is often praised for integration breadth and accuracy. Some reviewers describe Otter as stronger in cross-meeting insight and conversational continuity, while Fireflies leads in post-meeting analytics and automation.
None of this will matter, however, if enterprises distrust Otter’s data practices. In August 2025, a class action lawsuit was filed in U.S. District Court for the Northern District of California by plaintiff Justin Brewer, alleging that Otter’s “Otter Notetaker” and “OtterPilot” bots recorded private conversations on Zoom, Google Meet, and Microsoft Teams without notifying or obtaining consent from all participants. The suit further claims that Otter uses those recordings to train its models, violating federal statutes like the Electronic Communications Privacy Act and California’s privacy laws.
The complaint argues that Otter records utterances from participants who don’t have Otter accounts, such as guests, without their consent. Some coverage describes the alleged recordings as “deceptive” or “surreptitious,” and the suit claims Otter’s disclosures on training data may be inadequate.
Legal observers see the case as a warning for all AI meeting platforms. It could prompt new norms around multi-party consent, opt-out defaults, and tighter controls on model training data. Otter faces reputational risk, regulatory scrutiny, and potential court-imposed limits on how it operates within enterprises.
Otter’s Terms of Service place consent obligations on users, stating that “you are solely responsible for providing any notices to, and obtaining consent from, individuals in connection with any recordings.” While that stance may hold legally in some jurisdictions, courts could deem it insufficient, especially when meetings include guest participants.
Otter’s enterprise strategy will depend as much on trust as on technology. The market for meeting intelligence is real, yet enterprises must believe Otter can enforce access controls, audit AI behavior, and protect sensitive information. The class action casts an early shadow on whether Otter can expand its enterprise ambitions while navigating tightening legal and privacy norms.
