Otter.ai adds multilingual transcription that follows mid-meeting language switches

Otter.ai, the AI-powered meeting note-taker, has announced a multilingual transcription feature designed to follow conversations as speakers switch between languages during a single meeting. Alongside it, the company is rolling out support for 27 additional languages, its largest language expansion to date, according to TechCrunch.

Transcription that keeps up when the language changes

The core of the update is automatic language detection. Rather than forcing users to pick a language before a call, Otter detects when the conversation shifts and keeps transcribing without any manual adjustment. TechCrunch's illustration: a meeting could move from English to Korean to Portuguese, with the transcript following along the whole way.

That targets a common pain point for international teams. Meetings that mix languages, a routine pattern for companies spread across regions, tend to defeat tools that assume one language per session, leaving gaps in the record or forcing users to restart with different settings.

27 new languages, 31 in total

Once the rollout is complete, Otter will support 31 languages in total. Thirteen of the new ones are available now: Mandarin Chinese, Korean, German, Italian, Cantonese, Portuguese, Russian, Indonesian, Malay, Dutch, Turkish, Vietnamese, and Polish.

The remaining 14 are listed as coming soon: Swedish, Danish, Finnish, Arabic, Hindi, Thai, Hebrew, Norwegian, Greek, Macedonian, Persian, Czech, Hungarian, and Romanian.

Built on Otter's own speech models

According to TechCrunch, the new languages run on speech models that Otter trained itself. The company said it used publicly available datasets for training and brought in native-speaking volunteers to review transcripts and check accuracy, a step intended to catch errors that raw training data alone would leave behind.

Part of a broader push into workplace AI

The language expansion does not sit in isolation. TechCrunch notes that the announcement follows $320 million in funding from General Catalyst, and that Otter has been steadily moving beyond plain transcription into other workplace AI tools.

Two recent examples stand out. Work Mode draws on meeting history and connected apps to help users prepare for upcoming calls, surfacing information such as previous customer conversations, outstanding action items, notes from teammates' similar calls, and recent Google Drive files. Live Assist listens during a meeting and offers real-time coaching, suggesting responses based on what has already been discussed and what is happening in the moment.

An Otter spokesperson framed the language work in similar terms, telling TechCrunch: "Otter is breaking down language barriers so any company, no matter where they're based, can build a system of record for the decisions for voice AI communication."

Why it matters

Transcription tools have generally treated a meeting as a single-language event, but multilingual teams routinely code-switch mid-conversation. A tool that cannot follow those switches produces an incomplete or unusable record. If the automatic detection works as described, Otter removes a manual workaround for a large class of international users and makes its transcripts viable where they previously were not.

The decision to train its own speech models also matters. In-house models give Otter direct control over quality and language coverage instead of depending on third-party APIs, which can become a shared ceiling for products built on the same underlying engines. And in a crowded AI note-taking market, the combination of language switching, meeting preparation, and live coaching signals Otter's ambition to be a full workplace assistant rather than a passive transcriber, with $320 million in backing behind that effort.