Most meeting transcription tools still assume everyone in the room speaks one language. Real international teams don’t work that way, and Otter.ai is finally building for that. The company announced a multilingual transcription feature that detects language changes on its own and keeps transcribing, with no settings to toggle.
The example Otter gives is a call that moves from English to Korean to Portuguese, with the transcript following along the whole way. That’s the hard part. Adding a language to a list is easy. Handling code-switching inside a single meeting is what trips up most speech models, and it’s what bilingual teams actually need.
The feature ships alongside Otter’s biggest language expansion yet: 27 new languages, bringing the total to 31 once the rollout finishes. Thirteen are live now:
- Mandarin Chinese, Cantonese, and Korean
- German, Italian, Portuguese, Russian, Dutch, and Polish
- Indonesian, Malay, Turkish, and Vietnamese
The other 14 are coming soon: Swedish, Danish, Finnish, Norwegian, Arabic, Hindi, Thai, Hebrew, Greek, Macedonian, Persian, Czech, Hungarian, and Romanian. Arabic and Hindi are the ones to watch, given how many potential users they cover.
One detail matters for anyone evaluating accuracy. The new languages run on Otter’s own speech models, not a third-party API. The company says it trained them on publicly available datasets and used native-speaking volunteers to review transcripts. That’s a reasonable approach, but it’s also a thin disclosure. Public datasets skew toward major languages and clean audio, and volunteer review isn’t the same as published word-error-rate benchmarks. Expect uneven quality in the smaller languages until independent tests say otherwise.
Why does this matter? Because transcription is no longer a moat. Zoom, Microsoft Teams, and Google Meet all bundle AI notes, and Fireflies, Fathom, and Read.ai compete on price. Language coverage is one of the few places a specialist can still differentiate, especially for companies with teams across Asia, Europe, and the Middle East. Native-feeling multilingual support also makes it harder for a customer to swap Otter for whatever their video platform includes for free.
It also fits a broader push. Following its $320 million raise from General Catalyst, Otter is moving past transcription into workplace AI. Work Mode pulls from meeting history and connected apps to prep users for upcoming calls, surfacing past customer conversations, open action items, teammates’ notes on similar calls, and recent Google Drive files. Live Assist adds real-time coaching, offering suggestions based on what’s been said so far.
An Otter spokesperson told TechCrunch the goal is to help any company build a system of record for decisions made in voice conversations. That’s ambitious language, and it explains the strategy. A transcript is a commodity. A searchable, multilingual record that feeds prep and coaching is stickier.
My read: this is a real improvement, not noise, but the proof is in the accuracy. If mid-meeting language switching works reliably, it solves a genuine pain point that bigger rivals haven’t fully addressed. If it stumbles on accents and mixed-language sentences, it’s a checklist feature. Test it on your own meetings before you commit.
