Otter.ai in brief
| What it is | Live meeting transcription with summaries, action items and a searchable archive |
| Distinguishing feature | Transcription appears in real time, not after processing |
| OtterPilot | Joins calendar meetings on your behalf and records without you present |
| Platforms | Zoom, Google Meet, Microsoft Teams, plus direct and uploaded audio |
| Metering | Transcription minutes, not seats — plus a cap on minutes per single conversation |
| Free tier | Yes, permanent, with a monthly minute allowance |
| Vocabulary | Custom word list for names, jargon and product terms |
| Poor fit for | CRM-driven sales teams, heavily accented multi-speaker calls, confidential legal discussion |
What determines whether the transcript is usable
The four things that wreck accuracy
Crosstalk. Two people speaking at once is the single largest source of error, and it is why a boardroom on one microphone transcribes far worse than five people on five headsets.
Accents and dialects. Accuracy is noticeably stronger on North American English than on other varieties. This is a real and frequently under-reported limitation for international teams.
Domain vocabulary. Product names, drug names, technical terms and acronyms are transcribed as the nearest common word unless you tell it otherwise.
Microphone quality. A laptop’s built-in microphone in a hard-surfaced room degrades everything downstream. No processing recovers what was never captured.
The fix most people never apply
The custom vocabulary list takes ten minutes to populate and fixes the same twenty errors every single meeting — colleagues’ names, your product names, your industry’s acronyms. It is the highest-return configuration step in the product and it sits unused in most accounts.
Getting reliable transcripts from week one
| 1. Populate the vocabulary list | Team names, product names, recurring acronyms, client names. Ten minutes here removes the majority of recurring errors. |
| 2. Announce recording before you enable it | OtterPilot joining a call unannounced is how tools like this get banned internally. Say it in the invite, not at minute forty. |
| 3. Ask remote attendees to use headsets | Individual microphones eliminate crosstalk confusion — the biggest single accuracy improvement available. |
| 4. Assign speakers once | Naming speakers early trains recognition for later meetings, and turns the archive from a wall of text into something attributable. |
| 5. Correct the first few transcripts | Corrections improve subsequent recognition and cost a few minutes on a meeting you are reviewing anyway. |
| 6. Watch the per-conversation cap | Plans limit both monthly minutes and the length of a single conversation. A three-hour workshop can be truncated mid-session on lower tiers. |
Otter, Fireflies and tl;dv compared
| What decides it | Otter | Fireflies |
|---|---|---|
| Built around | The live transcript | The CRM record |
| Strongest for | Students, general business | Sales and revenue teams |
| Live transcription | Yes — its main advantage | Post-meeting focus |
| CRM write-back | Limited | Central to the product |
| Metering | Minutes | Seats plus storage |
| Choose when | You need the text as it happens | Calls must reach HubSpot or Salesforce |
tl;dv is the third option and competes almost entirely on price — its free tier is the most generous of the three, and it puts clips and highlights ahead of transcript search. Granola rejects the whole model: no bot joins the call at all.
The consent question every recording tool raises
This applies to all four tools in this cluster and it is not a formality.
- Recording law varies by jurisdiction. Some require all parties to consent, some only one. A call spanning several countries is governed by more than one rule.
- A bot joining is not consent. The visible participant tells people something is recording; it does not establish that they agreed.
- Announce it in the invitation. Then anyone uncomfortable can raise it before the conversation starts rather than after.
- Some conversations should not be recorded at all — HR matters, disciplinary discussions, legal advice, anything under privilege.
Teams that adopt these tools without a stated policy tend to acquire one after an incident. Writing the policy first is considerably cheaper.
Where Otter falls short
- Summaries are serviceable, not sharp — they capture topics well and decisions less reliably.
- Action-item extraction misses implied ownership, the most common way a task gets lost.
- Accuracy varies materially by accent, which limits it for global teams.
- Minute allowances are consumed quickly by anyone in back-to-back meetings.
- Shallow CRM integration compared with the sales-oriented alternatives.
Who Otter serves best
Students and researchers recording lectures and interviews, where live transcript and a permanent free tier matter more than integrations. General business teams wanting meeting records without a sales apparatus. Journalists and anyone conducting interviews who needs to search what was said during the conversation.
Not the right choice for sales organisations whose calls must land in a CRM, for teams working mostly in strongly accented or multilingual English, or for confidential discussions that should not be recorded at all.
Other meeting tools
- Fireflies.ai — CRM-first, built for revenue teams.
- tl;dv — the strongest free tier, clip-oriented.
- Granola — enhances your own notes, no bot in the meeting.
- Descript — when the recording is content to be edited and published.
Compiled from Otter.ai’s documentation and public sources. We have not hands-on tested this tool. Last reviewed 17 August 2026.
