Otter.ai

What it does

Otter.ai is an AI meeting-notes service that records, transcribes, and summarizes voice conversations. Its core job is to join your video calls automatically, produce a live transcript with speaker labels, and turn that transcript into a summary with extracted action items afterward. The product centers on the OtterPilot meeting assistant, which connects to your calendar, sends a bot into scheduled Zoom, Google Meet, and Microsoft Teams calls, and writes notes you can search later.

Beyond live calls, Otter handles uploaded audio and video files for transcription, and a phone app captures in-person conversations through the device microphone. Newer features add a chat layer (Otter AI Chat) that answers questions about a meeting or generates follow-up drafts from the transcript, and a channels view that aggregates notes across recurring meetings.

Who it's best for

The clearest fit is anyone sitting in five or more recurring video meetings a week where decisions and follow-ups happen verbally and someone needs a record afterward. In practice that means sales teams that want call notes synced to a CRM, product and project managers running standing syncs, consultants who bill against documented conversations, and academic or journalist users transcribing interviews and lectures.

It also suits accessibility use cases. Live captions during a call help hard-of-hearing participants and non-native speakers follow along in real time, and the running transcript lets someone who joined late catch up without interrupting.

Where it's strong

Live transcription. Captions stream during the call rather than appearing only afterward. This is genuinely useful for accessibility, for catching a number or name you missed, and for letting people who could not attend read along live.

Cross-platform meeting capture. OtterPilot joins Zoom, Google Meet, and Teams automatically once it has calendar access, so you do not have to remember to start a recording. It is one of the few tools that reliably covers all three major platforms plus file uploads and in-person mobile capture in a single subscription.

Speaker identification. Otter attributes lines to specific people and improves as you tag voices over time. Many cheaper transcription tools either skip diarization or guess poorly; Otter's is among the more usable, which matters when you need to know who committed to what.

Search and reuse. Every meeting becomes a searchable, timestamped document. Finding the moment a price or deadline was discussed across months of calls is the feature people keep it for, more than the summaries themselves.

Where it's weak

Summary quality. The auto-generated summaries and action items are functional but generic, and they miss nuance or invent tidiness that was not in the conversation. Fathom and several newer meeting-AI tools produce sharper summaries and cleaner action-item extraction. A common workaround is to let Otter capture the transcript and then run it through Claude or ChatGPT for a better summary.

Accuracy on hard audio. Like all automatic speech recognition, accuracy drops with heavy accents, crosstalk, technical jargon, and poor microphones. Expect to correct names, acronyms, and domain terms. For high-stakes transcripts you still need a human pass.

Bot presence and consent. OtterPilot joins as a visible participant, which some external attendees dislike, and recording calls raises consent obligations that vary by region. Otter has also drawn scrutiny in the past for emailing transcripts to people in your contacts; review sharing defaults before turning it loose on client calls.

Privacy on lower tiers. Free-tier usage can be used to improve Otter's models. Paid tiers offer stronger data-handling commitments, but if your meetings cover sensitive material, read the current data and retention policy rather than assuming the defaults protect you.

Pricing context

Otter offers a free tier with a monthly transcription-minute cap and per-conversation length limits, which is enough to evaluate the product but not to run a real meeting habit. Paid plans start around the mid-teens per month (roughly $16 to start at the time of writing; the exact figure changes, so confirm on Otter's pricing page), unlocking meaningfully higher minute allowances and longer recordings. Higher business tiers add admin controls, shared workspaces, usage analytics, and stronger privacy guarantees billed per user. The free tier's main role is trialing accuracy and the meeting-bot flow before committing.

For comparison, Fathom sits at a similar entry price and leans harder into summary quality, which is the main axis on which the two differ.

Integrations and workflow

Otter connects to Google and Microsoft calendars to auto-schedule the bot, and integrates with Slack and common CRMs and collaboration tools so notes and action items land where work already happens. Sales-oriented plans push call data into systems like Salesforce and HubSpot. There is also an API and Zapier-style automation path for routing transcripts into other tools.

The realistic workflow: connect your calendar, let OtterPilot join meetings, skim the live transcript during the call, and after the meeting either accept Otter's summary or feed the raw transcript into a stronger LLM for the version you actually send. Treat the transcript as the reliable artifact and the summary as a draft.

Who should skip it

Skip Otter if your priority is the quality of the post-meeting summary and action items over raw transcription — a purpose-built summarizer will serve you better. Skip it for sensitive legal, medical, or confidential negotiations unless you have vetted its current privacy terms and confirmed recording consent. And skip the bot-in-the-room model entirely if you only need to transcribe occasional uploaded audio; a pay-as-you-go transcription engine or a local Whisper setup is cheaper and avoids the recurring subscription.

Verdict

Otter.ai is a solid, established choice for workplace transcription with broad platform coverage, dependable speaker labels, and a searchable archive that pays off over months of meetings. Its weak spot is summary quality, where Fathom and newer entrants have pulled ahead. The pragmatic setup for many teams is to use Otter for accurate, cross-platform capture and search, then hand the transcript to Claude or ChatGPT when the summary needs to be genuinely good. Trial the free tier first to check accuracy on your own audio before paying.