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How to Switch from Otter.ai to Fireflies.ai

Otter.ai and Fireflies.ai look like the same product from the outside — a thing that joins your calls and hands you a transcript. They are not. Otter is fundamentally a note-taking tool built around the live meeting: captions as people speak, a transcript you read afterwards. Fireflies is built around what happens after the call — searchable conversation history, summaries pushed into a CRM, and analytics over how your team actually talks. Almost everyone who switches is switching because they've stopped needing better notes and started needing a searchable record. This guide covers the export you have to do first, the consent problem nobody warns you about, and the cases where the honest answer is to stay on Otter.

Meeting transcription & conversation intelligence⏱ About 2 hours, plus one week of running both in parallel7-step migration

Why people leave Otter.ai

🔎 Search across every conversation, not every transcript

Otter searches within meetings well. Fireflies is built to search across them — 'every time a customer mentioned pricing objections last quarter' is a query it answers, and the reason sales and CS teams end up here. If you find yourself opening five transcripts to reconstruct one thread, that's the signal.

🔗 CRM write-back instead of copy-paste

Fireflies pushes call summaries and notes into HubSpot, Salesforce and Pipedrive against the right record. The value isn't the integration existing; it's that the rep stops deciding whether the call was worth logging. Otter gets the transcript to you, but getting it into the deal record is still a human action.

📊 Topic trackers and talk-time analytics

You can define terms — a competitor name, a pricing objection, a feature request — and get flagged whenever they come up across the team's calls, plus talk-to-listen ratios per person. This is coaching infrastructure, and it's the capability Otter doesn't really try to compete on.

🤖 Automation hooks that fire without a person

An API and Zapier surface means 'when a call mentions churn, post to this Slack channel and create a ticket' is a rule, not a habit you have to maintain. If your process currently depends on someone reading the transcript and remembering to act, that process is the thing you're actually buying.

Stay on Otter.ai if…

A migration you regret costs more than the subscription you were trying to escape. These are the cases where Otter.ai is still the right answer.

•You use Otter for live captions during the meeting — for accessibility, or because you read along while someone talks. Fireflies is a recorder and a post-call product; the real-time reading experience is the single biggest thing you'd lose and it does not have an equivalent.
•You're a solo user who wants a transcript of your own calls. Almost everything Fireflies charges extra for is team infrastructure — cross-meeting search, coaching analytics, CRM routing. One person with a transcript need is what Otter is priced for.
•Your organisation restricts meeting bots. Fireflies joins as a visible participant, which some legal and IT teams simply prohibit, and some clients react badly to. Check the policy before you migrate, not after a customer asks who 'Fireflies Notetaker' is.
•You're on a legacy Otter plan, an education plan, or a lifetime deal. You'd be trading a price you can't buy back for a recurring bill — only worth it if the CRM and analytics side is genuinely load-bearing for you.

What you gain and what you give up

Capability	Otter.ai	Fireflies.ai
Live in-meeting captions	Core strength — read along in real time	Not the product; post-call oriented
Search across all past meetings	Workable but meeting-by-meeting	Built for it — cross-conversation queries
CRM write-back	Export and paste, or light integration	Native push to HubSpot/Salesforce/Pipedrive
Topic / keyword trackers	Not a first-class feature	Define terms, get alerted across the team
Talk-time & coaching analytics	Minimal	Talk-to-listen ratios, per-rep views
Joins as a visible bot	Can capture without a separate participant	Bot appears in the participant list
Shareable clips / highlights	Highlights within a transcript	Soundbites — clipped, shareable moments
Solo-user value for the price	Hard to beat	You pay for team features you won't use
Automation / API surface	Limited	API plus Zapier, rules can run unattended

Green marks the stronger side of each row. Rows where both are comparable are left neutral.

The migration, step by step

Decide which question you're trying to answer

15 minutes

Write down the specific thing you cannot currently do. 'Find every call where a customer asked for SSO.' 'Stop reps forgetting to log calls.' 'See who talks 80% of a discovery call.' If your list is really just 'get a better transcript', Fireflies will not feel like an upgrade and you should stop here — the transcription quality difference between these two is not what justifies a migration.

Export your Otter archive before you touch anything else

40 minutes

This is the step people skip and regret. Export your conversations from Otter in bulk — DOCX or PDF for readability, plus SRT or TXT if you ever want to reprocess them. Your transcripts do not migrate into Fireflies' searchable index, so the archive you export here is the only copy of your pre-switch history that survives. Do it while the subscription is live: once the plan lapses, access to the archive goes with it.

Clear the meeting-bot question with legal and with your team

20 minutes

Fireflies joins calls as a named participant. That is a visible change for everyone you meet with, and in regulated industries or two-party-consent jurisdictions it's a compliance question, not a preference. Get an answer on internal policy, decide your disclosure language, and agree which meeting types the bot is allowed into — one-to-ones and interviews are the usual carve-outs. Doing this before rollout avoids the migration dying on its first customer complaint.

Connect the calendar and set auto-join rules per meeting type

20 minutes

Connect your work calendar and then immediately narrow the auto-join rules. The default of 'record everything' is how teams end up with a library full of internal standups that dilute every search you run afterwards. Record external calls and named internal reviews; leave standups and one-to-ones out. A smaller, deliberate corpus is what makes cross-meeting search useful rather than noisy.

Rebuild vocabulary and set up topic trackers

25 minutes

Custom vocabulary does not transfer. Re-enter your product names, people names and internal acronyms — this is the single biggest lever on perceived transcription accuracy, and skipping it is why a new tool often 'seems worse' than the one you left. While you're in there, define the four or five topic trackers that map to the questions you wrote down in step 1.

Wire the CRM and verify one real deal end to end

30 minutes

Connect HubSpot, Salesforce or Pipedrive, then run one actual customer call and confirm the summary lands on the correct record — not just that the integration reports success. Field mapping is where this quietly breaks: notes attached to a contact instead of a deal are invisible to the person who needed them. One verified end-to-end call is worth more than any amount of configuration you haven't tested.

Run both for one week, then cancel

1 week of elapsed time

Keep Otter live for a week of overlap so you can compare on identical meetings and still have a fallback if the bot fails to join something important. At the end of the week, confirm your export from step 2 is readable, then cancel. If anyone on the team relied on Otter's live captions, resolve that before you pull it — that's the loss that generates complaints.

What does not come across

Every migration loses something. Budget for these before you cancel Otter.ai, not after.

✗Your Otter transcript archive as a searchable asset. Exports give you files; they do not repopulate Fireflies' index, so cross-meeting search only covers calls recorded after the switch.
✗Live captions during the meeting. This has no equivalent on the other side and is the most common reason a switch gets reversed.
✗Custom vocabulary, speaker labels and folder structure — all rebuilt manually.
✗Any links to Otter transcripts already pasted into Notion pages, tickets and email threads. They keep pointing at an account you're about to close.
✗The option of recording without a visible bot in the participant list.

Otter.ai → Fireflies.ai: common questions

Can I import my Otter.ai transcripts into Fireflies.ai?

Not in a way that makes them searchable. You can export transcripts from Otter as DOCX, PDF, TXT or SRT and keep them as an archive, but they do not load into Fireflies' cross-meeting index. Practically, this means your searchable history restarts on migration day — which is the strongest argument for switching sooner rather than after another six months of accumulating calls.

Does Fireflies.ai join meetings as a visible participant?

Yes. It appears in the participant list as a notetaker bot, and everyone on the call can see it. That is a feature for consent and a problem for policy — some IT and legal teams prohibit third-party bots outright, and some customers will ask about it. Confirm your internal policy and your disclosure wording before you roll it out to client-facing calls.

Is transcription accuracy better on Fireflies or Otter?

Close enough that it should not drive your decision. Both are strong on clear English audio and both degrade on crosstalk, heavy accents and bad microphones. The variable you actually control is custom vocabulary — a tool that knows your product and people names will read as dramatically more accurate than one that doesn't, regardless of which vendor it is.

Should I switch if I'm the only person using it?

Usually not. The things Fireflies does better are team things: cross-conversation search, CRM routing, coaching analytics, automation rules. A single user who wants a reliable transcript of their own calls is exactly who Otter is built and priced for, and you'd be paying for infrastructure you have no one to share with.

What happens to my Otter data when I cancel?

Access to your conversations goes away with the plan, so treat the export as mandatory and do it before you cancel, not after. Export in a readable format (DOCX or PDF) plus a machine-readable one (TXT or SRT) if there's any chance you'll want to reprocess or search that history later.