Otter vs Fireflies vs Fathom: Which AI Notetaker Holds Up

Pick Fathom if you want the most usable free plan and clean, structured summaries. Pick Fireflies if the meeting archive needs to be searchable and sync into a CRM. Pick Otter if you want a live transcript people can watch and annotate while the meeting is happening. And if the bot joining your calls is the thing you hate, Granola is the wildcard — it takes notes without ever appearing in the participant list.

Those are the four real answers. What follows is why, and — more usefully — the three failure modes that no vendor page mentions.

The thing every comparison skips: how the audio gets in

Almost every difference between these tools traces back to one architectural decision, and it isn't the AI. It's capture.

Bot-based capture (Otter, Fireflies, Fathom) means a participant called something like "Fathom Notetaker" joins your Zoom, Meet, or Teams call. It receives the same clean, per-speaker audio streams the meeting platform sends everyone else. That gives you excellent speaker separation, it works whether or not you personally attend, and it works on any device — the bot doesn't care that you dialled in from your phone.

The cost is social. A bot in the participant list changes the room. Candidates get stiffer. Prospects notice. Some organisations' IT policies block unknown bots outright, and some clients will simply ask you to remove it.

Bot-free capture (Granola, and the local-recording modes some tools offer) runs on your machine and listens to system audio and your microphone. Nothing joins the call. Nobody sees anything. It works on in-person meetings too, which the bots cannot do at all.

The cost is that you become a single point of failure. If you're not in the meeting, there's no recording. If your laptop sleeps, there's no recording. And speaker separation is harder, because the tool is hearing a mixed-down stream rather than clean per-participant channels — it's inferring who spoke from one audio blob.

Everything else — summary quality, CRM sync, pricing — is downstream of this choice. Decide it first.

Otter

The oldest name here, and it shows in both directions. Otter's live transcript view is still the best of the group: text appears as people speak, you can highlight and comment in real time, and other attendees can follow along. For lectures, interviews, and accessibility use cases, that live-collaboration angle is genuinely differentiated.

The summaries are competent rather than sharp. Otter has been layering AI features — chat over your meetings, automated action items — onto a product that was fundamentally built as a transcription engine, and it reads that way. Where newer tools start from "what should this meeting produce," Otter starts from "here is what was said."

Who should use it: students, journalists, researchers, and anyone who wants a shared live transcript during the call rather than a tidy summary after it. Also anyone who transcribes uploaded audio files as often as they transcribe meetings.

Who should not: sales teams. The CRM story is weaker than Fireflies', and the summary format is less deal-shaped.

The honest trade-off: best-in-class at the thing it was originally for; second-tier at the thing everyone now wants.

Fireflies

Fireflies is the one that treats your meetings as a database rather than as events. It records, transcribes, summarises — and then the actual product is what happens next: search across every call you've ever had, topic trackers that flag when a keyword like "pricing" or "competitor" comes up, and integrations that push notes and fields into Salesforce, HubSpot, and the rest.

That's a meaningfully different pitch. If your problem is "I can't remember what that client said in March," Fireflies is the answer and the others aren't really trying.

Who should use it: revenue teams, agencies with lots of client calls, and anyone whose pain is retrieval rather than note-taking. If you work in sales, pair it with the rest of the stack on our sales teams use-case page, and browse AI CRM tools for what it plugs into.

Who should not: solo users who just want a summary in their inbox. You'll be paying for an archive you never search.

The honest trade-off: the integration surface is the reason to buy it and the reason it feels heavier than Fathom. More setup, more admin, more to configure before it earns its keep.

Fathom

Fathom's free plan is the most aggressive in the category — it's the reason the tool spread by word of mouth. Recording and transcription are free in a way the others don't match, with the AI summary features rationed rather than the recording itself. The summaries are also the best-structured of the group: clearly sectioned, with action items that generally survive contact with reality.

The strategy is obvious enough — give the individual rep the tool for free, let it spread inside the org, then sell the team plan with CRM sync and shared libraries. That's fine. It just means the free plan you fell in love with is the on-ramp, and the features you'll eventually need are on the other side of it. Verify current limits before you build a process on the free tier, because this is the number vendors adjust most often.

Who should use it: individuals and small teams who want the least friction and the best summary-per-dollar. It's the default recommendation for most people reading this.

Who should not: organisations with strict controls on third-party bots, or anyone who needs deep CRM automation on day one.

The honest trade-off: you are the beachhead in a land-and-expand motion. Not a scam — just be clear-eyed that the generosity has a purpose.

Granola — the bot-free wildcard

Granola sits in a different category. It runs on your machine, captures system audio, and merges the transcript with the notes you type during the call. The output is a hybrid: your shorthand, expanded and corrected against what was actually said. No bot joins. Nobody knows it's there.

That last part is the whole story, and it cuts both ways. The upside is enormous for anyone doing sensitive conversations — investor calls, one-to-ones, hiring conversations, client work where a visible recording bot changes what people are willing to say. The downside is that the silence is yours to break. A bot announces itself. Granola doesn't. You are now the disclosure mechanism.

Who should use it: founders, consultants, managers, anyone taking notes in meetings where a bot would be unwelcome — and anyone who takes in-person meetings, where a bot simply cannot go.

Who should not: teams that need coverage of meetings the note-taker didn't attend, or anyone who needs reliable per-speaker attribution across a large call. Also worth checking platform support before you commit — this class of tool has typically been desktop-first, and often Mac-first.

The honest trade-off: you trade robustness and coverage for invisibility.

The comparison

Limits move constantly in this category. Treat the table as the shape of each product, not as a price list, and check the current plan before you commit a team to it.

Transcription quality: the part nobody benchmarks honestly

All four are built on strong modern speech recognition, and on a clean call — good mics, one person talking, native-accent English — you will struggle to tell them apart. The differences appear exactly where meetings actually get hard:

• Crosstalk. Two people talking over each other is where transcripts degrade fastest. Bot-based tools have a structural advantage here because the meeting platform hands them separated per-participant streams; a tool listening to mixed system audio has to untangle overlapping voices from one waveform.
• Accents. Recognition quality is uneven across accents. This is a property of the underlying speech models, not of any one product's marketing, and it is the single most common complaint from distributed teams. Test with your actual team, not with a demo call.
• Jargon and proper nouns. Product names, drug names, ticker symbols, unusual surnames. Tools that let you upload a custom vocabulary or keyword list will do noticeably better here — check whether that feature is on the plan you're buying.
• Bad audio. A participant on a laptop mic in a hard-surfaced room will wreck any of them. The fix is a headset, not a subscription.

If you want to know which one handles your meetings, record the same real call with two of them running and read both transcripts. That takes one meeting and tells you more than any comparison article, including this one.

The compliance part you should not skip

Recording law varies. Some jurisdictions require only one party to consent; others require everyone on the call to consent, and "everyone" includes the client who joined late. This is not a technicality — it is the part that generates actual legal exposure, and it is systematically under-covered in listicles about this category.

Practical rules that keep you out of trouble:

1. Announce it, every time. A visible bot is a form of notice, but a name in a participant list is not informed consent. Say it out loud in the first thirty seconds and let people object.
2. Bot-free tools shift the burden to you. If nothing joins the call, nothing tells the room. That's a feature, and it means the disclosure is entirely your responsibility.
3. Check your own policy before your vendor's. Many companies have rules about recording customer calls, storing them with a third party, and how long the transcripts persist. That constraint usually decides the tool for you.
4. Ask where the data lives and how long it stays. Meeting transcripts are among the most sensitive text your company produces — pricing, strategy, personnel. Retention settings matter more than summary quality.
5. For anything genuinely confidential, don't use a cloud notetaker. Run a local transcription model instead; see AI tools that work completely offline for the practical version of that.

How to choose in one pass

• Meetings you don't attend need coverage → bot-based. That rules Granola out immediately.
• In-person meetings matter → Granola. That rules the bots out immediately.
• Notes must land in the CRM without human effort → Fireflies.
• You want the best summary with the least setup and the smallest bill → Fathom.
• People need to read the transcript during the call → Otter.
• The recording itself is the deliverable — a podcast, a course, a video → none of these. You want an editor. Descript transcribes and edits audio and video by editing the text, which is a different job entirely.

Whichever you land on, remember that the notetaker is one piece of a stack — see AI productivity tools for what it should be feeding. Run the winner alongside your current process for two weeks before switching anyone else over. The failure mode in this category isn't bad transcripts — it's a beautiful summary that nobody reads, in a tool nobody opens.

FAQ

Which AI notetaker has the best free plan?

Fathom's, by a clear margin — it treats recording and transcription as the free part and rations the AI features on top, where most competitors do the reverse. Fireflies and Otter both have real free tiers with caps on minutes, AI credits, or storage. Check current limits before you build a workflow on any of them; free-plan ceilings in this category change more often than anything else on the pricing page. For the wider picture on what "free" really means, see our guide to free AI tools with no signup.

Do AI notetakers work without a bot joining the meeting?

Yes. Granola is the best-known bot-free option: it runs on your computer, captures system audio, and never appears as a participant. Some bot-based tools also offer a local-recording mode. The trade-off is coverage and speaker separation — a bot-free tool only works when you're personally in the meeting with the app running, and it's inferring speakers from a mixed audio stream rather than receiving separate channels.

Is Fathom better than Otter?

For most people in 2026, yes — Fathom produces better-structured summaries and asks for less money to do it. Otter still wins in one specific scenario: when you want a live transcript that participants can read, highlight, and comment on while the meeting is running. If that's your use case, Fathom isn't a replacement.

Is it legal to record a meeting with an AI notetaker?

It depends on where every participant is sitting, not just where you are. Some jurisdictions require consent from all parties; others require only one. Announcing the recording at the start of the call and giving people a chance to object is the practical baseline, and your employer's own policy on recording and storing customer conversations may be stricter than the law. Bot-free tools make disclosure entirely your responsibility, because nothing on the call announces itself.

Can an AI notetaker replace taking notes myself?

For recall, yes. For thinking, no. The transcript captures what was said; it does not capture what you concluded, what you decided not to say, or what you noticed. The tools that work best — Granola's model of merging your typed notes with the transcript is the clearest example — assume you're still paying attention, and use the recording to fill in what your hand couldn't keep up with.

Where to go next

Browse the full field in AI meeting tools, or go one layer down into AI transcription tools if the recording matters more than the summary. Our roundup of the best AI meeting notetakers covers the rest of the category, and AI note-taking tools is where these sit next to the tools that organise what you keep. Using something that beats all four? Submit it — this is a fast-moving category and the leaderboard is not settled.