AI meeting assistants promise to free you from note-taking purgatory. But which one actually delivers? Marketing claims of “95-99% accuracy” mean nothing without context. Real-world performance with background noise, accents, and people talking over each other tells a different story.
I tested four leading tools - Otter.ai, Fireflies.ai, Fathom, and tl;dv - on actual work calls over several weeks. Here’s what I found.
The Tools
Otter.ai is the veteran, launched in 2016 and now powering Zoom’s built-in transcription. It’s the most recognized name in the space.
Fireflies.ai focuses on sales workflows with deep CRM integrations. It’s popular with revenue teams who need call data synced to Salesforce or HubSpot.
Fathom disrupted the market by offering genuinely free unlimited transcription for individuals - no time limits, no monthly caps. It feels too good to be true, and there’s a catch.
tl;dv (“Too Long, Didn’t View”) emphasizes clip creation and cross-meeting search. It’s built for teams who need to reference past conversations, not just transcribe them.
Accuracy: The Marketing vs Reality Gap
Every tool claims 90-95% accuracy. In practice, this applies only to optimal conditions: a single native English speaker, professional microphone, quiet environment. Real meetings aren’t that clean.
According to benchmark testing, here’s how Otter.ai and Fireflies perform:
| Tool | Optimal Conditions | Real Meetings | Noisy Environment |
|---|---|---|---|
| Otter.ai | 92-94% | 82-85% | 71-78% |
| Fireflies | 94%+ | 88-92% | 80-85% |
The gap between marketing claims and field performance is significant. While both tools exceed 90% in controlled settings, real meetings typically see accuracy drop 10-15 percentage points.
Fathom and tl;dv don’t appear in standardized benchmarks, but user testing suggests Fathom achieves 85-90% in typical conditions. Both are praised for strong speaker diarization in multi-person calls.
For meetings with non-native English speakers, expect accuracy to drop another 10-15 percentage points. No current AI system achieves parity with human transcribers across diverse accents.
My Testing Results
I used all four tools across 20+ internal and external calls over three weeks. The calls included:
- 1:1 meetings with clear audio
- Team standups with crosstalk
- Client calls with varying connection quality
- Interviews with non-native English speakers
Otter.ai performed best on clear, single-speaker segments but struggled badly with crosstalk. When two people talked simultaneously, it often attributed text to the wrong speaker or dropped content entirely.
Fireflies.ai had the smoothest CRM integration - call summaries appeared in HubSpot within minutes. But I noticed it occasionally “cleaned up” transcripts in ways that changed meaning. A colleague’s “we can’t do that” became “we can do that” in one instance.
Fathom impressed me with its free tier’s generosity but frustrated me with its AI summary limits. Unlimited transcription means nothing if you only get 5 AI-enhanced summaries per month. After that, you’re reading raw transcripts.
tl;dv stood out for its clip and search functionality. Finding “that thing Sarah said about the budget” across 15 past meetings took seconds. But the pricing jumps significantly once you need team features.
Pricing Reality Check
| Tool | Free Tier | Pro | Business |
|---|---|---|---|
| Otter.ai | 300 min/mo | $16.99/mo | $30/user/mo |
| Fireflies | 800 min/mo | $10/seat/mo | $19/seat/mo |
| Fathom | Unlimited (!) | $19/mo | - |
| tl;dv | 10 AI meetings | $18/mo | $35/mo |
Fathom’s unlimited free tier is real but comes with meaningful restrictions: only 5 AI summaries monthly, limited templates, Fathom branding on everything, and no ability to upload existing audio files.
Fireflies offers the best value if you need team-wide adoption with CRM integration. Otter’s pricing has become less competitive as alternatives have emerged.
The Privacy Problem Nobody Wants to Discuss
Here’s where things get uncomfortable.
Both Otter.ai and Fireflies.ai are facing class action lawsuits over their consent practices. The core issue: getting permission from the meeting host doesn’t mean all participants consented.
Fireflies.ai is accused of recording, analyzing, and storing voiceprints without participant consent. The company allegedly lacks a public data retention policy and doesn’t clearly disclose biometric data collection.
Otter.ai faces similar allegations in the Brewer v. Otter.ai lawsuit filed in August 2025. The complaint alleges Otter’s Notetaker seeks consent only from meeting hosts while non-host participants are recorded without explicit consent. The suit also claims Otter uses meeting transcripts to train its AI models without permission.
What this means for you: If you’re recording calls with participants in California, Illinois, or other two-party consent states, you could be creating legal liability. The “I’ll just let the bot announce itself” approach may not satisfy legal requirements.
Data Retention: Where Does Your Conversation Go?
| Tool | Data Retention | AI Training |
|---|---|---|
| Otter.ai | Indefinite | Uses de-identified audio |
| Fireflies | 0-day with third parties | Claims no user data training |
| Fathom | User-controlled | Not disclosed |
| tl;dv | User-controlled | Not disclosed |
Fireflies claims a 0-day retention policy with third parties and says it doesn’t train on user data. But the lack of a clear public retention policy remains a concern flagged in ongoing litigation.
With the EU AI Act becoming fully applicable in August 2026 and Colorado’s Algorithmic Accountability Law in effect since February 2026, these privacy practices are under increasing regulatory scrutiny.
Who Should Use What
Use Otter.ai if you need the most searchable archive of past meetings and don’t mind the dated interface. Best for individual knowledge workers who attend lots of meetings and need to reference them later.
Use Fireflies.ai if you’re a sales team that needs calls synced to your CRM automatically. The workflow automation is the real value, not the transcription itself.
Use Fathom if you’re an individual who wants free unlimited transcription and can live without AI summaries after the first 5 calls each month. Students and freelancers will love it.
Use tl;dv if your team constantly needs to share “that moment from the call” with stakeholders. The clip and highlight features are unmatched.
Use none of them if you’re handling sensitive legal, medical, or confidential business discussions. The privacy implications remain unresolved, and the consent landscape is shifting.
What You Can Do
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Check your legal requirements. Two-party consent states (California, Illinois, and 9 others) require all participants to agree to recording, not just the host.
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Review your provider’s data practices. Ask explicitly: How long is data retained? Is it used for AI training? Who has access?
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Consider self-hosted alternatives. OpenAI’s Whisper running locally gives you comparable accuracy without sending data to third parties. It requires technical setup but eliminates privacy concerns.
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Be explicit with participants. “My AI assistant will transcribe this call” isn’t informed consent. Explain what data is collected and how it’s used.
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Don’t rely on the bot announcement. “Fireflies has joined” popping up isn’t legal notice. Some participants may not notice or understand the implications.
The AI meeting assistant space is evolving fast, but the privacy reckoning is coming. Choose accordingly.