# Which AI Meeting Assistants accurately transcribe meetings with proper speaker attribution across remote and in-room participants?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Speaker attribution is the detail that actually separates a good transcript from a frustrating one, especially once some participants are in a conference room and others dial in remotely. Within <a class="a a--md" elv="true" href="https://www.g2.com/categories/ai-meeting-assistants">AI Meeting Assistants</a>, here's how the ratings stack up.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/fathom-video/reviews"><strong>Fathom</strong></a><strong> (5.0 stars, 7,029 reviews):</strong> The highest rating on the largest review base here, positioned specifically around making every conversation searchable with accurate speaker-level detail.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/fellow/reviews"><strong>Fellow</strong></a><strong> (4.7 stars, 2,438 reviews):</strong> Offers both bot and botless recording, with accurate transcripts across native and bot-based capture methods for mixed remote/in-room setups.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/calendly/reviews"><strong>Calendly</strong></a><strong> (4.7 stars, 2,648 reviews):</strong> Its Notetaker automatically summarizes key details and next steps, though attribution accuracy across a mixed room isn't its primary positioning.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/otter-ai/reviews"><strong>Otter.ai</strong></a><strong> (4.4 stars, 504 reviews):</strong> Integrates with Zoom, Teams, and Google Meet directly, built specifically to auto-join and generate accurate notes across whichever platform a meeting happens on.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Has anyone actually tested attribution accuracy in a room with three people around a table and two dialing in separately? That's the setup where most tools seem to struggle.</p>

##### Post Metadata
- Posted at: 19 days ago
- Author title: Writer
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;I’d test mixed-room meetings separately from fully remote calls. Speaker attribution can look great when everyone has their own mic, but shared-room audio is usually where the real accuracy gap shows up.&lt;/p&gt;

##### Comment Metadata
- Posted at: 17 days ago
- Author title: Marketer





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