AI meeting notes are automatically generated records of a meeting — a transcript of who said what, a structured summary, and the action items — created by recording the meeting and letting software transcribe and organize it. Instead of typing while you talk, you record, and the notes write themselves.
This guide explains how the pipeline works, what makes the output trustworthy, and what to look for when choosing a tool.
How do AI meeting notes work?
Behind a single "record" button, four things happen in sequence:
- Transcription (speech-to-text). The audio is converted to text by an automatic speech recognition (ASR) model.
- Speaker diarization. The transcript is split by speaker — the "who said what" — so a wall of text becomes a labeled conversation.
- Structuring. A language model extracts an overview, the decisions, deadlines, and action items.
- Recall. The structured record is stored so you can search it or ask it questions later.
The result is that a 45-minute meeting becomes a titled, searchable note in seconds of reading, not an hour of cleanup.
What's the difference between transcription and AI notes?
A plain transcript is step one only. AI meeting notes go further:
| Plain transcript | AI meeting notes | |
|---|---|---|
| Output | A block of text | Speaker-labeled transcript + summary |
| Who said what | Often missing | Labeled automatically |
| Action items | You find them | Extracted for you |
| Later | Ctrl-F in one file | Ask questions across everything |
How accurate are AI meeting notes?
Modern ASR transcribes clear audio at roughly 95–99% word accuracy. Accuracy drops with background noise, crosstalk, heavy accents, or rare jargon — so the best tools also learn the voices and vocabulary you use most, and let you correct names once so they're right next time.
What should I look for in a meeting notes tool?
- Speaker recognition that persists. Assign a person once and have them recognized on every future call, instead of re-labeling "Speaker 2" every time.
- Grounded, cited answers. When you ask a question later, the answer should cite the exact moment it came from — not hallucinate.
- Privacy you can verify. Your recordings shouldn't be used to train shared models, and you should be able to export or delete them.
How Remindr does it
Remindr records on web and mobile, transcribes and labels speakers, and turns each meeting into an overview with action items and deadlines pulled out. Because it learns voices over time, recurring participants show up by name — and you can ask your meetings questions afterward and get answers with citations.
See it in context on the meetings use-case page, or read more about how speaker diarization works. Weighing tools? Compare Remindr vs Otter.ai, Remindr vs Fireflies.ai and Remindr vs Jamie.