What to look for in an AI meeting notes app

The market is crowded — and confusing

There are dozens of AI meeting note apps now. They all promise the same things: automatic transcription, AI summaries, action item extraction. Feature lists start to blur together.

But the differences that matter aren't in the feature list. They're in the architecture — how the tool works under the hood, where your data goes, and what happens when conditions aren't perfect.

Here's what to actually evaluate.

1. Where does the processing happen?

This is the most important question and the one most people skip. There are two models:

• Cloud processing: Your audio gets uploaded to a server, processed remotely, and results come back. This is how most tools work — Otter, Fireflies, and similar services. It means your conversations pass through infrastructure you don't control.
• On-device processing: The AI runs on your phone or computer. Audio never leaves your device. This is harder to build but better for privacy and reliability.

If privacy matters to you — and it should, given what gets discussed in meetings — on-device processing is the stronger choice.

2. Does it work without internet?

Meetings happen in conference rooms with bad Wi-Fi, on planes, in basements, at client sites with restricted networks. A meeting notes tool that requires internet fails in exactly the situations where you need it most.

Test this before you commit: put your phone in airplane mode and try to record and process a meeting. If the tool can't handle it, that's a fundamental limitation.

3. How does it handle multiple speakers?

Meeting notes are far more useful when you know who said what. "The budget needs to be revisited" means something very different depending on whether it came from the CEO or a junior analyst.

Look for speaker diarization — the ability to automatically identify and label different speakers. Some tools do this well, others barely attempt it. And check whether diarization works without requiring speakers to identify themselves first.

4. What's the actual summary quality?

AI summaries range from genuinely useful to worse than no summary at all. Bad summaries give you false confidence that you've captured the meeting, when you've actually missed the important parts.

Evaluate summaries by asking:

• Does it capture decisions made during the meeting?
• Does it extract action items with owners?
• Does it distinguish between discussion and conclusion?
• Is it concise enough to scan in 30 seconds?

A good summary should let you skip the transcript entirely for most meetings.

5. What does it cost — really?

Many AI meeting tools have aggressive pricing that scales with usage. Free tiers with strict limits, per-seat charges, per-minute pricing for transcription. The tool that seems affordable at 5 meetings a week can become expensive at 20.

Look at total cost of ownership:

• Is there a per-meeting or per-minute charge?
• Do essential features require the paid tier?
• What happens when you exceed usage limits?

Tools with on-device processing — like aira — have a structural advantage here. There's no server-side compute cost per meeting, which means the pricing model can be fundamentally different. No per-minute charges, no usage caps on core features.

6. Does it lock you in?

Your meeting notes are valuable data. Can you export them? In what format? What happens to your notes if you switch tools or the company shuts down?

Avoid tools where your data lives exclusively on the vendor's servers with no clean export path. Your notes should be yours — accessible and portable.

7. How intrusive is it?

Some meeting tools join calls as a visible bot — showing up in the participant list, announcing their presence, making everyone aware that the meeting is being recorded by a third party. This changes the dynamics of a meeting.

Other approaches are less intrusive: recording locally through system audio, capturing the microphone on your device, or working as a native app that doesn't need to "join" anything. These feel like using a notebook, not inviting a surveillance tool.

The checklist

When evaluating an AI meeting notes app, run through these questions:

• Does it process audio on-device or in the cloud?
• Does it work offline?
• Does it identify different speakers automatically?
• Are the AI summaries accurate and concise?
• Is pricing transparent with no usage surprises?
• Can you export your data easily?
• Does it work without joining calls as a bot?

aira was built to check every box: on-device processing, offline capability, automatic speaker diarization, structured AI summaries, no per-meeting pricing, and data that stays on your phone.

Frequently asked questions

Do I need a separate app or can I use what's built into Zoom/Teams?

Built-in transcription features are improving but still limited. They typically require internet, send data to the platform's servers, and offer basic transcription without structured summaries or action item extraction. A dedicated app gives you better AI processing and more control over your data.

What's the difference between transcription and meeting notes?

Transcription is a word-for-word record of everything said. Meeting notes are the useful parts: decisions, action items, key discussion points. Good meeting notes apps do both — they transcribe first, then summarize. The summary is what you'll actually use day-to-day.

How important is speaker identification?

Very. Meeting notes without speaker labels lose critical context. "We should delay the launch" means something completely different depending on who said it. Automatic speaker diarization is one of the features that separates genuinely useful tools from basic transcription.

Want a meeting notes app that processes everything on your phone? Learn about aira's private, on-device approach.