Evidence · first-party tested/Best AI Meeting Notetakers for Accurate Transcripts, Summaries, and Action Items
The summary can hallucinate a person name: the report says it substituted 'Nadine' for 'Mahreen' in a summary bullet, creating a false team-member attribution.
What was measured
Summary Quality
Captures decisions and key points, is structured and skimmable, and drops nothing important.
decisive for this rankingtransformation
The product is being judged on whether it produces a useful meeting summary that preserves key decisions and points without missing important content. (3 of 3 judges)
What was given, what came back
Test input: AI Demos Daily Standup — 31 July 2026 · image · group: ai-meeting-notetaker
Input — what we sent
AI Demos Daily Standup — 31 July 2026
A real 25-minute technical engineering daily standup with 14 attendees and about 10 active speakers, used as the single parallel-capture meeting for evaluating AI meeting notetakers on transcription, diarization, summaries, action items, search/chat, and collaboration features.
Why this input is hard
- · Transcription accuracy for real names, tool names, numbers, and technical jargon
- · Speaker diarization across multiple active speakers
- · Robustness to overlapping speech, crosstalk, and rapid turn-taking
- · Join reliability for bot-based and botless capture
- · Summary quality on identical source material
- · Action-item extraction with correct owners and commitments
- · Topic segmentation of standup updates
- · Search and chat grounded in the meeting content
- · Sharing, API, MCP, integrations, plan limits, languages, and privacy feature coverage
Output — unretouched
Also checked on this input — same tool, 7 other criteria
Action-Item Extraction◐ MixedIt extracted the real action item about updating logs, but owner attribution was wrong because the misheard name cascaded into the action item and showed 'Nadine' instead of 'Mahreen.'Chat with Notes / Ask Questions✓ WorkedAI chat answers a meeting question with a grounded transcript-backed response, returning that the call was scheduled for '6th August' and explicitly indicating it is reading the transcription.Join Method & Reliability✓ WorkedThe bot joined the Google Meet call and stayed connected through the full meeting capture with no visible dropout or mid-call disconnection.Search Across Notes⚠ StruggledThere is no dedicated transcript search UI, so direct keyword lookup across notes is not available from the transcript view and is only routed indirectly through AI Chat.Speaker Diarization◐ MixedIt identified most speakers, but the report says multiple transcript lines were assigned to the wrong speaker, so speaker-to-statement mapping was not fully reliable across transitions.Topic Segmentation✓ WorkedIt breaks the standup into logical topic sections that reflect meeting flow, instead of presenting the notes as a single undifferentiated block.Transcription Accuracy◐ MixedOn this ~25-minute multi-speaker standup, HappyScribe captured the vast majority of names, tools, and jargon correctly, and the report records only 1–2 misheard words.
Provenance
- Observation
- ab6fc227-dfb2-4524-a6ab-83adb117660f
- Evidence run
- ace58582-3d1e-48ee-996c-9b3cd03f27a2
- Study
- AI Meeting Notetakers — Capture Accurate Transcripts, Summaries & Action Items From Live Calls
- Research task
- 86baxegnv
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "happyscribe",
scenario: "ai-meeting-notetaker"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 7 other tools
measured on Summary Quality
Fathom✓ WorkedFathom produces a skimmable written recap with named sections such as Meeting Purpose, Key Takeaways, and Topics; the report describes the summary as structured and concise.Fellow✓ WorkedThe meeting recap was reported as clearly structured and complete, with the key decisions and discussion points preserved and nothing important dropped.Fireflies.ai✓ WorkedProduced a structured notes summary with a named header ('Task Status and Issue Resolution') rather than a blob, and the report says the full summary was multi-section and did not drop important points.Granola✓ WorkedGranola produces skimmable summaries with named sections; the meeting output is organized into at least three top-level sections, including Use Case Status and Review Progress, Tool Research and Publishing, and Access Tracker Updates.MeetGeek✓ WorkedIt produces a clear, skimmable meeting summary with topic organization and a Next Steps section, and the report says it preserved the major decisions and discussion points.Notta✓ WorkedThe generated meeting summary was comprehensive and skimmable, with structured sections such as Task & Issue Management and a mindmap-style organization that reflected the meeting flow.Otter.ai✓ WorkedOtter produced a clear, structured meeting summary that the report says covered the key decisions and discussion points without dropping anything important, and the summary page loaded with organized sections like Overview and Action Items.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com