Evidence · first-party tested/Best AI Meeting Notetakers for Accurate Transcripts, Summaries, and Action Items
It 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.'
What was measured
Action-Item Extraction
Finds the real action items, ideally with owner and due date, with low false positives.
decisive for this rankingtransformation
Finding the real action items is a central outcome readers are hiring the tool for, not just a convenience feature. (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, 8 other criteria
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.Summary Quality✓ WorkedThe meeting summary is structured into skimmable topic sections rather than one blob, with headings like 'Tool testing & publishing' and 'Access, tracker & expiries.'Summary Quality◐ MixedThe summary can hallucinate a person name: the report says it substituted 'Nadine' for 'Mahreen' in a summary bullet, creating a false team-member attribution.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
- a3626a76-5657-440e-9460-f49e46ad880b
- 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 Action-Item Extraction
Fathom✓ WorkedFathom extracts real commitments into an ACTION ITEMS section with owner attribution; the published output shows timestamped tasks and a named owner on the item.Fellow◐ MixedAction-item extraction was mostly correct, with real commitments and proper owner assignment for most items, but one real action item was misplaced from Mahreen to Anshika; the report states a 95%+ capture rate.Fireflies.ai✓ WorkedGrouped action items by owner, attributed them to the correct team member, and exposed a clickable source timestamp (19:13) for at least one item.Granola✓ WorkedGranola extracts concrete next steps with ownership: the visible action item says to create a subtask and add details, names Mahreen Fathima as owner, and marks the item for same-day follow-up; the report says the extracted list contained no false positives.MeetGeek✓ WorkedIt extracts real commitments as action items rather than noise; the report says all extracted items had correct ownership and timing, and the visible note includes an owned action item with timestamp 19:51.Notta✓ WorkedThe action-item list extracted the real commitments from the call, formatted them as checkbox items with @mentions, and the report says owner assignment was correct with no false positives.Otter.ai⚠ StruggledOtter extracted action items, including at least one due-today API-related task with an assignee, but the report says most items were left without an owner and duplicate entries also appeared, so the output needed manual cleanup before delegation.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com