Evidence · first-party tested/Best AI Meeting Notetakers for Accurate Transcripts, Summaries, and Action Items
Ask Fellow returned grounded answers to natural-language questions against the meeting notes, and the tested query produced a cited response rather than an unsupported hallucination.
What was measured
Chat with Notes / Ask Questions
Gives grounded answers with the cited moment and admits when unknown.
context, not decisivetransformation
Q&A over notes is useful, but it is an add-on to the capture and summarization job rather than a core measure of it. (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, 9 other criteria
Action-Item Extraction◐ 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.Editability◐ MixedSummary and action items are editable inline before sharing, but the transcript itself is locked for audit-trail purposes, so editing is only partial.Join Method & Reliability✓ WorkedThe bot auto-joined via Google Calendar integration and stayed connected for the full meeting capture without drops or disconnections, including the late closing portion of the call.Search Across Notes✓ WorkedTranscript search works with exact timestamp retrieval for matching terms, letting users jump to precise moments within the meeting; the report notes cross-meeting search was untested.Sharing Without Registration✓ WorkedShared recap links can be opened by anyone with the link without creating a Fellow account, and the share modal also offers optional password protection for viewers outside the workspace.Speaker Diarization✓ WorkedThe transcript attributed speaker turns correctly across the standup, with all ~10 speakers labeled by name and no attribution errors or generic labels reported.Summary Quality✓ WorkedThe meeting recap was reported as clearly structured and complete, with the key decisions and discussion points preserved and nothing important dropped.Topic Segmentation✓ WorkedThe tool broke the standup into logical topic sections with clear headers and separated discussion points, rather than leaving the meeting as one undifferentiated blob.Transcription Accuracy✓ WorkedThe transcript was near-clean: the tool captured nearly all names, technical jargon, and numbers correctly, with no significant misheard terms or hallucinations observed in the tested meeting.
Provenance
- Observation
- b8fe3f78-ae35-4ccf-b887-6188bac5ad2f
- 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: "fellow",
scenario: "ai-meeting-notetaker"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 7 other tools
measured on Chat with Notes / Ask Questions
Fathom✓ WorkedAsk Fathom answers direct factual questions from the meeting notes with grounded references; for one query it answered that a call was scheduled for 6th August and linked the supporting transcript mention.Fireflies.ai✓ WorkedAskFred answered a natural-language question with a specific grounded response ('August 6th') and relevant context, with no hallucination reported in the tested query.Granola✓ WorkedThe chat/Q&A surface gives grounded answers from the meeting record: on the tool-access question it says access was confirmed that day, cites both the notes and transcript, and identifies rerunning testing as the next step.HappyScribe✓ 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.MeetGeek◐ MixedIt answers direct grounded questions correctly, but the report records an incorrect answer on a speaker-dependent scheduling question, so chat is reliable for simple queries but weaker when attribution/context matters.Notta✓ WorkedThe Q&A interface answered a natural-language question with a grounded response from the meeting record, including the specific date "6th August," and the report observed no hallucinations.Otter.ai✓ WorkedOtter’s AI Chat answered meeting questions with a grounded response and a specific timestamp, and the report says the answers were cited and free of hallucinations in the tested queries.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com