Evidence · first-party tested/Best AI Meeting Notetakers for Accurate Transcripts, Summaries, and Action Items
Ask 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.
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, 7 other criteria
Action-Item Extraction✓ 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.Join Method & Reliability✓ WorkedThe bot joined Google Meet successfully and stayed connected for the full ~25-minute call, with no mid-call disconnections or plan-limit cutoffs.Search Across Notes✓ WorkedTranscript search supports keyword lookup and returns a matched snippet for "API," surfacing the relevant moment and the linked action item "Create subtasks for API benchmarking; tag Divya on completion."Speaker Diarization◐ MixedFathom separates most speakers correctly in a busy multi-speaker standup, but the report observed one rapid-transition segment where two speakers' lines were merged into a single speaker block.Summary Quality✓ 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.Topic Segmentation✓ WorkedFathom breaks the standup into named topical sections instead of one blob, including headers like "Process & System Blockers" and "Content Quality & Review Process."Transcription Accuracy◐ MixedFathom's transcript mostly preserves the meeting's names and technical content, but the report records one confirmed name-level error: "Mahreen" was rendered as "Meryl."
Provenance
- Observation
- 070f7f5f-046c-4139-a132-6e00a3b57acc
- 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: "fathom",
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
Fellow✓ WorkedAsk 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.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