{"observation":{"id":"d4b52ad2-b536-4580-99fa-644f4b772a93","tool":"fellow","tool_name":"Fellow","criterion":"transcription-accuracy","criterion_name":"Transcription Accuracy","criterion_definition":"Word accuracy on the shared call, especially names, tools, numbers, and jargon.","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"If the transcript gets names, numbers, and jargon wrong, the note-taker has failed at the core job of capturing the call accurately. (3 of 3 judges)","scenario":"ai-demos-daily-standup-31-july-2026","scenario_name":"AI Demos Daily Standup — 31 July 2026","group_tag":"ai-meeting-notetaker","scenario_description":"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.","modality":"image","input_text":null,"input_artifact_refs":[{"alt":null,"url":"https://cdn.futuresmart.ai/public/aidemos/547dd6f13e4a420fa8ad7bf2c88c7612.png?v=1","role":"input","filename":"31-july-meeting-screenshot.png"}],"stresses":["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"],"verdict":"worked","score":null,"score_total":null,"note":"The 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.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/7476ae6a377e411094940f94f34b21f9.png?v=1","role":"output","alt":null},{"url":"https://cdn.futuresmart.ai/public/aidemos/7550582c35e445c5a06d4928dcf28f9b.png?v=1","role":"output","alt":null}],"run_id":"ace58582-3d1e-48ee-996c-9b3cd03f27a2","study_title":"AI Meeting Notetakers — Capture Accurate Transcripts, Summaries & Action Items From Live Calls","study_kind":"generation","research_task":"86baxegnv","tested_at":null,"completeness":"input-and-output","input":{"state":"files","text":null,"files":[{"url":"https://cdn.futuresmart.ai/public/aidemos/547dd6f13e4a420fa8ad7bf2c88c7612.png?v=1","filename":"31-july-meeting-screenshot.png","alt":"AI Demos Daily Standup — 31 July 2026","role":"input"}],"modality":"image","stresses":["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"]},"tool_page_slug":"fellow","tool_url":"https://aidemos.com/tools/fellow","permalink":"https://aidemos.com/evidence/d4b52ad2-b536-4580-99fa-644f4b772a93","api_url":"https://ai.aidemos.com/v1/observations/d4b52ad2-b536-4580-99fa-644f4b772a93"},"peers":[{"id":"1c4f4fe3-3ed8-490d-992b-a25ddd604669","tool":"fathom","tool_name":"Fathom","verdict":"mixed","score":null,"score_total":null,"note":"Fathom'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.\"","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/19b062d60f8e45a6a5fa364948287362.png?v=1","evidence_url":"https://aidemos.com/evidence/1c4f4fe3-3ed8-490d-992b-a25ddd604669"},{"id":"bac222c7-f7cf-4041-8449-df5aa22c88ac","tool":"fireflies-ai","tool_name":"Fireflies.ai","verdict":"worked","score":null,"score_total":null,"note":"Generated a timestamped transcript view, and the report says the full transcript was very accurate: nearly all names, tools, jargon, and numbers were captured correctly with no significant misheard terms or hallucinations.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/7aecac3bebb2479aa0f18cf6c9f1f0db.png?v=1","evidence_url":"https://aidemos.com/evidence/bac222c7-f7cf-4041-8449-df5aa22c88ac"},{"id":"87d23b55-bc59-4d3e-8547-9b80fc1107f6","tool":"granola","tool_name":"Granola","verdict":"failed","score":null,"score_total":null,"note":"On this 25-minute, multi-speaker standup, Granola’s transcript quality is unreliable: the published excerpt shows garbled phrasing and mistranscribed wording, and the report says the mishearing pattern recurs across early, middle, and late sections rather than being isolated to one moment.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/d3ec039f484d40328057665e51ba34de.png?v=1","evidence_url":"https://aidemos.com/evidence/87d23b55-bc59-4d3e-8547-9b80fc1107f6"},{"id":"624ffd2e-c9da-4fb4-acc3-041a5b115a50","tool":"happyscribe","tool_name":"HappyScribe","verdict":"mixed","score":null,"score_total":null,"note":"On 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.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/768c8f926786411984134803cb5396a5.png?v=1","evidence_url":"https://aidemos.com/evidence/624ffd2e-c9da-4fb4-acc3-041a5b115a50"},{"id":"5a191ed7-02a9-4979-931d-9219e0b75fce","tool":"meetgeek","tool_name":"MeetGeek","verdict":"worked","score":null,"score_total":null,"note":"It transcribes a normal ~25-minute, ~10-active-speaker engineering standup mostly accurately, with only minor proper-noun/term drift noted in the report; one example given is \"Madin\" being misheard for \"Mahreen\".","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/f3fbc51e628c42c19595b82c5e481a25.png?v=1","evidence_url":"https://aidemos.com/evidence/5a191ed7-02a9-4979-931d-9219e0b75fce"},{"id":"893f5543-bd03-4e2a-ba30-f6426940628b","tool":"notta","tool_name":"Notta","verdict":"worked","score":null,"score_total":null,"note":"Notta’s transcript capture was accurate on the evaluated standup: the report says it correctly captured names, tool names, numbers, and engineering jargon with no significant word-level errors, silent hallucinations, or misheard terms.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/86173a6a33c7494b96de40392d0740b6.png?v=1","evidence_url":"https://aidemos.com/evidence/893f5543-bd03-4e2a-ba30-f6426940628b"},{"id":"0efa5738-c840-44ba-a72a-b35d289e70fb","tool":"otter-ai","tool_name":"Otter.ai","verdict":"worked","score":null,"score_total":null,"note":"Otter generated a full transcript for the standup and, per the report, captured names, tool names, jargon, and numbers correctly with minimal errors, making the transcript reliable for reference.","artifact_count":3,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/0db942cf24dd4c3f9383ac4f5208e840.png?v=1","evidence_url":"https://aidemos.com/evidence/0efa5738-c840-44ba-a72a-b35d289e70fb"}],"other_criteria":[{"id":"21587b7d-dc6e-4aa1-8ee4-4e5f13641a3e","criterion":"action-item-extraction","criterion_name":"Action-Item Extraction","rank_role":"decisive","verdict":"mixed","score":null,"score_total":null,"note":"Action-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.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/21587b7d-dc6e-4aa1-8ee4-4e5f13641a3e"},{"id":"b8fe3f78-ae35-4ccf-b887-6188bac5ad2f","criterion":"chat-with-notes-ask-questions","criterion_name":"Chat with Notes / Ask Questions","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"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.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/b8fe3f78-ae35-4ccf-b887-6188bac5ad2f"},{"id":"a47ae17f-dfbd-439c-9ba9-e3153156cca8","criterion":"editability","criterion_name":"Editability","rank_role":"context","verdict":"mixed","score":null,"score_total":null,"note":"Summary and action items are editable inline before sharing, but the transcript itself is locked for audit-trail purposes, so editing is only partial.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/a47ae17f-dfbd-439c-9ba9-e3153156cca8"},{"id":"5d9e1f80-f657-4216-8e73-e81047b806aa","criterion":"join-method-reliability","criterion_name":"Join Method & Reliability","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The 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.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/5d9e1f80-f657-4216-8e73-e81047b806aa"},{"id":"a8a8aaba-e0e1-44b8-9cce-4fa91c5e5213","criterion":"search-across-notes","criterion_name":"Search Across Notes","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"Transcript 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.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/a8a8aaba-e0e1-44b8-9cce-4fa91c5e5213"},{"id":"b22ab795-4b0c-4939-80f6-1f9daca9f6e6","criterion":"sharing-without-registration","criterion_name":"Sharing Without Registration","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"Shared 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.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/b22ab795-4b0c-4939-80f6-1f9daca9f6e6"},{"id":"5928b605-59f7-4372-a4b7-914060123f74","criterion":"speaker-diarization","criterion_name":"Speaker Diarization","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The transcript attributed speaker turns correctly across the standup, with all ~10 speakers labeled by name and no attribution errors or generic labels reported.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/5928b605-59f7-4372-a4b7-914060123f74"},{"id":"d89239cd-ae18-4967-90d8-e968276badf1","criterion":"summary-quality","criterion_name":"Summary Quality","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The meeting recap was reported as clearly structured and complete, with the key decisions and discussion points preserved and nothing important dropped.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/d89239cd-ae18-4967-90d8-e968276badf1"},{"id":"b69458f2-5b1d-4915-bf53-39ab59f059d2","criterion":"topic-segmentation","criterion_name":"Topic Segmentation","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"The tool broke the standup into logical topic sections with clear headers and separated discussion points, rather than leaving the meeting as one undifferentiated blob.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/b69458f2-5b1d-4915-bf53-39ab59f059d2"}],"appears_in":[{"page_type":"ranking","slug":"ai-meeting-notetakers","title":"Best AI Meeting Notetakers for Accurate Transcripts, Summaries, and Action Items","url":"https://aidemos.com/best/ai-meeting-notetakers","binding":"run"}],"same_scenario":[{"id":"1c4f4fe3-3ed8-490d-992b-a25ddd604669","tool":"fathom","tool_name":"Fathom","verdict":"mixed","score":null,"score_total":null,"note":"Fathom'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.\""},{"id":"bac222c7-f7cf-4041-8449-df5aa22c88ac","tool":"fireflies-ai","tool_name":"Fireflies.ai","verdict":"worked","score":null,"score_total":null,"note":"Generated a timestamped transcript view, and the report says the full transcript was very accurate: nearly all names, tools, jargon, and numbers were captured correctly with no significant misheard terms or hallucinations."},{"id":"87d23b55-bc59-4d3e-8547-9b80fc1107f6","tool":"granola","tool_name":"Granola","verdict":"failed","score":null,"score_total":null,"note":"On this 25-minute, multi-speaker standup, Granola’s transcript quality is unreliable: the published excerpt shows garbled phrasing and mistranscribed wording, and the report says the mishearing pattern recurs across early, middle, and late sections rather than being isolated to one moment."},{"id":"624ffd2e-c9da-4fb4-acc3-041a5b115a50","tool":"happyscribe","tool_name":"HappyScribe","verdict":"mixed","score":null,"score_total":null,"note":"On 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."},{"id":"5a191ed7-02a9-4979-931d-9219e0b75fce","tool":"meetgeek","tool_name":"MeetGeek","verdict":"worked","score":null,"score_total":null,"note":"It transcribes a normal ~25-minute, ~10-active-speaker engineering standup mostly accurately, with only minor proper-noun/term drift noted in the report; one example given is \"Madin\" being misheard for \"Mahreen\"."},{"id":"893f5543-bd03-4e2a-ba30-f6426940628b","tool":"notta","tool_name":"Notta","verdict":"worked","score":null,"score_total":null,"note":"Notta’s transcript capture was accurate on the evaluated standup: the report says it correctly captured names, tool names, numbers, and engineering jargon with no significant word-level errors, silent hallucinations, or misheard terms."},{"id":"0efa5738-c840-44ba-a72a-b35d289e70fb","tool":"otter-ai","tool_name":"Otter.ai","verdict":"worked","score":null,"score_total":null,"note":"Otter generated a full transcript for the standup and, per the report, captured names, tool names, jargon, and numbers correctly with minimal errors, making the transcript reliable for reference."}]}