{"observation":{"id":"9552a2b6-0bc3-4802-8f1b-f9cf98c13b46","tool":"otter-ai","tool_name":"Otter.ai","criterion":"speaker-diarization","criterion_name":"Speaker Diarization","criterion_definition":"Correctly attributes who said what across a multi-speaker standup.","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"Correctly attributing who said what is part of making the transcript and notes trustworthy in multi-speaker meetings. (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":"failed","score":null,"score_total":null,"note":"Otter’s diarization was effectively unusable in this multi-speaker standup: only 1 of about 10 active speakers was identified by name, while the other 9 were left as generic labels or unattributed, which the report summarizes as a 90% failure rate.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/c2c822851e2f4e71a1ae3b14247c11d3.png?v=1","role":"output","alt":null},{"url":"https://cdn.futuresmart.ai/public/aidemos/703ba634c2d64e048e0a4679dc590568.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":"otter-ai","tool_url":"https://aidemos.com/tools/otter-ai","permalink":"https://aidemos.com/evidence/9552a2b6-0bc3-4802-8f1b-f9cf98c13b46","api_url":"https://ai.aidemos.com/v1/observations/9552a2b6-0bc3-4802-8f1b-f9cf98c13b46"},"peers":[{"id":"e9695d25-df6e-448b-b185-4ad01e885bdf","tool":"fathom","tool_name":"Fathom","verdict":"mixed","score":null,"score_total":null,"note":"Fathom 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.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/e6b553ff015d4c309c161b0bb12a1660.png?v=1","evidence_url":"https://aidemos.com/evidence/e9695d25-df6e-448b-b185-4ad01e885bdf"},{"id":"5928b605-59f7-4372-a4b7-914060123f74","tool":"fellow","tool_name":"Fellow","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,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/f6c095044c7a4498b82f300b683163dd.png?v=1","evidence_url":"https://aidemos.com/evidence/5928b605-59f7-4372-a4b7-914060123f74"},{"id":"a1eae6d9-4eff-41c0-9357-c4b9c8e6f7fb","tool":"fireflies-ai","tool_name":"Fireflies.ai","verdict":"worked","score":null,"score_total":null,"note":"Attributed consecutive turns to distinct speakers in the transcript, and the report says speaker identification was almost complete with only minor attribution errors.","artifact_count":3,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/04c680b706994807aa25f0135512b6ee.png?v=1","evidence_url":"https://aidemos.com/evidence/a1eae6d9-4eff-41c0-9357-c4b9c8e6f7fb"},{"id":"73b827a9-4822-4d1e-a8ad-b6853c5eab4d","tool":"granola","tool_name":"Granola","verdict":"failed","score":null,"score_total":null,"note":"Granola’s default capture does not attribute speakers: the settings panel shows Speaker tags switched off, and the transcript excerpt is a plain text wall with no speaker labels, so diarization is absent unless the user manually enables it.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/ecd4eac38c5f4f1f9e0d671349a4f71a.png?v=1","evidence_url":"https://aidemos.com/evidence/73b827a9-4822-4d1e-a8ad-b6853c5eab4d"},{"id":"472fb01a-44b0-4713-b649-40ee52da5802","tool":"happyscribe","tool_name":"HappyScribe","verdict":"mixed","score":null,"score_total":null,"note":"It 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.","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/64855a79c2564122bac93c704797f365.png?v=1","evidence_url":"https://aidemos.com/evidence/472fb01a-44b0-4713-b649-40ee52da5802"},{"id":"4f7e5b21-ff4f-4846-9a07-3219c0659681","tool":"meetgeek","tool_name":"MeetGeek","verdict":"mixed","score":null,"score_total":null,"note":"It identifies most speakers in a multi-speaker standup, but leaves at least one utterance as \"Unknown speaker\" and misattributes some lines to the wrong speaker, so attribution is not fully reliable.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/a909947fdbe64d41b2bc10dca0f44193.png?v=1","evidence_url":"https://aidemos.com/evidence/4f7e5b21-ff4f-4846-9a07-3219c0659681"},{"id":"089aaaff-2da4-4739-8045-46df7a2f1e6b","tool":"notta","tool_name":"Notta","verdict":"mixed","score":null,"score_total":null,"note":"Speaker attribution was mostly correct, with nearly all speakers identified by name, but the transcript still showed some misattributed lines, so diarization was not fully reliable for every turn.","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/f10e8fde29a2451f990006d9cee5ec84.png?v=1","evidence_url":"https://aidemos.com/evidence/089aaaff-2da4-4739-8045-46df7a2f1e6b"}],"other_criteria":[{"id":"914e606f-d39b-4941-8b42-0f3b3653ee40","criterion":"action-item-extraction","criterion_name":"Action-Item Extraction","rank_role":"decisive","verdict":"struggled","score":null,"score_total":null,"note":"Otter 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.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/914e606f-d39b-4941-8b42-0f3b3653ee40"},{"id":"295ea299-5f4d-480e-8ff7-36708e2bc9f7","criterion":"chat-with-notes-ask-questions","criterion_name":"Chat with Notes / Ask Questions","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"Otter’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.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/295ea299-5f4d-480e-8ff7-36708e2bc9f7"},{"id":"0364fbbc-9644-47cc-97a6-60174baab699","criterion":"editability","criterion_name":"Editability","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"Otter exposes inline editing controls for transcript and summary outputs before sharing, so wrong content can be corrected in-product rather than only exported as-is.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/0364fbbc-9644-47cc-97a6-60174baab699"},{"id":"1ec8c4c4-913b-4e17-8150-83589c5c2f7b","criterion":"join-method-reliability","criterion_name":"Join Method & Reliability","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Otter’s bot joined Google Meet successfully and stayed connected through the full ~25-minute call with no mid-call dropout or ejection, so the meeting was captured end to end.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/1ec8c4c4-913b-4e17-8150-83589c5c2f7b"},{"id":"68c18886-3c73-4ed3-bd68-92814dc4b10b","criterion":"search-across-notes","criterion_name":"Search Across Notes","rank_role":"context","verdict":"mixed","score":null,"score_total":null,"note":"Otter does not show a direct transcript keyword-search workflow in the transcript view; lookup is routed through AI Chat instead, where a natural-language timestamp question returned a specific answer at 0:07:06.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/68c18886-3c73-4ed3-bd68-92814dc4b10b"},{"id":"bc9e6d91-ebd3-4a9e-99eb-5cc194791f45","criterion":"sharing-without-registration","criterion_name":"Sharing Without Registration","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"A shared meeting transcript opened without requiring sign-in, exposing the meeting title, metadata, and transcript snippets; the share dialog also offers restricted access and link-copy controls.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/bc9e6d91-ebd3-4a9e-99eb-5cc194791f45"},{"id":"85b52298-f079-4410-b519-3fc1d34593a0","criterion":"summary-quality","criterion_name":"Summary Quality","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Otter 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.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/85b52298-f079-4410-b519-3fc1d34593a0"},{"id":"eedc69a7-0929-4cbd-a001-6122eed42379","criterion":"topic-segmentation","criterion_name":"Topic Segmentation","rank_role":"context","verdict":"worked","score":null,"score_total":null,"note":"Otter broke the standup into useful topic sections rather than one blob, with named headings such as Issue Task Assignments and Status Updates and Error Resolution and Task Link Sharing, making the summary skimmable.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/eedc69a7-0929-4cbd-a001-6122eed42379"},{"id":"0efa5738-c840-44ba-a72a-b35d289e70fb","criterion":"transcription-accuracy","criterion_name":"Transcription Accuracy","rank_role":"decisive","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,"evidence_url":"https://aidemos.com/evidence/0efa5738-c840-44ba-a72a-b35d289e70fb"}],"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":"e9695d25-df6e-448b-b185-4ad01e885bdf","tool":"fathom","tool_name":"Fathom","verdict":"mixed","score":null,"score_total":null,"note":"Fathom 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."},{"id":"5928b605-59f7-4372-a4b7-914060123f74","tool":"fellow","tool_name":"Fellow","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."},{"id":"a1eae6d9-4eff-41c0-9357-c4b9c8e6f7fb","tool":"fireflies-ai","tool_name":"Fireflies.ai","verdict":"worked","score":null,"score_total":null,"note":"Attributed consecutive turns to distinct speakers in the transcript, and the report says speaker identification was almost complete with only minor attribution errors."},{"id":"73b827a9-4822-4d1e-a8ad-b6853c5eab4d","tool":"granola","tool_name":"Granola","verdict":"failed","score":null,"score_total":null,"note":"Granola’s default capture does not attribute speakers: the settings panel shows Speaker tags switched off, and the transcript excerpt is a plain text wall with no speaker labels, so diarization is absent unless the user manually enables it."},{"id":"472fb01a-44b0-4713-b649-40ee52da5802","tool":"happyscribe","tool_name":"HappyScribe","verdict":"mixed","score":null,"score_total":null,"note":"It 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."},{"id":"4f7e5b21-ff4f-4846-9a07-3219c0659681","tool":"meetgeek","tool_name":"MeetGeek","verdict":"mixed","score":null,"score_total":null,"note":"It identifies most speakers in a multi-speaker standup, but leaves at least one utterance as \"Unknown speaker\" and misattributes some lines to the wrong speaker, so attribution is not fully reliable."},{"id":"089aaaff-2da4-4739-8045-46df7a2f1e6b","tool":"notta","tool_name":"Notta","verdict":"mixed","score":null,"score_total":null,"note":"Speaker attribution was mostly correct, with nearly all speakers identified by name, but the transcript still showed some misattributed lines, so diarization was not fully reliable for every turn."}]}