{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tl-dv","slug":"tl-dv","name":"tl;dv","type":"product","url":"https://tldv.io","page_url":"https://unfragile.ai/tl-dv","categories":["automation"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tl-dv__cap_0","uri":"capability://automation.workflow.browser.native.meeting.capture.without.bot.injection","name":"browser-native meeting capture without bot injection","description":"Captures audio and video from Zoom, Google Meet, and Teams calls directly through browser extension or native app integration without requiring a meeting bot to be invited. The capture mechanism operates client-side at the browser/app level, intercepting the media stream before it reaches the meeting platform's servers, then streams or buffers the raw audio/video for post-processing. This approach eliminates the need for explicit bot invitations and reduces meeting participant friction.","intents":["I want to record meetings without adding a bot participant that everyone can see","I need automatic recording that starts when I join a call without manual setup","I want to capture calls across multiple platforms (Zoom, Google Meet, Teams) with a single tool"],"best_for":["sales teams conducting frequent client calls who want frictionless recording","remote-first organizations where meeting bots create UX friction","enterprises with strict meeting participant policies that discourage bots"],"limitations":["Capture mechanism is undisclosed — unclear if it uses WebRTC interception, native API hooks, or browser extension content scripts","No real-time transcription mentioned; processing appears post-meeting only","Requires browser extension or app installation on user's device; cannot capture from shared/borrowed devices without setup","Recording consent and legal compliance (one-party vs two-party consent) are user's responsibility — product does not enforce or guide this"],"requires":["Active Zoom, Google Meet, or Teams account","Browser extension installed (Chrome/Edge/Safari/Firefox — specific versions unknown)","tl;dv account (free tier available)","Sufficient local storage for buffering audio/video during call"],"input_types":["audio stream from meeting platform","video stream from meeting platform"],"output_types":["raw audio file (format unknown)","raw video file (format unknown)","buffered media ready for transcription pipeline"],"categories":["automation-workflow","voice-audio"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_1","uri":"capability://data.processing.analysis.automatic.speech.to.text.transcription.with.speaker.attribution","name":"automatic speech-to-text transcription with speaker attribution","description":"Converts captured meeting audio into timestamped text transcripts with speaker identification, enabling users to search and reference specific moments in calls. The transcription pipeline processes audio post-meeting (latency unknown) and generates word-level timestamps, allowing clips and summaries to reference exact moments. Speaker attribution mechanism is undisclosed but implied by action item extraction and CRM logging features that track who said what.","intents":["I need a searchable text record of everything said in my meetings","I want to find the exact moment someone mentioned a specific topic or objection","I need to know who committed to what action and when they said it"],"best_for":["sales teams needing to track objections and commitments by speaker","customer success teams analyzing customer feedback and pain points","product teams extracting feature requests and bug reports from customer calls"],"limitations":["Transcription engine provider is unknown — could be proprietary, OpenAI Whisper, Google Speech-to-Text, or other; affects accuracy and language support","Multi-language support only explicitly confirmed for Japanese and Spanish; other languages unknown","Transcription accuracy metrics not published; no SLA provided","Speaker diarization mechanism unknown — may fail with multiple speakers, overlapping speech, or accents","No real-time transcription; appears to be post-meeting batch processing only","Handling of long meetings (2+ hours) unknown — may truncate, summarize, or chunk transcripts"],"requires":["Completed meeting recording from tl;dv capture","Audio quality sufficient for speech recognition (background noise tolerance unknown)","Meeting language must be supported (Japanese, Spanish confirmed; others unknown)"],"input_types":["audio stream from captured meeting"],"output_types":["timestamped transcript (text with word-level timing)","speaker-attributed transcript (speaker name/ID + text + timestamp)","searchable transcript index"],"categories":["data-processing-analysis","voice-audio"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_10","uri":"capability://automation.workflow.free.tier.with.unlimited.meeting.recording","name":"free tier with unlimited meeting recording","description":"Offers a free tier that includes unlimited meeting recording, transcription, and basic summarization without time limits or meeting count restrictions. The free tier is designed to reduce friction for individual users and small teams to adopt tl;dv before upgrading to paid features. Specific limitations of the free tier (e.g., storage limits, feature restrictions, user seat limits) are not disclosed in documentation.","intents":["I want to try tl;dv without paying to see if it works for my team","I need unlimited meeting recording without worrying about hitting a quota","I want basic meeting intelligence (transcripts, summaries) without paying"],"best_for":["individual contributors and small teams evaluating tl;dv","budget-conscious teams wanting to start with free tier and upgrade later","teams with low meeting volume who don't need paid features"],"limitations":["Free tier feature set is not clearly defined — unclear what features are included vs paid-only","Free tier limitations unknown — unclear if there are storage limits, user seat limits, or feature restrictions","Upgrade path unknown — unclear what triggers upgrade to paid tier or what paid features cost","Free tier SLA unknown — unclear if free tier has lower priority support or performance guarantees","Data retention for free tier unknown — unclear if meetings are deleted after a period","CRM integration availability on free tier unknown — may be paid-only feature"],"requires":["tl;dv account (free signup)","Zoom, Google Meet, or Teams account","Browser extension installation"],"input_types":["meeting audio/video from supported platforms"],"output_types":["meeting recording (storage location unknown)","transcript (text with timestamps)","basic summary (text, format unknown)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_2","uri":"capability://text.generation.language.customizable.ai.meeting.summarization.with.framework.templates","name":"customizable ai meeting summarization with framework templates","description":"Generates post-meeting summaries using AI models with user-selectable frameworks (MEDDIC, Smart AI Topics, custom) that structure the summary output to match sales, product, or marketing workflows. The summarization engine processes the full transcript and produces abstractive summaries (not just extractive highlights) in 1-5 minutes (claimed 'instantly' but latency unknown). Users can define custom summary templates via prompts, enabling role-specific summaries (e.g., 'extract only objections and how they were handled' for sales, 'extract feature requests and prioritize by frequency' for product).","intents":["I need a quick recap of what happened in a 60-minute call without reading the full transcript","I want summaries formatted for my specific role (sales objection tracking, product feature requests, marketing pain points)","I want to define custom summary formats that extract only the information relevant to my team"],"best_for":["sales managers needing MEDDIC-formatted call recaps for pipeline management","product managers extracting feature requests and bugs from customer calls","marketing teams identifying customer pain points and quotes for campaigns","customer success teams quickly understanding call context for follow-ups"],"limitations":["LLM provider unknown — could be GPT-4, Claude, proprietary model, or ensemble; affects summary quality, bias, and hallucination risk","Context window handling for long meetings unknown — may truncate, sample, or hierarchically summarize","Summary accuracy and hallucination rates not published; no quality SLA","Custom template depth unknown — unclear if templates are simple prompts or structured schema-based","MEDDIC and Smart AI Topics implementations are undisclosed — may not match sales/product team expectations","Latency claimed as 'instant' but actual SLA unknown; may be 1-5 minutes post-meeting","No A/B testing or feedback loop mentioned — summaries may not improve over time"],"requires":["Completed meeting transcription from tl;dv transcription pipeline","tl;dv account with summarization feature enabled (may be paid tier only)","For custom templates: ability to write natural language prompts or access to template builder (interface unknown)"],"input_types":["full meeting transcript (text with timestamps and speaker attribution)"],"output_types":["MEDDIC-formatted summary (text with sections: Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, Champion)","Smart AI Topics summary (text with auto-identified topics and key points)","custom-template summary (text formatted per user-defined prompt)","structured summary (if schema-based; format unknown)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_3","uri":"capability://data.processing.analysis.automatic.action.item.extraction.and.assignment","name":"automatic action item extraction and assignment","description":"Identifies commitments, tasks, and next steps mentioned during meetings and extracts them as structured action items with speaker attribution, due date inference, and optional CRM task creation. The extraction uses NLP/LLM-based pattern matching to identify phrases like 'I'll send you', 'we need to', 'by next week', etc., and maps them to speakers and inferred deadlines. Extracted action items can be automatically logged to CRM systems or exported as task lists.","intents":["I want to automatically capture who committed to what without manually taking notes","I need action items to be assigned to the right person based on who said them","I want action items automatically created in my CRM or task management system"],"best_for":["sales teams tracking deal-related commitments and follow-ups","customer success teams ensuring promised actions are completed","product teams tracking feature requests and bug fixes committed in calls","any team needing accountability for meeting commitments"],"limitations":["Extraction logic is undisclosed — unclear if rule-based, regex, NLP, or LLM-based; affects accuracy","Accuracy metrics not published; no SLA for false positives/negatives","Implicit vs explicit commitments — unclear if tool catches 'we should' vs 'I will'","Due date inference mechanism unknown — may fail with vague timelines ('soon', 'ASAP', 'next quarter')","Speaker attribution depends on transcription quality — may fail if speaker diarization is poor","No manual review/correction workflow mentioned — extracted items may be incorrect and require manual editing","CRM integration scope unknown — may not support all CRM systems or may require manual mapping"],"requires":["Completed meeting transcription with speaker attribution","tl;dv account with action item extraction enabled (may be paid tier only)","Optional: CRM account for automatic task creation (specific systems unknown)"],"input_types":["full meeting transcript with speaker attribution and timestamps"],"output_types":["structured action item list (format: speaker, action, inferred due date, priority unknown)","CRM task objects (if CRM integration enabled; schema depends on CRM system)","task list export (format unknown — CSV, JSON, etc.)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_4","uri":"capability://tool.use.integration.crm.integration.with.automatic.call.logging.and.field.population","name":"crm integration with automatic call logging and field population","description":"Automatically logs meeting summaries, transcripts, action items, and call outcomes to CRM systems (specific platforms unknown) without manual data entry. The integration maps tl;dv outputs (summary, action items, speaker attribution) to CRM fields (call notes, next steps, deal stage, etc.) and creates or updates CRM records based on meeting participants and detected deal context. Supports auto-drafting of follow-up emails and task creation within the CRM.","intents":["I want meeting notes automatically logged to my CRM without copying and pasting","I need action items automatically created as CRM tasks assigned to the right person","I want follow-up emails auto-drafted and ready to send from my CRM"],"best_for":["sales teams using CRM for pipeline management and call tracking","customer success teams logging customer interactions in CRM","enterprises with CRM-centric workflows requiring meeting data integration"],"limitations":["Supported CRM systems are unknown — may only support Salesforce, HubSpot, Pipedrive, or others; not listed in documentation","Field mapping mechanism is undisclosed — unclear if automatic, configurable, or manual","Deal/contact matching logic unknown — may fail if meeting participants are not in CRM or if deal context is ambiguous","Follow-up email drafting quality unknown — may require significant editing before sending","No API documentation provided — unclear if integration is via native API, Zapier, or proprietary connector","Data sync latency unknown — unclear if real-time or batch (hourly, daily)","No mention of conflict resolution — unclear how tl;dv handles existing CRM data or duplicate records","Requires CRM account and API credentials — security/permission model unknown"],"requires":["Completed meeting summary and action items from tl;dv","CRM account (specific systems unknown; likely Salesforce, HubSpot, Pipedrive, or similar)","CRM API credentials or OAuth token for tl;dv integration","CRM field mapping configuration (manual or automatic — unknown)"],"input_types":["meeting summary (text)","action items (structured list with speaker attribution)","call transcript (text with timestamps)","meeting participants (email addresses or CRM contact IDs)","detected deal/account context (inferred from transcript or participant data)"],"output_types":["CRM call log entry (format depends on CRM system)","CRM task objects (assigned to action item owners)","CRM field updates (deal stage, next steps, call outcome, etc. — schema unknown)","auto-drafted follow-up email (text, ready for manual review and sending)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_5","uri":"capability://search.retrieval.semantic.search.across.meeting.archive.with.clip.generation","name":"semantic search across meeting archive with clip generation","description":"Enables full-text and semantic search across all recorded meetings to find specific topics, speakers, or moments, then generates shareable video/audio clips of matching segments. The search mechanism is undisclosed but likely combines transcript keyword matching with semantic embeddings to find conceptually similar moments across meetings. Clip generation extracts the relevant audio/video segment with context (speaker name, timestamp, summary) and produces a shareable link or downloadable file.","intents":["I need to find all mentions of a specific objection across my last 50 sales calls","I want to create a highlight reel of customer testimonials for a marketing campaign","I need to share a specific moment from a call with my team without sharing the entire recording"],"best_for":["sales teams analyzing objection patterns across multiple calls","marketing teams extracting customer quotes and testimonials for campaigns","product teams finding all feature requests related to a specific feature","training teams creating call examples for coaching"],"limitations":["Search algorithm is undisclosed — unclear if full-text only, semantic, or hybrid; affects search quality and false positive rate","Semantic search implementation unknown — may use tl;dv embeddings, OpenAI embeddings, or other; affects relevance","Search latency unknown — unclear if real-time or indexed; may be slow for large archives","Clip generation mechanism unknown — unclear if automated (based on search results) or manual selection","Clip format and quality unknown — unclear if original video quality, compressed, or audio-only","Clip sharing mechanism unknown — unclear if public links, password-protected, or team-only","Clip retention/expiration unknown — unclear if permanent or time-limited","Search scope unknown — unclear if searches across transcripts only or also summaries and metadata"],"requires":["Multiple completed meeting recordings in tl;dv archive","Search query (natural language or keyword)","tl;dv account with search feature enabled (may be paid tier only)"],"input_types":["search query (text — keyword or natural language)","optional filters (speaker name, date range, meeting type — unknown if supported)"],"output_types":["search results list (matching transcript segments with timestamps and speakers)","video/audio clip (format unknown — MP4, WebM, MP3, etc.)","shareable clip link (format unknown — public, password-protected, or team-only)","clip metadata (speaker, timestamp, summary, meeting date)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_6","uri":"capability://data.processing.analysis.multi.meeting.trend.analysis.and.custom.report.generation","name":"multi-meeting trend analysis and custom report generation","description":"Analyzes patterns across multiple meetings to identify trends, recurring themes, and aggregate insights, then generates custom reports via email or dashboard. The analysis engine processes summaries and transcripts from multiple meetings, applies user-defined custom prompts (e.g., 'extract all customer pain points and rank by frequency'), and produces structured reports with visualizations (charts, tables — format unknown). Reports can be scheduled (daily, weekly, monthly) or generated on-demand.","intents":["I want to know the top 10 customer objections across all my sales calls this month","I need a weekly report of feature requests mentioned in customer calls for the product roadmap","I want to identify trends in customer sentiment or pain points across my team's calls"],"best_for":["sales managers analyzing team performance and objection patterns","product managers aggregating feature requests from customer calls","marketing teams identifying customer pain points and messaging themes","customer success leaders tracking customer sentiment and satisfaction trends","executives needing meeting intelligence dashboards for decision-making"],"limitations":["Custom prompt interface is unknown — unclear if natural language, template-based, or schema-based","Aggregation logic is undisclosed — unclear how trends are identified (frequency, semantic clustering, LLM-based pattern matching)","Report generation latency unknown — unclear if real-time or batch (daily, weekly)","Visualization types unknown — unclear if charts, tables, word clouds, or other formats","Report delivery mechanism unknown — email only mentioned; no dashboard or API access mentioned","Report scheduling options unknown — unclear if daily, weekly, monthly, or custom intervals","Data freshness unknown — unclear if reports include only completed meetings or in-progress calls","No accuracy metrics for trend detection — unclear if trends are statistically significant or just frequent mentions"],"requires":["Multiple completed meeting recordings and summaries in tl;dv archive (minimum number unknown)","Custom prompt definition (natural language or template — interface unknown)","tl;dv account with reporting feature enabled (may be paid tier only)","Email address for report delivery"],"input_types":["meeting summaries and transcripts from multiple meetings (date range configurable)","custom prompt or report template (text)","optional filters (speaker, meeting type, participant, date range — unknown if supported)"],"output_types":["structured report (text with sections and key findings)","visualizations (charts, tables, word clouds — format unknown)","email report (HTML or PDF — format unknown)","dashboard view (if available — unknown)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_7","uri":"capability://data.processing.analysis.role.specific.meeting.intelligence.dashboards","name":"role-specific meeting intelligence dashboards","description":"Provides pre-configured dashboards tailored to sales, product, and marketing roles that surface relevant meeting insights without requiring custom configuration. Sales dashboards show objection tracking, deal progress, and commitment follow-ups; product dashboards show feature requests and bug reports; marketing dashboards show customer pain points and quotes. Dashboards aggregate data from multiple meetings and update as new meetings are recorded and processed.","intents":["As a sales manager, I want a dashboard showing top objections and how my team handled them","As a product manager, I want to see all feature requests mentioned in customer calls ranked by frequency","As a marketing manager, I want a dashboard of customer pain points and quotes for campaign messaging"],"best_for":["sales managers needing quick visibility into team call quality and objection handling","product managers tracking customer feedback and feature request trends","marketing managers identifying messaging themes and customer quotes","team leads needing role-specific meeting intelligence without custom configuration"],"limitations":["Dashboard availability and configuration unknown — unclear which roles have pre-built dashboards or if customizable","Metrics and KPIs unknown — unclear what specific data points are shown (e.g., objection frequency, resolution rate, feature request priority)","Update frequency unknown — unclear if real-time, hourly, or daily","Data accuracy depends on upstream capabilities (summarization, action item extraction, trend analysis) — inherits their limitations","No mention of drill-down or filtering capabilities — unclear if dashboards are static or interactive","Export/sharing options unknown — unclear if dashboards can be shared with stakeholders or exported","Mobile access unknown — unclear if dashboards are web-only or mobile-accessible"],"requires":["Multiple completed meeting recordings in tl;dv archive","tl;dv account with dashboard feature enabled (may be paid tier only)","Role selection (sales, product, marketing, or custom — unknown if customizable)"],"input_types":["meeting summaries, transcripts, and extracted insights from tl;dv pipeline","role selection (sales, product, marketing, etc.)"],"output_types":["role-specific dashboard (HTML/web interface)","dashboard metrics and KPIs (text, numbers, charts — format unknown)","drill-down views (if available — unknown)","export options (if available — format unknown)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_8","uri":"capability://data.processing.analysis.meeting.participant.context.and.crm.contact.matching","name":"meeting participant context and crm contact matching","description":"Automatically identifies meeting participants from email addresses or video call metadata and matches them to CRM contacts, enabling automatic call logging to the correct account/contact record and enriching meeting context with CRM data (company, title, deal stage, etc.). The matching logic is undisclosed but likely uses email domain matching, exact name matching, and fuzzy matching for ambiguous cases. Matched contacts are used to populate CRM fields and determine deal/account context for reporting.","intents":["I want meeting notes automatically logged to the correct CRM contact without manual lookup","I need to know which deal or account a meeting is related to based on participants","I want to enrich meeting context with CRM data like participant title, company, and deal stage"],"best_for":["sales teams using CRM for contact and deal management","customer success teams tracking customer interactions by account","enterprises with large contact databases requiring accurate matching"],"limitations":["Matching logic is undisclosed — unclear if email-based, name-based, or fuzzy matching; affects accuracy","Accuracy metrics not published — unclear false positive/negative rate for ambiguous names or email domains","Handling of multiple matches unknown — unclear if tool prompts for manual selection or auto-selects","CRM system support unknown — unclear which CRM systems are supported for contact matching","Contact enrichment scope unknown — unclear what CRM fields are retrieved and used","Deal/account context inference unknown — unclear how tool determines which deal a meeting relates to","Requires CRM API access — security and permission model unknown"],"requires":["CRM account with contact database (specific systems unknown)","CRM API credentials or OAuth token for tl;dv integration","Meeting participants' email addresses or video call metadata"],"input_types":["meeting participant list (email addresses, names, or video call metadata)","CRM contact database (via API)"],"output_types":["matched CRM contact records (contact ID, name, company, title, email)","matched deal/account records (deal ID, account name, stage, owner)","enriched meeting context (participant roles, company, deal stage, etc.)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__cap_9","uri":"capability://data.processing.analysis.multi.language.transcription.and.summarization","name":"multi-language transcription and summarization","description":"Supports meeting recording, transcription, and summarization in multiple languages, with explicit support for Japanese and Spanish mentioned and other languages unknown. The transcription and summarization pipelines process non-English audio and generate outputs in the source language, enabling global teams to use tl;dv without language barriers. Language detection is likely automatic based on audio characteristics.","intents":["I conduct calls in Japanese and need transcripts and summaries in Japanese","I work with a global team and need tl;dv to support multiple languages","I want to search and analyze meetings across different languages"],"best_for":["global sales teams conducting calls in multiple languages","international customer success teams supporting customers in their native languages","enterprises with multilingual workforces"],"limitations":["Supported languages only explicitly confirmed for Japanese and Spanish; other languages unknown","Language detection mechanism unknown — unclear if automatic or manual selection","Transcription accuracy for non-English languages unknown — may be lower than English","Summarization quality for non-English languages unknown — may be lower than English","Custom templates and frameworks (MEDDIC, Smart AI Topics) may not be available in all languages","Search and analysis may not work across language boundaries (e.g., searching for English term in Spanish meeting)"],"requires":["Meeting audio in supported language (Japanese, Spanish, or others — unknown)","tl;dv account with multi-language support enabled (may be paid tier only)"],"input_types":["meeting audio in supported language"],"output_types":["transcript in source language (text with timestamps and speaker attribution)","summary in source language (text, customizable format)","action items in source language (structured list)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tl-dv__headline","uri":"capability://automation.workflow.ai.meeting.recorder.and.transcription.tool","name":"ai meeting recorder and transcription tool","description":"tl;dv is an AI-powered meeting recorder that captures video calls from Zoom and Google Meet, providing timestamped transcripts, AI summaries, and shareable clips, making meeting documentation effortless.","intents":["best AI meeting recorder","AI transcription tool for video calls","automated meeting summaries for teams","AI meeting insights for CRM integration","top tools for recording Zoom meetings"],"best_for":["sales teams","project managers","remote teams"],"limitations":["limited to Zoom and Google Meet"],"requires":[],"input_types":["video calls"],"output_types":["transcripts","summaries","video clips"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":54,"verified":false,"data_access_risk":"high","permissions":["Active Zoom, Google Meet, or Teams account","Browser extension installed (Chrome/Edge/Safari/Firefox — specific versions unknown)","tl;dv account (free tier available)","Sufficient local storage for buffering audio/video during call","Completed meeting recording from tl;dv capture","Audio quality sufficient for speech recognition (background noise tolerance unknown)","Meeting language must be supported (Japanese, Spanish confirmed; others unknown)","tl;dv account (free signup)","Zoom, Google Meet, or Teams account","Browser extension installation"],"failure_modes":["Capture mechanism is undisclosed — unclear if it uses WebRTC interception, native API hooks, or browser extension content scripts","No real-time transcription mentioned; processing appears post-meeting only","Requires browser extension or app installation on user's device; cannot capture from shared/borrowed devices without setup","Recording consent and legal compliance (one-party vs two-party consent) are user's responsibility — product does not enforce or guide this","Transcription engine provider is unknown — could be proprietary, OpenAI Whisper, Google Speech-to-Text, or other; affects accuracy and language support","Multi-language support only explicitly confirmed for Japanese and Spanish; other languages unknown","Transcription accuracy metrics not published; no SLA provided","Speaker diarization mechanism unknown — may fail with multiple speakers, overlapping speech, or accents","No real-time transcription; appears to be post-meeting batch processing only","Handling of long meetings (2+ hours) unknown — may truncate, summarize, or chunk transcripts","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:28.696Z","last_scraped_at":null,"last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=tl-dv","compare_url":"https://unfragile.ai/compare?artifact=tl-dv"}},"signature":"jPOalV3AW1myisTxHsdJjhnLXHTgDWJLAWrWI9HIZwbHyz3AidNyCysuMzMLdfUn2X5vu+Kskzy8Rwnj0kYnAw==","signedAt":"2026-06-22T04:11:56.057Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/tl-dv","artifact":"https://unfragile.ai/tl-dv","verify":"https://unfragile.ai/api/v1/verify?slug=tl-dv","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}