{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_glossai","slug":"glossai","name":"Glossai","type":"product","url":"https://glossai.co","page_url":"https://unfragile.ai/glossai","categories":["video-generation"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_glossai__cap_0","uri":"capability://data.processing.analysis.automatic.video.to.transcript.conversion","name":"automatic-video-to-transcript-conversion","description":"Converts long-form video content into searchable text transcripts using speech-to-text processing. The system likely employs a multi-stage pipeline: video ingestion → audio extraction → speech recognition (possibly via third-party APIs like Whisper or similar) → timestamp-aligned transcript generation. This enables downstream keyword matching and clip detection by creating a queryable text representation of video content with temporal markers.","intents":["I need to extract spoken content from a 2-hour podcast to find quotable moments","I want to search for specific keywords within my video to identify relevant segments","I need a full transcript of my webinar for accessibility and SEO purposes"],"best_for":["podcasters and streamers with high-volume content libraries","course creators needing to repurpose lecture material","content teams managing multiple long-form video sources"],"limitations":["Transcription accuracy depends on audio quality; background noise and overlapping speakers degrade precision","No speaker diarization mentioned — cannot distinguish between multiple speakers in output","Timestamp alignment may drift for videos with variable playback speed or complex audio mixing"],"requires":["Video file in common format (MP4, MOV, WebM, etc.)","Audio track with sufficient clarity for speech recognition","Internet connectivity for cloud-based transcription processing"],"input_types":["video files","audio streams"],"output_types":["text transcripts","timestamped text with temporal markers"],"categories":["data-processing-analysis","video-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_1","uri":"capability://data.processing.analysis.keyword.driven.highlight.clip.extraction","name":"keyword-driven-highlight-clip-extraction","description":"Analyzes transcripts to identify and automatically extract video segments containing user-specified or AI-detected keywords and phrases. The system uses keyword matching (likely regex or token-based search) against the timestamped transcript to locate relevant moments, then extracts the corresponding video segments with configurable padding (pre/post-roll duration). This approach prioritizes semantic relevance over visual composition, making it efficient for repurposing educational or interview content but potentially missing emotional or narrative beats.","intents":["I want to automatically pull all clips where my guest mentions our product name","Extract 15-30 second segments around key talking points from a 90-minute interview","Find and cut all moments where the speaker says 'actionable insight' or similar phrases"],"best_for":["content teams with structured, keyword-rich content (interviews, webinars, tutorials)","creators who can define clear keyword targets upfront","use cases where semantic relevance matters more than visual storytelling"],"limitations":["Misses context-dependent highlights — a powerful moment with no keyword match gets skipped","No emotional or narrative flow detection — may extract technically relevant but boring segments","Keyword false positives can create clips around incidental mentions rather than substantive discussion","Requires manual keyword definition or relies on generic AI detection that may not match creator intent"],"requires":["Completed transcript with timestamps","Keyword list (user-provided or system-generated)","Original video file for segment extraction"],"input_types":["timestamped transcripts","keyword lists","video files"],"output_types":["video clip segments with start/end timecodes","clip metadata (duration, keywords matched)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_2","uri":"capability://image.visual.platform.specific.video.formatting.and.optimization","name":"platform-specific-video-formatting-and-optimization","description":"Automatically reformats extracted clips to match platform-specific technical requirements and best practices. The system applies transformations including: aspect ratio adjustment (16:9 → 9:16 for TikTok/Reels, 1:1 for Instagram), resolution scaling, frame rate normalization, and safe-zone padding for text overlays. This is likely implemented via FFmpeg or similar video codec libraries with preset profiles for each platform, ensuring clips are immediately uploadable without manual adjustment.","intents":["I need to export clips optimized for TikTok, Instagram Reels, and YouTube Shorts simultaneously","Automatically crop my landscape interview footage to vertical format for mobile platforms","Ensure all clips meet platform specifications without manual resizing in post-production"],"best_for":["multi-platform content distributors managing clips across 3+ social channels","solo creators without video editing expertise","teams prioritizing speed over creative customization"],"limitations":["Fixed formatting rules — no custom aspect ratios or creative framing options","Automatic cropping may cut off important visual elements (faces, text) if not carefully configured","No support for platform-specific features like TikTok transitions, Instagram Reels effects, or YouTube Shorts cards","Limited to standard platform specs; cannot optimize for emerging formats or niche platforms"],"requires":["Extracted video clip","Target platform specification (TikTok, Instagram, YouTube, etc.)","Video codec support (H.264, VP9, etc.)"],"input_types":["video clips in various aspect ratios and resolutions"],"output_types":["platform-optimized video files","multiple format variants (one per platform)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_3","uri":"capability://automation.workflow.batch.video.processing.pipeline","name":"batch-video-processing-pipeline","description":"Orchestrates end-to-end processing of multiple videos in sequence or parallel, managing the workflow from upload through transcription, clip extraction, formatting, and export. The system likely implements a job queue (possibly using task workers like Celery or similar) that handles asynchronous processing, allowing users to upload multiple videos and receive processed clips without blocking. Progress tracking and error handling ensure visibility into multi-video batches.","intents":["I have 10 podcast episodes to process this week — I need to upload them all and get clips back automatically","Process a month's worth of stream VODs in the background while I work on other projects","Batch-convert all my webinar recordings to social clips in one workflow"],"best_for":["content teams with high-volume production (10+ videos/week)","creators who want to set-and-forget processing","organizations managing content libraries across multiple creators"],"limitations":["Processing time scales with video count and duration — no guaranteed SLA for completion","Batch processing may queue behind other users' jobs, causing unpredictable delays","No granular control over processing priority or resource allocation per video","Failed jobs in a batch may require manual retry or intervention"],"requires":["Multiple video files (format: MP4, MOV, WebM, etc.)","User account with sufficient storage quota","Internet connectivity for upload and processing"],"input_types":["multiple video files","batch configuration (keywords, platforms, output formats)"],"output_types":["processed clip sets","batch processing status/logs"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_4","uri":"capability://planning.reasoning.ai.powered.clip.highlight.detection","name":"ai-powered-clip-highlight-detection","description":"Uses machine learning to identify potentially interesting or engaging moments within video content beyond simple keyword matching. The system likely analyzes transcript sentiment, topic shifts, speaker emphasis (inferred from transcript patterns), and engagement signals to score segments and rank them by predicted interest. This may involve embeddings-based similarity matching or rule-based heuristics applied to transcript features, generating a ranked list of candidate clips for extraction.","intents":["I want the AI to automatically find the most engaging 30-second moments from my 2-hour interview without specifying keywords","Identify moments where the speaker's tone or emphasis suggests they're making an important point","Get AI-suggested clips ranked by predicted engagement for my audience"],"best_for":["creators who don't want to manually define keywords upfront","content with strong narrative or emotional arcs (interviews, storytelling, debates)","teams wanting AI-assisted editorial decisions"],"limitations":["AI detection often misses the 'best' moments that human editors intuitively select — prioritizes keywords over narrative flow","No personalization to creator's unique style or audience preferences","Struggles with sarcasm, irony, or context-dependent humor","Cannot detect visual moments (facial expressions, gestures) — relies only on transcript analysis","Ranking may be inconsistent across similar content types"],"requires":["Completed transcript with semantic content","ML model trained on engagement signals (may be proprietary)","Original video for segment extraction"],"input_types":["timestamped transcripts","video metadata (duration, topic, etc.)"],"output_types":["ranked list of candidate clip segments","engagement scores per segment"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_5","uri":"capability://automation.workflow.multi.format.clip.export.with.metadata","name":"multi-format-clip-export-with-metadata","description":"Exports processed clips in multiple formats and resolutions simultaneously, bundling each with metadata (title, description, keywords, timestamps, platform tags). The system generates platform-ready files (MP4, WebM, etc.) and optionally creates accompanying metadata files (JSON, CSV) or social media captions. This enables direct integration with scheduling tools or manual upload workflows, reducing post-processing friction.","intents":["Export clips as MP4 files ready to upload to TikTok, plus auto-generated captions","Get all clips with metadata (keywords, timestamps) in a structured format for import into my CMS","Download clips optimized for each platform plus a CSV with clip descriptions for bulk scheduling"],"best_for":["creators using external scheduling or CMS tools","teams needing structured metadata for content management","multi-platform distributors who want to automate upload workflows"],"limitations":["Metadata generation is basic — auto-generated captions lack creativity or brand voice","No direct integration with scheduling platforms (e.g., Buffer, Later) — requires manual import","Export formats are limited to standard video codecs; no support for platform-specific formats (e.g., TikTok's proprietary optimization)","Metadata accuracy depends on upstream clip detection quality"],"requires":["Processed video clips","Metadata source (transcript, keywords, user input)","Export format specification (MP4, WebM, etc.)"],"input_types":["processed video clips","clip metadata (keywords, timestamps, titles)"],"output_types":["video files in multiple formats","metadata files (JSON, CSV)","social media captions"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_6","uri":"capability://automation.workflow.customizable.clip.duration.and.padding.control","name":"customizable-clip-duration-and-padding-control","description":"Allows users to specify or adjust the duration of extracted clips and the amount of pre/post-roll padding around detected moments. Users can define target clip lengths (e.g., 15-30 seconds for TikTok, 60+ seconds for YouTube) and padding duration (e.g., 2 seconds before/after keyword match), which the system applies during extraction. This is implemented via simple temporal offset calculations on the transcript timestamps, enabling flexible clip sizing without re-processing.","intents":["I want all my TikTok clips to be exactly 15-30 seconds, but my YouTube clips can be 60 seconds","Add 3 seconds of context before and after each keyword match so clips don't feel abrupt","Extract variable-length clips based on the natural pause points in the transcript"],"best_for":["creators with platform-specific clip length requirements","teams wanting to standardize clip duration across content","use cases where context padding improves clip quality"],"limitations":["Padding is temporal only — cannot intelligently extend clips to natural sentence boundaries","No detection of optimal cut points (e.g., pauses, topic shifts) — uses fixed duration rules","Clips may be cut off mid-sentence if duration limits don't align with content structure","No preview of clips before extraction — users must adjust settings and re-process to see results"],"requires":["Extracted clip timecodes","Duration and padding parameters (in seconds)","Original video file"],"input_types":["clip timecodes","duration/padding configuration"],"output_types":["adjusted clip segments with new start/end times"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_glossai__cap_7","uri":"capability://image.visual.basic.caption.and.text.overlay.generation","name":"basic-caption-and-text-overlay-generation","description":"Automatically generates captions from the transcript and optionally overlays them on video clips. The system likely uses the transcript text directly, applies basic formatting (font, size, color), and positions captions in safe zones for each platform. This is a straightforward text-to-video overlay implementation, not a sophisticated caption editor — it generates generic captions without speaker identification, styling variation, or creative formatting.","intents":["Add auto-generated captions to all my clips for accessibility and engagement","Overlay the transcript text on video clips without manual caption editing","Generate captions that fit within safe zones for each platform"],"best_for":["creators prioritizing speed over caption quality","accessibility-focused teams needing basic captions","high-volume content production where manual caption editing is infeasible"],"limitations":["No speaker identification — captions don't distinguish between multiple speakers","Generic styling — no custom fonts, colors, animations, or creative formatting","No caption timing adjustment — relies on transcript timestamps which may not align perfectly with speech","No support for sound effects or music cues in captions","Caption accuracy depends entirely on transcript quality"],"requires":["Transcript with timestamps","Video clip","Caption styling parameters (optional)"],"input_types":["timestamped transcripts","video clips"],"output_types":["video files with embedded captions","SRT/VTT caption files"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"low","permissions":["Video file in common format (MP4, MOV, WebM, etc.)","Audio track with sufficient clarity for speech recognition","Internet connectivity for cloud-based transcription processing","Completed transcript with timestamps","Keyword list (user-provided or system-generated)","Original video file for segment extraction","Extracted video clip","Target platform specification (TikTok, Instagram, YouTube, etc.)","Video codec support (H.264, VP9, etc.)","Multiple video files (format: MP4, MOV, WebM, etc.)"],"failure_modes":["Transcription accuracy depends on audio quality; background noise and overlapping speakers degrade precision","No speaker diarization mentioned — cannot distinguish between multiple speakers in output","Timestamp alignment may drift for videos with variable playback speed or complex audio mixing","Misses context-dependent highlights — a powerful moment with no keyword match gets skipped","No emotional or narrative flow detection — may extract technically relevant but boring segments","Keyword false positives can create clips around incidental mentions rather than substantive discussion","Requires manual keyword definition or relies on generic AI detection that may not match creator intent","Fixed formatting rules — no custom aspect ratios or creative framing options","Automatic cropping may cut off important visual elements (faces, text) if not carefully configured","No support for platform-specific features like TikTok transitions, Instagram Reels effects, or YouTube Shorts cards","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3333333333333333,"quality":0.6900000000000001,"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":"2026-05-24T12:16:30.892Z","last_scraped_at":"2026-04-05T13:23:42.552Z","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=glossai","compare_url":"https://unfragile.ai/compare?artifact=glossai"}},"signature":"VgPROE6u6FqKndHNvzIiPOpXOdeJ0xKQ2ff8eSn0wrUqotX3sfzLOcK6V80xjvYSQyEdX++D22lFv1W4mRDLDA==","signedAt":"2026-06-20T21:19:46.671Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/glossai","artifact":"https://unfragile.ai/glossai","verify":"https://unfragile.ai/api/v1/verify?slug=glossai","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"}}