{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_a-v-mapping","slug":"a-v-mapping","name":"A.V. Mapping","type":"product","url":"https://avmapping.co","page_url":"https://unfragile.ai/a-v-mapping","categories":["voice-audio"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_a-v-mapping__cap_0","uri":"capability://data.processing.analysis.ai.driven.audio.to.video.temporal.alignment","name":"ai-driven audio-to-video temporal alignment","description":"Automatically synchronizes audio tracks to video content by analyzing temporal features in both modalities using deep learning models that detect onset patterns, speech phonemes, and rhythmic structures. The system likely employs cross-modal embeddings or attention mechanisms to identify corresponding time points between audio and video streams, then applies dynamic time warping or frame-level adjustment to achieve frame-accurate sync without manual keyframe placement.","intents":["I need to sync a music track to a pre-recorded video without manually adjusting timeline markers","I want to automatically align dialogue audio with lip movements in video footage","I need to synchronize multiple audio stems (vocals, instruments, effects) to a single video timeline"],"best_for":["Independent musicians producing music videos with single-track audio","Podcast producers syncing intro/outro music to video intros","Content creators working with straightforward linear video projects without complex multi-track requirements"],"limitations":["Accuracy likely degrades on complex multi-track scenarios with overlapping audio sources","No documented support for live performance videos with variable tempo or timing drift","Freemium tier probably restricts output to standard resolutions (likely 1080p or lower) and common codecs","Sync precision not publicly benchmarked — unknown whether it achieves frame-level accuracy or operates at 100ms granularity"],"requires":["Video file in common format (MP4, MOV, WebM)","Audio file in standard format (MP3, WAV, AAC)","Internet connection for cloud-based model inference","Active A.V. Mapping account (freemium or paid tier)"],"input_types":["video (MP4, MOV, WebM, AVI)","audio (MP3, WAV, AAC, FLAC)"],"output_types":["synchronized video file (MP4, MOV)","timeline metadata (likely JSON or proprietary format with sync points)"],"categories":["data-processing-analysis","audio-video-synchronization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_1","uri":"capability://automation.workflow.batch.audio.video.synchronization.with.project.management","name":"batch audio-video synchronization with project management","description":"Processes multiple video-audio pairs in sequence or parallel, managing project state, tracking sync results per file, and organizing outputs into exportable collections. The system maintains a project workspace where users can upload multiple assets, queue sync jobs, monitor processing status, and retrieve synchronized outputs — likely using a job queue (Redis, RabbitMQ, or similar) to distribute inference across backend workers and a database to persist project metadata and sync parameters.","intents":["I need to sync 20 music videos in one batch without uploading and processing each individually","I want to organize multiple sync projects and revisit previous results without re-processing","I need to apply consistent sync settings across a series of related videos (e.g., all songs from an album)"],"best_for":["Music producers releasing multiple music videos in a campaign","Podcast networks syncing audio to video across dozens of episodes","Content creators managing recurring video production workflows"],"limitations":["Freemium tier likely caps batch size (e.g., max 5-10 files per batch) or imposes daily processing limits","No documented support for conditional sync logic (e.g., different sync strategies for different video types)","Project storage duration on freemium tier unknown — may auto-delete projects after 30 days","Parallel processing may be restricted to paid tiers; freemium may queue jobs sequentially"],"requires":["A.V. Mapping account with project creation permissions","Multiple video and audio files (format requirements as above)","Sufficient storage quota for project workspace (freemium limit unknown)"],"input_types":["video files (batch upload, 2-50 files)","audio files (batch upload, 2-50 files)","project configuration (sync parameters, output preferences)"],"output_types":["synchronized video files (batch download as ZIP or individual files)","project report (CSV or JSON with sync status per file)","project metadata (saved for future reference and re-processing)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_2","uri":"capability://data.processing.analysis.adaptive.sync.parameter.tuning.based.on.content.type","name":"adaptive sync parameter tuning based on content type","description":"Analyzes video and audio characteristics (genre, tempo, speech vs. music, visual motion intensity) and automatically adjusts sync algorithm parameters (e.g., onset detection sensitivity, time-warping aggressiveness, phonetic alignment weight) to optimize for the specific content type. The system likely classifies input content using audio/video feature extractors, then selects or interpolates pre-trained model weights or hyperparameters tuned for that category.","intents":["I want the sync algorithm to handle music videos differently than dialogue-heavy podcast intros","I need sync to work well for both fast-paced EDM and slow acoustic songs without manual tuning","I want the system to automatically detect if my video is live performance, animated, or studio footage and adjust accordingly"],"best_for":["Creators working across diverse content types (music, podcasts, tutorials) who need one-click sync without parameter tweaking","Teams producing content in multiple genres that require different sync sensitivities"],"limitations":["Content classification likely limited to broad categories (music/speech/mixed) — no fine-grained genre detection","Unknown whether parameter tuning is rule-based or learned from training data; may not generalize to niche content types","No user control over parameter adjustment — fully automated, which may be suboptimal for edge cases","Freemium tier may disable adaptive tuning and force default parameters"],"requires":["Video and audio files with sufficient duration (likely 10+ seconds) for reliable feature extraction","A.V. Mapping account (may be paid-tier feature)"],"input_types":["video file (any supported format)","audio file (any supported format)"],"output_types":["synchronized video with applied parameter settings","metadata indicating detected content type and selected parameters (if exposed to user)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_3","uri":"capability://automation.workflow.real.time.sync.preview.and.iterative.refinement","name":"real-time sync preview and iterative refinement","description":"Provides in-browser or desktop preview of synchronized audio-video output with frame-accurate scrubbing, allowing users to inspect sync quality before export. The system likely streams video frames and audio samples in sync, enabling users to jump to any timestamp and visually verify alignment. May support iterative refinement by allowing users to mark sync errors and re-run alignment on specific segments or with adjusted parameters.","intents":["I want to preview the sync result before downloading a large video file","I need to spot-check sync quality at specific moments (e.g., chorus, dialogue) without exporting","I want to fix sync errors in a specific segment without re-processing the entire video"],"best_for":["Creators who want to validate sync quality before committing to export","Producers working with tight deadlines who need rapid iteration on sync results","Users with limited bandwidth who want to preview before downloading large files"],"limitations":["Preview quality likely lower than export quality (compressed video, reduced frame rate) to minimize latency","Segment-level refinement may not be supported on freemium tier","Real-time preview requires low-latency streaming infrastructure — may be unavailable in regions with poor connectivity","No documented support for A/B comparison of different sync parameters"],"requires":["Modern web browser (Chrome, Firefox, Safari, Edge) or desktop app","Stable internet connection (likely 5+ Mbps for smooth preview)","A.V. Mapping account with active project"],"input_types":["synchronized video-audio pair (from prior sync operation)"],"output_types":["real-time video-audio stream (preview only, not exportable)","sync quality metrics (if exposed — e.g., confidence score, detected sync points)"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_4","uri":"capability://automation.workflow.multi.format.export.with.codec.and.resolution.options","name":"multi-format export with codec and resolution options","description":"Exports synchronized video in multiple formats, codecs, and resolutions, allowing users to optimize for different platforms (YouTube, TikTok, Instagram, web) or archival. The system likely wraps FFmpeg or similar transcoding libraries with preset configurations for common platforms, enabling one-click export without codec knowledge. May support batch export to multiple formats simultaneously.","intents":["I need to export my synced video as MP4 for YouTube and WebM for web simultaneously","I want to export at 4K for archival but also create a 1080p version for social media","I need to export with specific codec settings (H.264, VP9, AV1) for compatibility with different platforms"],"best_for":["Content creators distributing to multiple platforms with different technical requirements","Producers needing both high-quality archival and optimized social media versions","Teams managing video libraries with diverse playback environments"],"limitations":["Freemium tier likely restricted to single format/resolution per export (e.g., 1080p MP4 only)","Advanced codec options (AV1, VP9) may be paid-tier features","Export time scales with output resolution and codec complexity — 4K exports may take 30+ minutes","No documented support for custom FFmpeg parameters or advanced transcoding options"],"requires":["Synchronized video-audio pair from prior sync operation","Sufficient storage quota for export (freemium limit unknown)","A.V. Mapping account"],"input_types":["synchronized video-audio pair (internal format)"],"output_types":["video file (MP4, MOV, WebM, AVI, MKV — format depends on tier and selection)","multiple formats simultaneously (if batch export supported)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_5","uri":"capability://image.visual.lip.sync.detection.and.phonetic.alignment","name":"lip-sync detection and phonetic alignment","description":"Analyzes video frames to detect mouth movements and lip positions, then aligns audio phonemes to corresponding video frames to ensure dialogue or singing matches visual lip movements. The system likely uses face detection (e.g., MediaPipe, dlib) to locate lips, extracts mouth shape features (e.g., openness, position), and correlates these with audio phoneme sequences from speech recognition models. Applies frame-level adjustments to achieve phonetic alignment without global time-stretching.","intents":["I need to sync dialogue audio to video with precise lip-sync accuracy","I want to ensure singing vocals align with visible mouth movements in music videos","I need to fix lip-sync drift in multi-take or edited video footage"],"best_for":["Music video producers requiring frame-accurate vocal sync","Podcast/video creators with dialogue-heavy content","Filmmakers working with dubbed or re-recorded dialogue"],"limitations":["Lip-sync detection fails on videos with obscured faces (masks, angles, low resolution, poor lighting)","Phonetic alignment assumes clear speech — may fail on heavily accented, mumbled, or heavily processed audio","No support for non-English languages (likely English-only speech recognition)","Lip-sync refinement may be paid-tier feature; freemium may disable this capability","Frame-level adjustment may introduce audio artifacts (pitch shift, time-stretching artifacts) if applied aggressively"],"requires":["Video with visible face and mouth (resolution 720p+ recommended)","Clear audio with intelligible speech or singing","A.V. Mapping account (likely paid tier)"],"input_types":["video file (with visible face)","audio file (speech or singing)"],"output_types":["synchronized video with frame-level phonetic alignment","lip-sync confidence metrics (if exposed)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_6","uri":"capability://data.processing.analysis.automatic.audio.level.normalization.and.ducking","name":"automatic audio level normalization and ducking","description":"Analyzes audio dynamics and automatically adjusts levels to ensure consistent loudness across the synchronized track, and applies ducking (volume reduction) to background music or ambient sound when dialogue or primary audio is present. The system likely uses loudness metering (LUFS), peak detection, and audio segmentation to identify foreground vs. background content, then applies dynamic range compression and gain adjustments to achieve broadcast-standard loudness levels.","intents":["I want the synced audio to have consistent loudness without manual mixing","I need background music to automatically lower when dialogue is present","I want to ensure my video meets platform loudness standards (YouTube, Spotify, etc.) without manual mastering"],"best_for":["Solo creators without audio engineering expertise","Podcast producers needing quick audio normalization","Music video creators wanting professional-sounding audio without mixing"],"limitations":["Automatic ducking may fail on complex multi-track scenarios with overlapping dialogue and music","Loudness normalization assumes standard content types (speech, music) — may not work well for experimental or heavily processed audio","No user control over ducking threshold, compression ratio, or makeup gain — fully automated","May introduce audio artifacts (pumping, distortion) if applied too aggressively","Likely freemium-tier feature with limited customization"],"requires":["Audio file with clear foreground and background content (for ducking to be effective)","A.V. Mapping account"],"input_types":["synchronized audio track (from prior sync operation)"],"output_types":["normalized and ducked audio file (WAV, MP3, AAC)","loudness metrics (LUFS, peak level — if exposed)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_7","uri":"capability://tool.use.integration.cloud.based.inference.with.local.caching.and.offline.fallback","name":"cloud-based inference with local caching and offline fallback","description":"Performs AI model inference on cloud servers to leverage GPU acceleration and large pre-trained models, while caching results locally to avoid redundant processing and enabling offline access to previously synced projects. The system likely uses a hybrid architecture: cloud inference for new sync jobs, local SQLite or similar database for project metadata and cached results, and optional offline mode for preview/export of cached projects.","intents":["I want fast sync processing without running heavy ML models locally on my machine","I need to access my synced projects offline without re-downloading from the cloud","I want to avoid re-processing the same video-audio pair if I've already synced it before"],"best_for":["Solo creators with limited local GPU resources","Teams working in environments with intermittent internet connectivity","Users wanting to minimize local storage and computational overhead"],"limitations":["Cloud inference introduces network latency (likely 30-120 seconds per sync job) compared to local processing","Offline mode limited to cached projects — new syncs require internet connection","Cache storage on device likely limited (freemium may cap at 1-5 GB)","Privacy concern: audio and video uploaded to cloud servers for processing (no documented encryption or deletion policy)","Sync quality depends on cloud model versions — updates may change results for same input"],"requires":["Internet connection for initial sync (cloud inference)","A.V. Mapping account with cloud storage quota","Local storage for project cache (1-5 GB recommended)"],"input_types":["video and audio files (uploaded to cloud for inference)"],"output_types":["synchronized video (downloaded from cloud or retrieved from local cache)","project metadata (stored locally for offline access)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_a-v-mapping__cap_8","uri":"capability://automation.workflow.freemium.tier.with.usage.based.quotas.and.upgrade.paths","name":"freemium tier with usage-based quotas and upgrade paths","description":"Offers free access to core sync functionality with limitations on processing time, output resolution, project storage, or export formats, while paid tiers unlock premium features (higher resolution, batch processing, advanced refinement). The system likely tracks usage metrics (minutes of video processed, projects created, storage used) and enforces soft limits (slower processing, watermarks) or hard limits (export blocked) when quotas are exceeded.","intents":["I want to test A.V. Mapping on a single music video before committing to a paid plan","I need occasional sync capability without paying for a full subscription","I want to upgrade to paid features only when my usage justifies the cost"],"best_for":["Solo creators and hobbyists with occasional sync needs","Teams evaluating A.V. Mapping before enterprise adoption","Users wanting low-risk entry point to audiovisual automation"],"limitations":["Freemium tier likely caps output to 1080p or lower, limiting professional use","Processing speed on freemium may be throttled (e.g., queued behind paid users)","Batch processing, advanced refinement, and lip-sync features likely paid-only","Project storage duration on freemium unknown — may auto-delete after 30-90 days","Watermarks or branding may be applied to freemium exports","No documented upgrade path or pricing transparency — users may not know cost before committing"],"requires":["A.V. Mapping account (free signup)","Video and audio files within freemium size/duration limits (unknown)"],"input_types":["video and audio files (within freemium quotas)"],"output_types":["synchronized video (limited resolution/format on freemium)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Video file in common format (MP4, MOV, WebM)","Audio file in standard format (MP3, WAV, AAC)","Internet connection for cloud-based model inference","Active A.V. Mapping account (freemium or paid tier)","A.V. Mapping account with project creation permissions","Multiple video and audio files (format requirements as above)","Sufficient storage quota for project workspace (freemium limit unknown)","Video and audio files with sufficient duration (likely 10+ seconds) for reliable feature extraction","A.V. Mapping account (may be paid-tier feature)","Modern web browser (Chrome, Firefox, Safari, Edge) or desktop app"],"failure_modes":["Accuracy likely degrades on complex multi-track scenarios with overlapping audio sources","No documented support for live performance videos with variable tempo or timing drift","Freemium tier probably restricts output to standard resolutions (likely 1080p or lower) and common codecs","Sync precision not publicly benchmarked — unknown whether it achieves frame-level accuracy or operates at 100ms granularity","Freemium tier likely caps batch size (e.g., max 5-10 files per batch) or imposes daily processing limits","No documented support for conditional sync logic (e.g., different sync strategies for different video types)","Project storage duration on freemium tier unknown — may auto-delete projects after 30 days","Parallel processing may be restricted to paid tiers; freemium may queue jobs sequentially","Content classification likely limited to broad categories (music/speech/mixed) — no fine-grained genre detection","Unknown whether parameter tuning is rule-based or learned from training data; may not generalize to niche content types","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"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":"2026-04-05T13:23:42.562Z","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=a-v-mapping","compare_url":"https://unfragile.ai/compare?artifact=a-v-mapping"}},"signature":"Wp6qtpKDtOml5PpnUriv1EQ+DGRDHv+Qki8a5eSOMDROOFU8GLrcWGOMFVTLK7YkK68sivAYjlTzs2+I+krLAQ==","signedAt":"2026-06-22T03:50:28.035Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/a-v-mapping","artifact":"https://unfragile.ai/a-v-mapping","verify":"https://unfragile.ai/api/v1/verify?slug=a-v-mapping","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"}}