A music-video house run by one person
AuraFlow turns a single audio file into a narrative music video. Storyboard, scenes where the cast actually stays the same, lyrics that land on the syllable, thumbnails, all the way to scheduled YouTube publishing. One workflow, one app.
Every number on this page is counted from the running application.
Control every stage down to the detail. Or let go and let the engine decide. Both are valid.
Upload the song. The engine reads tempo, beats and dynamics, then suggests genre, mood and a visual direction. Vocals can be separated automatically on the server.
AI builds a real arc. Setup, conflict, resolution. With a suggested cast and locations. Take it as is, or rewrite every word.
Each scene becomes an image, then moves as a clip. Duration, camera move and shot size are decided per scene, not averaged across the video.
Cuts land on the beat. Camera motion, transitions, colour grade and effects are assembled into one video. With a technique report you can actually read.
Not quite right? A manual timeline: nudge, split at the playhead, duplicate, drag-trim, swap transitions. Full undo and redo.
Lyrics are forced-aligned to the audio, per word, not per line. Then burned into the video pixels.
Not a bag of separate tools. What one module learns, the next one uses.
Complete pipeline
A narrative music video from scratch: storyboard, scenes, cast, locations, production, right through to burned-in lyrics. Control down to each scene.
Zero AI cost
One song, one looping clip, one paste of lyrics. A synced lyric video. Rendered on our own machine, so it adds nothing to your generation bill.
Rendered locally
Thumbnails built to be clicked: automatic face focus, bold type that survives a small screen, correct size per platform.
Diagnosis, not a dashboard
It does more than show numbers. It names the problem, explains the cause, then offers a fix you can apply in one click and roll back just as fast.
Runs itself
Render, publish to YouTube and archive to Google Drive on a schedule. With a searchable archive catalogue by artist, channel or file type.
The parts where AI video generators usually fall apart are the parts with the most work behind them here.
Character consistency is defended in five layers: an identity lock from reference photos, multi-reference conditioning while drawing, a scene planner that knows who appears where, an asset bible that pins locations and props too, and face swapping as the final guard. Wardrobe is handled separately from identity, so a change of clothes is not a change of person.
Not "transcribe, then match". Your actual lyrics are forced onto the audio, producing per-WORD timing. Which is why the karaoke fill feels welded to the vocal instead of trailing half a second behind.
Video health scoring puts retention and watch time above everything else, because that is what actually moves reach.
Lessons from diagnosis and research are stored per channel, then read back by the generation engine on the next video. From title wording to cutting pace. The longer it runs, the sharper it gets.
Lyric videos, thumbnails, vocal separation and the entire assembly stage run on our own machine. AI cost appears only when a scene is genuinely drawn or animated. And every rupiah is logged per project.
These numbers are not decoration. Each one is a real choice inside the app.
Final render quality is decoupled from generation quality: the video can be rendered up to 1080p without adding a cent to the AI bill.
Not demo reels. These are live on our channels.
Each job goes to the tool that is genuinely strongest at it.
The app is equally honest about its limits: metrics the YouTube API does not expose are never guessed, and scores without data are marked empty rather than filled with invented numbers.
This application is used every day to produce and publish music videos. It is not a prototype.
Sign inAccess is private. Accounts are created manually by the operator; there is no self sign-up.
