Filler Word Removal
Automatically removing “um,” “uh,” “like” and other verbal fillers to make a clip sound crisper.
Filler-word removal strips the ums, uhs, you-knows and likes that clutter natural speech. Cutting them makes a speaker sound more confident and a clip feel more polished, and it usually shortens the runtime too.
AI editors flag each filler on the transcript so you can remove them in bulk instead of hunting frame by frame.
Keep reading.
Silence Removal
Automatically detecting and cutting silent gaps and pauses from a recording to tighten pacing.
Read →Transcript-Based Editing
Editing video by editing its text transcript — delete a sentence and the matching footage is removed.
Read →Captions
On-screen text of a video's spoken words, keeping viewers engaged when they watch with sound off.
Read →A-roll
The primary footage in a video — the main subject or speaker — that carries the core narrative.
Read →Stop reading, start posting.
Turn a long video into ranked, captioned clips — free to start.
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