Long Video to Short Clips Converter with AI - OpenClip
Long to Short

Turn Long Videos Into Short Clips Automatically

Every long video — podcast, stream, lecture, keynote, vlog — contains a handful of moments built for short-form. OpenClip finds them with AI, reframes them vertical with face tracking, captions every word, and hands you a ranked clip set from a single upload.

content-repurposing
starter

Scenario

The gap between long-form and short-form isn't just duration — it's economics. Long videos earn depth: subscribers, watch time, trust. Short clips earn reach: TikTok, Reels, and Shorts distribute to people who've never heard of you. Creators who feed both compound; creators who only make long-form stay invisible to the feeds where audiences are actually built. The conversion bottleneck is always the same three jobs: finding the moments (an hour of footage, maybe four postable segments), reframing (16:9 to 9:16 without decapitating anyone), and captioning (word-timed, styled, burned in). Done manually that's an hour or more per clip; done badly it's worse than not posting. OpenClip runs all three jobs from one upload of any long video — it transcribes, scores every segment for hook and payoff, tracks faces through the vertical reframe, and exports captioned clips ranked by predicted performance. Source length is the input, not the obstacle.

Workflow

1

Upload any long video

Podcast episode, livestream VOD, lecture, keynote, tutorial, vlog — paste a URL or upload the file. Ten minutes or four hours, the pipeline is identical.

2

AI transcribes and scores everything

The full transcript is analyzed segment by segment for hook strength, emotional spikes, self-containedness, and payoff — the properties that separate a clip from a random excerpt.

3

Review a ranked clip shortlist

Instead of a timeline, you get 5-15 candidates ranked by clip potential, each with clean in and out points cut on natural speech boundaries.

4

Vertical reframe with face tracking

Every clip converts from its source aspect to 9:16 with faces tracked and framed — single speakers, two-shots, and moving subjects all handled without manual keyframing.

5

Export captioned clips for every platform

Word-level captions burn in with your chosen preset, and the finished clips work across TikTok, Reels, and Shorts — one long video in, a multi-platform posting batch out.

Benefits

One long video becomes 5-15 short clips without timeline editing
AI ranking finds the moments — no more scrubbing footage at 2x
Clips cut on natural speech boundaries, opening on the hook line
Face-tracked 9:16 conversion works for any source aspect ratio
Word-level burned-in captions serve every sound-off feed
The same clip set distributes to TikTok, Reels, and Shorts simultaneously

Key Metrics

5-15

Clips per video

Minutes to hours

Source length handled

~1 hr

Manual time per clip replaced

TikTok, Reels, Shorts

Destination platforms

Features

Viral Moment Detection

Every segment of the transcript is scored for hook, emotion, and payoff — the AI reads the whole video so you review a shortlist instead of a timeline.

Any-Aspect Vertical Conversion

16:9, 4:3, or ultrawide sources reframe to 9:16 with faces tracked and centered — no static crops, no manual keyframes.

Word-Level Captions, 10 Presets

Captions sync to each spoken word and burn into the export, styled from clean-minimal to bold-viral to match your brand.

Length-Agnostic Processing

A 3-hour VOD processes as easily as a 10-minute tutorial — longer sources simply yield a deeper pool of ranked moments.

Multi-Speaker Intelligence

Speaker diarization plus face tracking handles conversations, panels, and interviews — framing follows whoever is talking.

One Upload, Every Platform

The exported clip set is format-correct for TikTok, Instagram Reels, and YouTube Shorts at once — repurposing without re-rendering.

Frequently Asked Questions

Upload the video (or paste its URL) to OpenClip. The AI transcribes it, scores every segment for clip potential, and returns 5-15 ranked candidates already cropped to 9:16 with face tracking and captioned at word level. The three manual jobs — finding moments, reframing, captioning — happen in one automated pass, leaving you a review-and-post step.

It depends on the destination: TikTok's completion sweet spot is roughly 21-34 seconds, Reels favors 15-60 seconds within its 3-minute cap, and YouTube Shorts allows up to 3 minutes — where 60-120 second story clips can work. The shared principle is completeness: a clip should open on a hook and end on a payoff, whatever its length. OpenClip cuts on those boundaries automatically.

It reads the transcript the way a clip editor would: looking for strong opening lines, emotional or informational spikes, and segments that make sense with zero surrounding context. Each segment gets a composite score and the highest-ranked become your candidates. The full methodology is covered in auto-detecting viral moments.

Yes — that's the core of the reframe. Face tracking follows subjects through the shot and positions the 9:16 window around them dynamically, cutting between speakers in multi-person footage. Static center-cropping, the approach that beheads subjects, is exactly what this replaces. Background on the formats in understanding aspect ratios.

Spoken-word content clips best: podcasts, interviews, webinars, lectures, streams, commentary, keynotes. The detection engine is transcript-driven, so videos where the value is verbal give it the most signal. Purely visual content — b-roll montages, music videos — has less for the AI to score. For specific formats, see podcast to Shorts or livestream to clips.

OpenClip is built for long sources — multi-hour podcast episodes and stream VODs are routine inputs. Processing is credit-based on source minutes, so a longer video uses more credits but doesn't require different handling. Practically, the longer the source, the more the automated detection saves you versus manual scrubbing.

Stop Sitting on Hours of Footage Worth Fifteen Clips

Upload any long video to OpenClip and get back a ranked set of vertical, captioned short clips — found, framed, and finished by AI.

Related Pages