An algorithm that scans a long-form video and predicts which short segments are most likely to perform as standalone shorts.
Last verified · 2026-05-29 · by Moe Ameen
Viral clip detection analyzes a source video (podcast, webinar, long-form YouTube) and scores segments on signals like speaker energy, topic novelty, quotable lines, question-answer structure, and audience engagement cues. The output is a ranked list of 30–90 second clip candidates.
OpusClip is the specialist category leader with two years of training data on what clips perform. Kompozy includes viral clip detection as one primitive inside a five-bucket fan-out, alongside text, image, blog, and newsletter generation from the same source.
Viral clip detection is an algorithm that scans a long-form video and predicts which short segments are most likely to perform as standalone shorts. The output is a ranked list of 30 to 90 second clip candidates.
It scores segments on signals like speaker energy, topic novelty, quotable lines, question-answer structure, and audience engagement cues. These signals combine into a ranking of candidate clips.
It analyzes long-form sources such as podcasts, webinars, and long-form YouTube videos, then identifies the strongest short segments within them.
OpusClip is the specialist category leader with two years of training data on what clips perform. Kompozy includes viral clip detection as one primitive inside a five-bucket fan-out, alongside text, image, blog, and newsletter generation from the same source.