Viral Moment Analyzer
An experimental AI system that analyzes long-form video and attempts to identify moments with high viral potential.
- Year
- 2025
Stack
- AI
- Video Processing
- LLMs
- Computer Vision
- Analytics
01
Overview
An experiment in whether "this part is interesting" can be modelled from a long video's own signals.
02
Problem
Finding the good 40 seconds inside a two-hour recording is slow, subjective work.
03
Idea
Combine what is said, how it is said and what is shown into a single moment score.
04
Architecture
Extract transcript, audio energy, scene changes and visual salience, fuse the features, then have an LLM pass judge narrative payoff.
05
Design
A timeline with a score curve. You scrub the peaks instead of the whole video.
06
Development
Processing is chunked and cached per signal so re-scoring never re-decodes the video.
07
AI / Technical Challenges
Transcript-only scoring rewarded loud nonsense. Adding energy and scene-change features, then requiring an explanation from the model, made rankings defensible.
08
Results
Suggested clips consistently overlapped with the moments a human editor picked.
09
What I learned
Multimodal problems are mostly data-plumbing problems.
10
Next steps
Automatic vertical reframing and per-audience scoring profiles.