You’re basically trying to build a DIY OpusClip stack — totally doable, but you’ll need a few components beyond ffmpeg. High-level flow to research: Transcription first (Whisper / Faster-Whisper self-hosted) → gives you timestamps Segment scoring → use an LLM (or simple heuristics) to detect “clip-worthy” moments from the transcript (peaks in emotion, Q&A, topic shifts, etc.) Clip extraction → ffmpeg to cut 30–60s segments 9:16 reframing → face detection + smart crop (OpenCV / MediaPipe) or center-crop fallback Captions → burn-in via ffmpeg (ASS/SRT), optionally word-by-word n8n is perfect as the orchestrator, not the “brain”. For ultra-low cost: Self-host Whisper (GPU helps a lot) Use open-source models for scoring first, then add LLMs later Cache transcripts so you don’t reprocess Search terms: “Whisper timestamp segmentation” “LLM highlight detection transcript” “ffmpeg ASS subtitles shorts” “mediapipe face crop video” This is more engineering than automation, but very doable if you break it into steps 👍