Content Automate
A self-built Python automator powered by AI that turns hours of manual editing into a single command. It stitches tracks into music sets, montages full video sequences, removes watermarks, generates covers, and overlays one video on top of another.
From raw assets to a publishable video
Drop tracks, clips, and source videos into a folder. The automator analyses the material, makes the edit decisions with AI, runs FFmpeg under the hood, and writes out a finished video, audio set, and cover image — ready to upload.
- 01Ingest assets
- 02AI decisions
- 03FFmpeg pipeline
- 04Publish-ready output
Key Features
Each capability is a building block — together they replace the editor, audio mixer, and designer for solo creators.
Auto-stitched music sets
Feed it a folder of tracks and it produces a beat-aware, gapless music set — analysing tempo, key, and energy to choose smooth transitions between songs.
Automatic video montage
Generates full video sequences from raw clips — cuts on the beat, balances pacing, and assembles a finished montage without a manual timeline.
Watermark removal
Detects watermarks and logos with computer vision, then uses AI inpainting to clean them out frame-by-frame while preserving the underlying content.
AI-generated covers
Builds custom thumbnails and covers for every video — composes background art, overlays titles, and exports ready-to-publish images.
Picture-in-picture overlay
Overlays one video on top of another with configurable position, scaling, fade-ins, and transparency — perfect for reaction-style and dual-stream content.
AI-driven decisions
Uses LLMs and computer-vision models for the judgement calls — clip selection, transition choice, cover composition — so the output looks intentional, not templated.
Single-command pipeline
Everything runs from one CLI entry point. Drop the source assets, run the command, walk away — outputs land in a structured folder ready to publish.
Reusable processing modules
Built as composable Python modules so the same building blocks (audio analysis, FFmpeg ops, inpainting, cover generation) can power new content workflows.
Hours saved per video
Replaces the manual editor → audio mixer → designer loop with a self-serve toolchain — turning a multi-day workflow into a few minutes of compute.
Tech Stack
Python
Core language
FFmpeg
Video / audio processing engine
MoviePy
Programmatic video editing
OpenCV
Computer vision & watermark detection
AI / Inpainting
Watermark cleanup & cover generation
Pillow
Image composition for covers