Full AI Video Pipeline From Script to Published Video
N8N
Project's Category
Intro
This one turns a single Airtable record into a finished, published video with nobody touching an editor. It writes the script, breaks it into scenes, generates images and video for each scene, merges everything, adds audio, and publishes.
Problems
The client wanted to produce video content at a pace no single editor could keep up with, but stitching together separate AI tools for script, images, video, and audio by hand for every single video was actually slower than just editing it manually.
Solutions
We built a five stage n8n pipeline running off Airtable as the project tracker. Stage one writes and splits the script into scenes with an AI agent and saves it back to the record. Stage two generates an image for every scene, polling the generation API until each one comes back ready. Stage three turns each image into a short video clip the same way. Stage four collects all the clips once every scene is done and merges them into one video. Stage five adds audio and publishes the finished piece.
Final Thoughts
Splitting this into five separately scheduled stages instead of one long workflow was the right call. Each stage only picks up records once the previous one actually finished, so a slow image generation doesn't hold up scenes that were ready early.
Full AI Video Pipeline From Script to Published Video
N8N
Project's Category
Intro
This one turns a single Airtable record into a finished, published video with nobody touching an editor. It writes the script, breaks it into scenes, generates images and video for each scene, merges everything, adds audio, and publishes.
Problems
The client wanted to produce video content at a pace no single editor could keep up with, but stitching together separate AI tools for script, images, video, and audio by hand for every single video was actually slower than just editing it manually.
Solutions
We built a five stage n8n pipeline running off Airtable as the project tracker. Stage one writes and splits the script into scenes with an AI agent and saves it back to the record. Stage two generates an image for every scene, polling the generation API until each one comes back ready. Stage three turns each image into a short video clip the same way. Stage four collects all the clips once every scene is done and merges them into one video. Stage five adds audio and publishes the finished piece.
Final Thoughts
Splitting this into five separately scheduled stages instead of one long workflow was the right call. Each stage only picks up records once the previous one actually finished, so a slow image generation doesn't hold up scenes that were ready early.
Building the automation systems that handles business processes.
Clear Communication
Reliable
Professional
Reliable Quality
Building the automation systems that handles business processes.
Clear Communication
Reliable
Professional
Reliable Quality
