Charter Pro added done-for-you highlight videos to its app, used by fishing guides across the United States. An AI assistant shortlisted the platform, an AI agent wrote the integration, and Shotstack renders every video with no human in the loop.
At a glance
| Industry | Outdoor recreation and fishing charters |
| Use case | Automated highlight videos for fishing trip guests |
| Products used | Edit API |
| Output | Short highlight videos built from guest photos and clips |
| Integration | Fully automated, JSON-driven, built with an AI coding agent |
With Shotstack, Charter Pro:
Charter Pro builds software for fishing guides. Guides are experts on the water, not video editors. Their guests go home with a phone full of photos and a story worth sharing, and Charter Pro’s idea was to send every guest a finished highlight video of their trip.
Charter Pro runs lean. Its owner also leads another technology startup, so anything that required manual video work, or even much of his attention, was off the table. Early experiments ran on a browser-based editor driven programmatically, but it solved a different problem. The videos had to come from an API that his backend, or his AI agent, could drive end to end.
“When I did the research for a new video platform, I actually had AI do it. It brought me five options, and it identified that Shotstack was able to solve our needs.”
Owner, Charter Pro
The shortlist came from the assistant. The decision stayed human: a quick table of pros and cons, pricing, and speed across the five options, with one filter above all, whether a platform did a whole lot more than the job needed. Shotstack fit the job without the excess.
His first visit to the Shotstack website was also his last. He pasted a small JSON edit into the test console to check two things: how fast the render came back, and whether the JSON was human-readable. Both passed. Everything since has happened through the API.
The integration was written by an AI coding agent and working within a couple of days. The pipeline now runs itself:
Under the hood, every render is a single request to the Edit API. There is no saved template and no editor session. For each trip, the backend assembles a fresh edit: the AI-picked segment of the raw footage, the guide’s photos in sequence, and licensed music underneath. It describes all of that in one JSON document: which clips, in what order, with what timing and transitions. Then it sends the edit. Shotstack answers with a render ID, the backend checks in until the status comes back done, and the finished video lands on the guest’s recap page.
The ingredients change with every trip. The structure never does. That is the whole integration.
“AI did everything essentially. It was solved pretty quickly, and since then, we have just been using the product. These videos are made automatically for our users. I do not even really see them anymore.”
“Everything is super quick. Everything works, I would say, flawlessly.”
The evaluation criteria were fit and legibility, not feature count. A platform that did far more than the job would have counted against it. Shotstack matched the need exactly: a JSON-driven API a backend can call, readable enough that both the human and the AI agent writing the code could reason about it, at a price that made sense.
If your app collects photos and clips, you can build what Charter Pro built. Define the edit as JSON once, let your code (or your AI agent) fill it with each user’s content, and render through the API.
Get a free Shotstack API key and render your first video in minutes.
curl --request POST 'https://api.shotstack.io/v1/render' \
--header 'x-api-key: YOUR_API_KEY' \
--data-raw '{
"timeline": {
"tracks": [
{
"clips": [
{
"asset": {
"type": "video",
"src": "https://shotstack-assets.s3.amazonaws.com/footage/beach-overhead.mp4"
},
"start": 0,
"length": "auto"
}
]
}
]
},
"output": {
"format": "mp4",
"size": {
"width": 1280,
"height": 720
}
}
}'