Listen
“Show the mistakes and fixes—not only the reveal. The 30 seconds where you admitted the s…”
compost_confessions · 231 likes · 26 supporting comments
Audience intelligence for creators
From audience signals to publish-ready content.
Synthetic data · no account · nothing gets published
NextBestContent reads the comments under a video, finds the three signals the audience keeps repeating, and turns the one you choose into a six-scene YouTube Short or a LinkedIn document post — then runs seven transparent checks before anything leaves the studio.
Every recommendation carries the actual comments behind it.
The whole journey, previewed
From the synthetic “Maya Makes Space” demo — fictional creator, fictional comments, original artwork
Decide
Show the mistakes and fixes—not only the reveal.
Opportunity score 81 / 100 · one of exactly three signals
Create
“3 mistakes that nearly killed my balcony garden.”
Six scenes · LinkedIn alternative: “6 decisions behind a 2m² food garden.”
Preflight & export
Seven transparent checks
Then copy, storyboard, PNG, and PDF exports — nothing is published automatically
Where your content can land
YouTube
- YouTube Short
- Document post
- Text post — planned
X / Twitter
Coming soon — nothing drafted or published yet
Coming soon — nothing drafted or published yet
Sources: live YouTube comments and creator imports (self-hosted) · the synthetic demo right here.
Built to be trusted with an audience
- Synthetic by design
- The public experience runs on clearly labeled fictional data — no real comments are read and none are stored.
- No account needed
- The demo runs entirely in your browser session. Nothing to sign up for, nothing persisted.
- Nothing is published
- Exports are local files — captions, storyboards, images, PDFs. You upload them yourself, deliberately.
- Private by default
- The full product runs on your machine. The recommended key path is server-managed container configuration; optional request-scoped keys are never stored.
Run it privately with your own key
The complete product — live YouTube analysis, comment imports, and generation — runs on your machine. The recommended setup keeps your model key in the container environment. If the operator enables request-scoped keys, they stay in memory for one run and are never stored.
- 1 Clone the repository and copy the example environment file.
- 2 Set your model key and feature gates in the container environment.
- 3 Start it up and open your private workspace on localhost.