Find
Pre-launch market scouting. Paste any keyword, get a verdict - wide_open, workable, saturated, or brutal - plus a cross-market comparison and long-tail variants generated on-device.
An on-device, macOS-native App Store Optimization copilot for indie developers. Scout markets before you build, track what you shipped, and close the loop by attributing rank movements back to the specific metadata rewrites you copied from the app.
Pre-launch market scouting. Paste any keyword, get a verdict - wide_open, workable, saturated, or brutal - plus a cross-market comparison and long-tail variants generated on-device.
Post-launch ASO copilot. Keyword ranks, auto-discovered competitors, review clustering with reply drafts, a weekly plan, and a metadata rewriter that produces 3–5 candidates per field - all on-device.
Every metadata candidate you copy is tracked from copy → adoption → 7/14/28-day rank-delta verdict. The wins ledger is built from real rank movements, not guesses. No other indie ASO tool ties rewrites to outcomes.
git clone https://github.com/jafforgehq/orbion.git
cd orbion
open Orbion.xcodeproj
Build the Orbion scheme, ⌘R to run. Onboarding picks a country, asks for one App Store URL or ID, and starts collecting rank data within a minute.
For your own signing team, copy Configs/Local.xcconfig.example to Configs/Local.xcconfig and edit. The local config is gitignored, so your team ID never lands in the repo.
I built Orbion because I wanted an ASO tool that fit how I actually work: a Mac app I open occasionally, no monthly bill, no API keys to babysit, no data leaving my machine. Once the pieces were in place for my own use, opening the source was the obvious next step - if it's useful to me, someone else might want it too.
Foundation Models on-device means there's no API cost for the AI, no key to manage, and nothing leaves your Mac. The only network calls are public iTunes endpoints - and your own App Store Connect API key, if you choose to connect it.