Xybrid: AI on-device
Build apps that work with on-device AI, using Xybrid.
"A founder wants to create a new app that scans restaurant menus and recommends the best dishes, based on user ratings and dietary restrictions. They start by setting up a Rust development environment, create an Xybrid instance, and use its APIs to integrate on-device image recognition. After a few hours of development, they test the app and see that it can accurately identify menu items and provide personalized recommendations. The app is now ready to be released on the App Store."
- •When you need to build an app that can perform complex AI tasks without requiring a constant internet connection
- •When user data privacy is a top concern and you want to keep processing on-device
- •When you're looking to reduce latency and improve the overall user experience of your app
To get started with a basic image classification model, use the command `xybrid::init_model("image_classification")` in your Rust codeSkip the builder — one click puts this in Claude, Cursor, Antigravity and more.
We haven’t analyzed this repo’s setup — your AI agent will work it out from the README and ask you if anything is missing.
mkdir -p ~/.claude/skills/xybrid && curl -fsSL https://workflowstacks.com/api/skills/xybrid/claude-skill -o ~/.claude/skills/xybrid/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
What's inside — free to inspect
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
We haven’t analyzed this repo’s setup — your AI agent will work it out from the README and ask you if anything is missing.
mkdir -p ~/.claude/skills/xybrid && curl -fsSL https://workflowstacks.com/api/skills/xybrid/claude-skill -o ~/.claude/skills/xybrid/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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