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Install Ignia.

Ignia runs as a desktop app, a mobile app, and in the browser. Pick the platform you need; the first-launch steps follow below.

Desktop.

Windows, macOS, Linux. Built with Tauri, so the binary is small and the app feels native.

  1. 1. Download the release.

    During the closed beta the installer link comes with your invitation. Pick the artifact matching your OS: .msi for Windows, .dmg for macOS, .AppImage or .deb for Linux.

  2. 2. Install and open the app.

    Double-click the installer. On macOS, you may need to right-click and choose Open the first time, since the build is not yet signed.

  3. 3. Configure your AI.

    First launch will ask you to set up an AI provider. See AI providers for the three options: managed, your own key, or fully local with Ollama.

Roughly 200 MB on disk, 4 GB RAM is enough. For local model use, see the Ollama tier in AI providers.

Mobile.

Android available; iOS coming.

  1. 1. Get the APK.

    The Android build comes with the same invitation link. Sideloading required for now; Play Store distribution is planned.

  2. 2. Allow install from this source.

    Your phone will warn about installing outside the Play Store. Permit it for the file manager you used to download the APK.

  3. 3. Sync with desktop (optional).

    If you already use Ignia on desktop, sign in with the same email on mobile and your courses come across: plans, course text, exercises, your answer history and your review schedule.

Browser.

Self-host Ignia and use it from any browser. Useful for shared machines or work-restricted laptops.

  1. 1. Clone the repo.

    Clone Ignia-org/Ignia-app. The Rust backend (Axum) is in crates/ignia_http.

  2. 2. Run the docker compose stack.

    A docker-compose.yml is shipped at the repo root. Run docker compose up -d. The frontend builds, the backend serves on the configured port, and Caddy acts as a reverse proxy in front.

  3. 3. Open the URL.

    Navigate to the host you set in the Caddy config. The web mode is single-tenant: one user per deployment.