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ZiG v0.2.0 — Smarter, Faster, Fully Redesigned

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@prithvi-vasistha prithvi-vasistha released this 07 Jul 05:18
v0.2
0d7c934

🚀 ZiG v0.2.0 — Smarter, Faster, Fully Redesigned

The second public release of ZiG (Zen i Guess).

Since v0.1, ZiG has received a complete UI redesign, a significantly smarter on-device decision pipeline, and numerous UX improvements—while staying true to the principles it was built on:

  • 🔒 100% on-device processing
  • 🚫 No cloud
  • 🚫 No telemetry
  • 🚫 No accounts
  • 🌐 No internet connection required

✨ What's New

🎨 Complete UI Redesign

The interface has been rebuilt from the ground up using Jetpack Compose and Material 3.

Highlights include:

  • Cleaner and more consistent visual design
  • Faster notification triage
  • Improved navigation throughout the app
  • Reduced friction across the entire experience

📥 Notification Review

Notification Review has been redesigned into a fast, one-tap inbox.

  • ✅ Approve or block notifications instantly
  • ↩️ Undo is always available
  • ⚡ Faster workflow with fewer interactions

🧠 Smarter & More Efficient Decision Pipeline

⚡ Deterministic Exact-Match Cache (New)

Before running any AI inference, ZiG now checks whether a notification has already been seen.

If the newest notification message exactly matches one you've previously approved or blocked:

  • No embedding generation
  • No TensorFlow Lite inference
  • No KNN similarity search

Instead, your previous decision is replayed instantly.

The cache is:

  • Case-insensitive
  • Database index-backed
  • Based on the newest message in a notification, allowing repeated messages in long conversations to be recognized correctly

This dramatically reduces latency for recurring notifications while also lowering CPU usage.

🧩 Improved Classification

The on-device ensemble has been made significantly more robust.

Changes include:

  • Stronger consensus requirements before decisions are made
  • Better interaction between the base classifier and Personal Memory
  • Reduced influence from sparse or ambiguous user history

This results in more stable predictions while still allowing the model to gradually adapt to your personal preferences.

⚠️ Known Limitations

ZiG is still an early preview release.

Areas actively being improved include:

  • ML classification accuracy
  • Personal Memory adaptation
  • Additional rule capabilities
  • UI polish
  • Performance optimizations

💬 Feedback

Bug reports, feature requests, and contributions are always welcome.

Please use GitHub Issues for feedback and bug reports.

❤️ Thank You

Thank you for using ZiG.

Your notifications. Your AI. Your phone.

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