ZiG-v0.1-Release

ZiG v0.1.0 — Initial Public Release

Welcome to the first public release of ZiG (Zen i Guess).

ZiG is a privacy-first Android notification filter that intelligently decides which notifications deserve your attention—entirely on your device. No cloud services, no telemetry, no accounts, and no internet access.

What's Included
Privacy by Design
All notification processing happens locally.
No Internet permission.
No analytics or telemetry.
No notification data ever leaves your phone.
No third-party cloud AI services.
Smart Notification Pipeline

Every notification passes through a layered decision pipeline designed for speed and battery efficiency:

Managed Apps filtering
Contact whitelist
Custom keyword rules
On-device machine learning

Deterministic checks run first, ensuring the AI is only invoked when necessary.

On-Device Machine Learning

When rules aren't enough, ZiG uses an entirely local ML ensemble to classify notifications.

The classifier combines:

A custom TensorFlow Lite notification classifier
Personal Memory powered by on-device embeddings
Similarity-based learning from your previous decisions

Nothing is uploaded. Everything stays on your device.

Personal Memory

ZiG gradually adapts to how you handle notifications.

Manual overrides become local training examples that improve future predictions while never leaving your phone.

Managed Apps

Choose exactly which applications ZiG manages.

Apps you don't explicitly enable remain completely untouched.

Custom Rules

Create deterministic keyword rules that bypass AI entirely.

Examples:

OTP
PNR
Boarding Pass
cab, arriving

Rules support multi-keyword matching for precise filtering.

Daily Summary

Receive a once-per-day summary of filtered notifications through a local notification.

No cloud scheduling.

No external services.

Native Rust Engine

Performance-critical components are implemented in Rust, including:

Contact lookup
Managed app filtering
Keyword matching

This provides extremely fast decision making while keeping memory usage low.

Built With
Kotlin
Jetpack Compose
Material 3
Rust (JNI)
TensorFlow Lite
MediaPipe Text Embedder
Room
Hilt
MVVM Architecture
Known Limitations

This is the first public release and should be considered an early preview.

Areas that will continue to improve include:

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

Bug reports, feature requests, and contributions are welcome.

GitHub Issues are the preferred place for reporting problems or suggesting improvements.

Thank you for trying ZiG.

Your notifications. Your AI. Your phone.