PennyPincher by Neski
Intelligent, Cross-Platform personal finance tracking with real-time AI insights.
Project Overview
Managing finances across multiple platforms often leads to data fragmentation. PennyPincher addresses this by providing a unified experience where data flows seamlessly between a native Android experience and a full-featured web dashboard. The project emphasizes clean architecture, real-time synchronization, and accessibility.
Key Features
Real-time Synchronization
Instant data parity between Android and Web using Firebase Realtime Database.
AI-Powered Categorization
Intelligent transaction tagging based on user behavior and history.
Multi-Currency Support
Seamlessly track and convert between multiple currencies for global utility.
Native Performance
Fully native Android app built with Kotlin and Jetpack Compose for high-performance interactions.
System Architecture
A synchronized client-server architecture leveraging serverless backend services for high scalability and zero-config deployment.
Mobile Frontend
Declarative UI with reactive state management for the Android platform.
Web Frontend
Responsive, server-side rendered dashboard optimized for desktop analysis.
Backend & Storage
Centralized authentication and data synchronization layer.
Engineering Challenges
Handling offline data entry and ensuring eventual consistency when the user regains connectivity.
Implemented a local-first repository pattern in the Android app using Room/DataStore and Firebase's native offline persistence.
Maintaining a consistent UI language across different platforms (Jetpack Compose vs. CSS/Tailwind).
Established a shared design token system for colors, spacing, and typography that were manually mapped to both platform libraries.
Screenshot Gallery
Mobile Experience
Key Takeaways
Mastery of Firebase's real-time capabilities and security rules.
In-depth knowledge of Jetpack Compose state management and animations.
Optimizing React performance for large, data-heavy dashboards.
Tech Stack
My Role
- Architected the entire system from mobile client to web dashboard.
- Implemented real-time synchronization logic and offline-first data handling.
- Designed the database schema for efficient cross-platform querying.
- Developed the AI categorization engine using pattern matching and historic data.