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    Mobile App

    Lace Inventory Manager

    A personal project built for my father's textile business. He managed 800-900 unique lace entries in a handwritten diary; finding any specific design meant flipping through pages every time. I replaced it with a searchable mobile app, simple enough for a non-technical user to operate daily.

    React Native
    Expo
    TypeScript
    React Query
    Google Apps Script
    Cursor AI
    Read Story

    The Problem

    Over years of running the business, my father's diary filled up with 800-900 handwritten lace entries, each with its own design number and stone details. Finding a specific lace meant flipping through pages one by one with no search, no structure, and no way to compare entries quickly.

    The Outcome

    Built and shipped in 6-7 hours using only free AI tools. The app replaced the physical diary entirely; lookups went from page-flipping to instant search, and Google Sheets as the backend keeps data accessible without requiring any technical knowledge.

    Overview

    Lace Inventory Manager is a personal project built out of a genuine need. My father runs a textile business and had been maintaining all product records in a physical diary for years. Over time that diary grew to 800-900 unique lace entries, each with its own design number, stone composition, labour cost, and selling price. Retrieving any specific entry meant flipping through pages every single time. I built this app to put the entire inventory at his fingertips, on his phone, searchable in seconds.

    Approach

    I kept the architecture deliberately simple to match the actual user. Instead of a server and database, I used Google Apps Script connected to a Google Sheets spreadsheet as the backend. That means the data stays in a format my father can read and edit directly if ever needed, with no technical knowledge required. On the frontend, a single React Native codebase built with Expo runs across iOS, Android, and web. React Query handles all data fetching, caching, and background syncing. The entire project was planned, designed, and shipped in 6-7 hours using Cursor, ChatGPT, and Google Gemini as AI tools.

    Key Features

    • Instant search by lace design number (D.N code)
    • Full CRUD: add, view, edit, and delete lace entries
    • Dynamic stone composition tracking with name and quantity per stone type
    • Labour cost and actual selling price recorded per entry
    • Top 20 recently searched laces surfaced automatically on the home screen
    • Smart duplicate detection while creating new entries
    • Reference an existing entry to pre-fill a new one
    • Light, dark, and system-default theme support with persistent preference

    Challenges Solved

    • Designing a serverless backend using Google Apps Script and Sheets that is reliable for daily production use while remaining fully readable by a non-technical business owner
    • Building mobile-first instant search without a traditional database query layer or indexing
    • Aggregating flat stone rows returned by the API into structured lace entries with stone tables, entirely on the client side
    • Keeping the UI simple enough for a non-technical user while supporting the full range of inventory operations the business actually needs
    • Implementing real-time duplicate detection with debouncing so the app checks for conflicts without flooding the API on every keystroke

    By the Numbers

    6-7 hrs

    Built In

    800+

    Lace Entries

    3

    Platforms

    3

    AI Tools Used

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