05 · 2026SoftwareAI
Laundry Manager (LoadCheck)
Deterministic Bilingual Voice & Offline-First Garment Load Engine
Role & Context
Full-Stack & Systems Developer
Production Application · Next.js & IndexedDB
Languages
English & Hinglish
Architecture
Offline-First Browser App
Storage
Dexie IndexedDB
Balancing
Weight & Fabric Care
English + Hinglish NLU Sandbox
Pipeline Output Trace
Ready · Deterministic pipeline mirrors loadcheck IntentDetector.ts
Simulated Drum Load4.05 / 7.00 kg (58%)
Cotton Shirts4 × 0.25 kg
Denim Jeans2 × 0.65 kg
Bath Towels2 × 0.45 kg
Bedsheets1 × 0.85 kg
Project Context & Objectives
Standard laundry tracking apps lack intelligence for fabric care, leading to overloaded drums, fabric damage, and color bleeding. LoadCheck parses natural text or voice inputs to automatically calculate drum weight and recommend optimal wash cycles.
Key Features & Design Solutions
- Natural language parser handling multi-item English and Hinglish commands with number and reference resolution.
- Drum capacity and dry-weight balance engine enforcing safe load thresholds across fabric types.
- Offline-first browser persistence with IndexedDB ensuring full functionality without a server connection.
Key Deliverables
- English & Hinglish Intent Parser
- Drum Capacity & Dry-Weight Balancing Engine
- Interactive Deterministic NLU Simulator Embedded Below
Tools & Stack
Next.jsReact 19TypeScriptDexie (IndexedDB)Voice & Speech APIs