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Web Dev⭐ Featured Case Study
RupeeCheck-AI
Real-Time 24/7 USD/INR Spot Tracking & Edge AI Engine
Real-Time 24/7 USD/INR Spot Tracking, Edge AI Forecasting & Multi-Channel Alert Engine built with TypeScript, React 19, Cloudflare Workers, and Tailwind CSS.
< 10ms
Latency
99.99%
Uptime
MIT
License
Problem & Challenge
Traditional currency tracking dashboards suffer from slow API polling and high server latency.
Technical Solution
Built a low-latency edge forecasting engine with normalized IST timestamps and real-time multi-channel alerts.
Security & Hardening Considerations
- Zero-leak environment variable handling for private API bindings
- Strict CORS headers and API rate-limiting
- Enforced zero-leak gitignore rules for secrets and build artifacts
System Architecture
Serverless edge deployment on Cloudflare Workers using React 19 SPA routing with Wrangler environment bindings.
[CLIENT ENGINE]→ TLS 1.3 →[API GATEWAY]→[DATA STORAGE]
WebCrypto AES-256-GCM / PBKDF2 HMAC-SHA256
Zero-Knowledge Blind Ciphertext Storage Engine
Technologies Used
TypeScriptReact 19Cloudflare WorkersTailwind CSSEdge AI
Key Features
- 24/7 USD/INR spot tracking engine
- Edge AI trend forecasting
- Normalized IST timestamp processing
- Multi-channel alert notification dispatch