Building an AI Watermark Remover on Cloudflare Workers (Single-File Architecture)

Last week, I launched an AI-powered watermark remover that runs entirely on Cloudflare Workers. In this post, I'll walk you through the architecture, challenges, and lessons learned from building a production-ready SaaS with a single-file backend. Live Demo : https://watermark-remover-cf.shop GitHub : https://github.com/zhuwei290/watermark-remover-cf Why Cloudflare Workers? I wanted to build a privacy-focused image processing tool where: Images are never stored on servers (processed in-memory) Global low-latency access (edge computing) Minimal operational overhead (no servers to manage) Cost-effective at scale Cloudflare Workers checked all these boxes. The free tier gives you 100,000 requests/day, which is perfect for an MVP. Architecture Overview Single-File Design The entire backend is one JavaScript file ( worker.js , ~2000 lines) that handles: ┌─────────────────────────────────────────┐ │ Cloudflare Worker │ ├─────────────────────────────────────────┤ │ Frontend (HTML/CSS/JS) │ │