Building a Privacy-First Media Converter in the Browser: No Servers, No Cloud, 100% Client-Side (RAM-Friendly)

Most online file converters require uploading your documents, images, or videos to an unknown server. This is slow, inconvenient, and raises serious privacy concerns. I decided to build something different: a converter that works entirely inside your browser. Processing large files without a backend presents two main engineering challenges: How do you avoid consuming all available RAM? How do you prevent the user interface from freezing? This article explains how I solved these problems using OPFS, Web Workers, and a Backpressure mechanism. The result is a working tool you can try right now: PixelForge Free . The Architecture at a Glance Here is the simplified data flow of the entire pipeline: Drag & Drop → OPFS (Virtual Disk) → Worker Pool (Backpressure) → ZIP Stream → Download Problem 1: Out-of-Memory (OOM) Crashes The Challenge: Loading many files directly into the browser's memory is impossible. A user dropping a folder with 100+ high-resolution images would instantly crash the tab. The Solution: Origin Private File System (OPFS) OPFS provides a fast, isolated virtual disk inside the browser. Instead of loading files into RAM, my pipeline intercepts the drop event and streams the raw binary data directly to this virtual disk. Here is a simplified version of how it works: // Get a reference to the virtual disk const root = await navigator . storage . getDirectory (); const fileHandle = await root . getFileHandle ( `input_ ${ id } .raw` , { create : true }); // Create a writable stream to the disk const writable = await fileHandle . createWritable (); // Stream the file directly from the user's computer to the virtual disk await file . stream (). pipeTo ( writable ); This allows the application to accept a folder with 500+ items without consuming more than a few megabytes of actual RAM. The data stays on the user's SSD, not in memory. Problem 2: UI Freezing The Challenge: Image compression, PDF parsing, and video encoding are CPU-intensive operations. Running them