Handling sensitive data like Electronic Health Records (EHR) is a nightmare for privacy compliance. Whether it's HIPAA in the US or GDPR in Europe, sending a patient's medical history to a cloud-based LLM often triggers a cascade of security audits and potential liabilities. But what if the data never left the user's computer? In this tutorial, we are diving deep into Edge AI and Privacy-preserving AI by building a local EHR parser. Using WebLLM , WebGPU acceleration , and React , we will transform raw medical text into structured JSON entirely within the browser sandbox. No servers, no APIs, and zero data leakage. The Architecture: Why WebLLM? Traditionally, local LLMs required a heavy Python environment (Ollama, LocalAI). With the advent of WebGPU , the browser can now access the local GPU's power directly. WebLLM (powered by TVM.js) allows us to run models like Llama 3 or Mistral directly in the browser's memory.…