š Building a Privacy-First Mobile Document AI App Using Local LLMs, OCR & RAG
In today’s AI-driven world, most document intelligence solutions depend heavily on cloud services. While powerful, they often raise privacy, cost, and compliance concerns —especially in domains like healthcare, legal, and enterprise systems. To solve this, I’m building a mobile-first document intelligence application backed by a local AI server architecture that runs entirely offline . This post explains the idea, architecture, and future roadmap of the project. š§ What Is This Project About? The application is designed to scan, understand, and intelligently process documents such as PDFs and images using on-device and local AI models . Key goals: š Privacy-first processing š» No dependency on cloud APIs ⚡ Fast, local inference š Real-world document workflows At its core, the system uses a single Flask-based backend that powers a mobile application . ⚙️ High-Level Architecture š PDF / Image ↓ š¼ Image Preprocessing ↓ š OCR (Text Extraction) ↓ š RAG + Local Vecto...