ID Scanner & Document Capture

Problem

Real-world document capture involves poor lighting, motion blur, damaged documents, inconsistent layouts, and follow-up steps such as previewing PDFs, collecting signatures, and sending structured data to backend systems.

Solution

Built a mobile capture workflow that guides users through document scanning, prepares captured files for preview and signing, and coordinates with backend APIs for processing and structured data extraction.

Architecture & Approach

React Native application using Vision Camera for capture workflows, API integrations for processing, PDF preview and signature flows for document review, and OCR-supported extraction for structured fields.

Key Tradeoffs

• Balancing local capture quality with backend processing keeps the workflow responsive without losing structured extraction flexibility
• Supporting many document types requires continuous updates as formats evolve
• User guidance during capture is more effective than post-processing low-quality images

What I Learned

• Camera workflows need careful optimization to feel reliable on real mobile devices
• Real-world data is significantly messier than sample datasets
• Immediate visual feedback during capture dramatically improves accuracy