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🩺 InfoRx – Healthcare Clarity When You Need It Most

💡 Inspiration

In many parts of Nigeria, patients often receive prescriptions, lab results, or scan reports with little or no explanation. Doctors are overwhelmed. Patients are left confused. Some delay care simply because they don’t understand what was written.

InfoRx was inspired by a common frustration: "I have my result, but what now?"
I built this tool to bridge that gap between diagnosis and understanding, especially when doctors aren't immediately available or communication is rushed.

⚙️ What it does

InfoRx helps users upload medical documents (prescriptions, lab results, scan images, etc.) and provides a clear, AI-generated interpretation — breaking down medical jargon into:

Simple next steps
Medication guidance
Test explanations
Referral or red-flag notices

It also includes:

A secure Medical Vault to manage uploaded records
Real-time activity tracking
User-friendly dashboard with dark mode
Logging and analytics for usage patterns

🛠 How I built it

Frontend:

Bolt.new the primary tool for the project
Next.js 13 (App Router)
Tailwind CSS + Shadcn UI for styling
Zustand for global state (auth, theme)
GSAP for smooth UI animations
Cursor & ChatGPT to iterate UI & fix bugs

Backend:

Supabase (auth, database, file storage, realtime logs)
Supabase Edge Functions for future AI triggers
File processing layer to extract text from PDFs, DOCX, TXT, and image files (via OCR)

AI & Processing:

Claude-3-Haiku (via OpenRouter.ai) to explain medical content
Tesseract.js for client-side OCR
Mammoth.js for Word document parsing

🧗 Challenges I ran into

Hydration errors in Next.js when mixing client/server logic (especially around auth and theme)
Managing PDF and DOCX parsing on the frontend with limited libraries
Handling Supabase storage access (private vs public access)
Handling authentication with Supabase since Bolt.new doesn't directly integrate Supabase with Next.js
Ensuring fast feedback in the dashboard during file uploads and processing
Time constraints with implementing file-based AI processing in production-ready flow

🏆 Accomplishments that I am proud of

Built a clean, intuitive dashboard from scratch
Implemented secure auth and file vault system
Designed an AI flow that interprets diverse medical documents
Created a real-time activity logging system

📚 What I learned

Fine-tuning user experience is just as hard (and important) as the AI logic
Supabase is powerful but requires careful planning with security and file access
Small touches like animation, clear feedback, and theme switching make a huge difference
Building trust in healthcare tools means being clear, careful, and respectful with users’ data