Predictye AI: Resale Value Prediction Platform

Built an AI-powered platform that estimates resale values for furniture and jewelry using image analysis and conversational interfaces. This project was my deep dive into AI integration and building intelligent user experiences.

Technical Challenge

People struggle to accurately price items for resale either leaving money on the table or overpricing and not selling. I wanted to build a solution that combines visual AI analysis with conversational UX to provide accurate estimates.

AI Integration Journey

API Integration: Google Gemini 2.0 Flash for multi-modal AI (text + image processing)

Image Processing: Cloudinary for upload, optimization, and analysis pipeline

Conversation Flow: Built dynamic questionnaire system that adapts based on item category

Data Visualization: Recharts for displaying price trends and confidence ranges

Technical Stack

Frontend: Next.js 14 with App Router for optimal SEO and performance

Backend: Prisma ORM with MongoDB Atlas for flexible data modeling

Authentication: NextAuth.js with Google OAuth integration

AI Services: Google Gemini API for intelligent image and text analysis

Deployment: Vercel with environment-based configuration

Key Features Built

Multi-modal AI analysis combining image recognition with conversation context

Dynamic form generation that adapts questions based on detected item categories

Real-time price estimation with confidence intervals and market trend data

Conversation memory for context-aware follow-up predictions

Save and compare functionality for tracking multiple items

Learning Experience

This project taught me AI API integration, building conversational interfaces, and creating intelligent user flows. The biggest challenge was designing prompts that consistently returned structured data while maintaining natural conversation flow.

Current Status

Live platform processing image uploads and generating AI-powered resale estimates.