AutoSphere - NextGen Automotive Marketplace in Rwanda

React
Node.js
Three.js
TensorFlow.js
AWS

Project Overview

AutoSphere revolutionizes the automotive marketplace in Rwanda, offering a sophisticated platform that integrates advanced search, immersive 360° vehicle visualizations, and AI-driven pricing recommendations. Built with Next.js, Three.js, and TensorFlow.js, it caters to both dealers and private sellers with unparalleled functionality and performance.

Category

E-Commerce Platform

Client

James Wilson

Timeframe

Q4 2022 - Q2 2023

Role

Lead Developer

Goals

  • Enable real-time vehicle configuration with dynamic pricing
  • Reduce search-to-listing time by 40%
  • Increase dealer adoption by 35% within the first 90 days
Hele

How I Grew

This project accelerated technical expertise: - Gained proficiency in 3D visualization and WebGL through Three.js. - Developed client-side machine learning models for dynamic pricing. - Mastered optimization of complex data structures for real-time updates. - Enhanced AWS deployment strategies for global scalability.

Challenges

The automotive sector posed complex challenges: - Managing extensive vehicle datasets with hundreds of attributes per listing. - Delivering immersive 3D visualizations without compromising performance. - Unifying B2C and B2B functionalities in a single platform, unlike existing solutions that prioritized one over the other.

Solution

- Engineered a unified data model to streamline consumer and dealer interactions. - Implemented interactive 360° vehicle views with hotspot annotations using Three.js. - Developed a TensorFlow.js-based machine learning model for fair pricing recommendations. - Built a dealer portal with inventory management and lead tracking capabilities. - Designed a progressive loading system to optimize media-heavy pages, ensuring responsiveness.

Results

- Reduced search-to-listing time by 52%, exceeding the 40% goal. - Achieved 68% dealer adoption within 90 days, surpassing the 35% target. - Attained a 4.8/5 average rating for search relevance. - Processed $28M in transactions in the first quarter post-launch.