Smart Homes: AI-Powered E-Commerce Platform
I engineered a full-stack e-commerce platform for smart home products that solved key business challenges in user engagement and customer support. By integrating advanced AI and a robust dual-database architecture, the platform offers a uniquely intelligent and seamless shopping experience.
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Project Goal
To design and build an e-commerce platform that goes beyond standard functionality by incorporating AI to automate customer service and provide a more intuitive product discovery experience.
Project Highlights
Performance Metrics
Key Features
- ▹AI-Powered Features: Integrated an OpenAI-powered chatbot to resolve over 30 common support questions, reducing user response time by 80%.
- ▹Optimized Semantic Search: Leveraged Elasticsearch to enable semantic product search, offering more relevant and intuitive results.
- ▹Scalable Architecture: Designed a dual-database system, utilizing MySQL for transactional data and MongoDB for flexible review storage, and used Docker for containerized deployment.
- ▹Full E-Commerce Workflow: Implemented all core functionalities, including user authentication with JWT, a product catalog of over 70 items, and a streamlined order processing system.
- ▹Data Processing Pipeline: Created Jupyter Notebooks for data preprocessing, generating AI content, and pushing embeddings to Elasticsearch.
Technology Deep Dive
React.js
Built a dynamic and responsive user interface with a component-based architecture for a seamless shopping experience.
Node.js / Express.js
Developed a robust RESTful API to handle user authentication, product management, and order processing.
MySQL & MongoDB
Designed a dual-database system, using MySQL for transactional data and MongoDB for flexible storage of user reviews.
Elasticsearch
Implemented a powerful semantic search engine for products and reviews, providing more intuitive and relevant results.
OpenAI
Leveraged GPT and embedding models to create intelligent features like automated content generation and smart product recommendations.
Docker
Containerized all backend services, ensuring a consistent and portable environment for development and deployment.