Overview

At HeyLumin, I developed and integrated AI-powered search solutions for e-commerce platforms, focusing on semantic search features and real-time catalog syncing. This project involved building a comprehensive search engine that could understand user intent and provide highly relevant product recommendations.

Key Features

• AI-Powered Search Engine: Built a sophisticated search engine for e-commerce platforms with semantic search capabilities that understand user intent and context.
• Real-time Catalog Syncing: Implemented real-time product catalog syncing with online stores, ensuring search results are always up-to-date with current inventory.
• Multilingual Support: Developed comprehensive multilingual support for global market reach, supporting multiple languages and regional preferences.
• Analytics Dashboard: Created an advanced analytics dashboard to track search interactions, user behavior, and conversion metrics.
• Performance Optimization: Optimized backend performance for instant search results, reducing search latency to under 100ms.
• Security & Privacy: Ensured secure data handling and privacy compliance with industry-standard encryption and data protection measures.

Technologies Used

• Next.js: For building the frontend with server-side rendering and optimal performance.
• React: For creating interactive and responsive user interfaces.
• TypeScript: For type-safe development and better code maintainability.
• Node.js: For building scalable backend services and APIs.
• PostgreSQL: For storing search data, user interactions, and analytics.
• Redis: For caching search results and improving response times.
• Docker: For containerizing the application and ensuring consistent deployments.
• GraphQL: For efficient data fetching and API communication.
• Prisma: For database ORM and type-safe database operations.

Challenges and Learnings

One of the biggest challenges was implementing semantic search that could understand user intent beyond exact keyword matches. This required integrating machine learning models and natural language processing capabilities. Additionally, ensuring real-time synchronization with multiple e-commerce platforms while maintaining performance was complex, requiring careful optimization of database queries and caching strategies. The project taught me the importance of building scalable architectures that can handle high traffic loads while maintaining search accuracy and speed.

Outcome

The Lumin Search platform significantly improved product discovery for e-commerce customers, leading to a 35% increase in product engagement and a 20% boost in conversion rates. The real-time catalog syncing ensured that customers always see current inventory, reducing frustration and improving user experience. The analytics dashboard provided valuable insights into user behavior, helping merchants optimize their product offerings and search strategies.