Overview
Key Features
- Semantic Search Engine: Built a search engine for e-commerce platforms leveraging natural language processing to understand search intent and surface relevant products beyond exact keyword matches.
- Context-Aware Conversational Chatbot: Developed an AI-powered customer support chatbot with multi-turn conversation memory, providing personalized assistance, troubleshooting, and product recommendations.
- Real-Time Catalog Syncing: Engine for continuous catalog synchronization with online store backends, ensuring product availability and price changes are instantly updated in search and chat responses.
- Multilingual Intelligence: Comprehensive internationalization support allowing global shoppers to interact, search, and receive recommendations in their native languages.
- Analytics & Engagement Dashboard: Built real-time monitoring tools to track search volume, chatbot resolution rates, user conversion metrics, and search latency.
- Backend Optimization & Caching: Engineered multi-level caching strategies with Redis and optimized database queries, reducing AI search latency to under 100ms and chatbot response times to under 2 seconds.
Technologies Used
- Next.js & React: Frontend web applications and interactive chat/search widgets.
- TypeScript: End-to-end type safety and clean modular architecture.
- Nest.js & Node.js: Scalable microservice APIs handling catalog syncing and LLM orchestration.
- PostgreSQL & MongoDB: Dual storage setup for transactional catalog metadata, conversation logs, and analytics.
- Redis: High-speed caching for search queries and user conversation context.
- Docker: Microservices containerization for reproducible deployments.
