• Built and scaled a comprehensive restaurant discovery and analytics platform that grew from 183 to 1,894 weekly visitors, with daily active users reaching 324 at peak engagement.
• Developed semantic search infrastructure using vector embeddings with pagination, delivering sub-200ms response times for contextual restaurant review analysis
• Architected scalable microservices platform using Python FastAPI with async request handling, enabling real-time restaurant availability updates through distributed API integrations
• Built interactive analytics dashboard with SQL-powered data aggregation, providing restaurant owners with real-time reservation metrics and business insights
• Created responsive chatbot interface using Next.js, TypeScript, Shadcn, and Tailwind CSS, achieving 70% reduction in UI lag and sub-50ms message load times