Customer Support Triage Dashboard - 24h Programming Challenge

Built for a 24h programming challenge - This is a comprehensive customer support management dashboard designed to streamline ticket triage and response workflows. The application intelligently categorizes incoming support messages using both AI-powered analysis and keyword-based matching, providing agents with prioritized, organized views of customer requests.

The dashboard features real-time filtering, sorting, and status tracking for support tickets, along with detailed analytics on response times, resolution rates, and performance metrics. Agents can quickly triage messages, update statuses, and view customer histories all from a single interface.

The hybrid categorization system allows teams to toggle between AI accuracy and keyword speed depending on their needs, while maintaining persistence of user preferences.

The dashboard was developed with Next.js 14 using the App Router for optimal performance and SEO. TypeScript ensures type safety across the entire application, reducing bugs and improving developer experience.

Key features include:

- **Hybrid Categorization Engine**: Implemented AI-powered categorization using LLM API for intelligent analysis, with fallback to keyword-based matching for offline functionality.

- **Real-time Analytics**: Dynamic summary cards calculate response times, resolution rates, and priority distributions using custom utility functions.

- **Interactive UI**: Built with Tailwind CSS and Lucide React icons for a clean, modern interface with smooth animations and hover effects.

- **State Management**: Uses React hooks (useState, useEffect, useMemo, useCallback) for efficient state handling and performance optimization.

- **Local Storage**: User preferences for categorization method are persisted across sessions.

- **Filtering & Sorting**: Advanced filtering by category, priority, and status with multi-field sorting capabilities.

- **Message Management**: Interactive cards with quick status updates, detailed views, and response time tracking.

A core challenge was implementing the hybrid categorization system with seamless toggling between AI and keyword modes. We optimized API calls to prevent rate limiting and built fallback mechanisms for reliability. The dashboard features a responsive design that works across all devices while maintaining complex functionality.

This project showcases modern full-stack development with focus on user experience, performance optimization, and practical AI integration.