🚀 ResolvAI: Enterprise AI Customer Support & SLA Platform

ResolvAI is an enterprise-grade, full-stack AI-Powered Customer Support Ticketing & SLA Automation Platform. Built with Next.js 14 (App Router), Python Machine Learning (TF-IDF Vectorization), Node.js, and Vercel Serverless Architecture, it delivers automated ticket classification, intelligent agent routing, real-time SLA breach tracking, customer sentiment analytics, and an interactive ResolvAI Copilot Bot.

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🌐 Live Production Demo

• Live Web App: https://resolvai-platform.vercel.app
• GitHub Repository: https://github.com/ByteBySway/resolvai

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✨ Key Features & Capabilities

🧠 1. Automated AI Ticket Classification & Routing

• Live AI Inference Preview: Auto-classifies ticket Category (Technical & Bugs, Billing & Payments, Account & Security, Feature Requests), Priority (Urgent, High, Medium, Low), and Sentiment (Positive, Neutral, Negative, Frustrated) in real-time as the customer types.
• Intelligent Agent Match: Uses TF-IDF keyword vectorization and agent capacity scoring to assign tickets to the best-matched online support specialist.

⏱️ 2. Real-Time SLA Tracking & Breach Alarms

• Dynamic SLA target countdown timers (1h Urgent, 4h High, 12h Medium, 24h Low).
• Stitch Circular SLA Donut Infographic: Real-time visual compliance gauge displaying 96.4% SLA target performance.

🤖 3. Interactive ResolvAI Copilot Bot

• Floating interactive chat assistant drawer in the bottom right corner.
• Answers support manager queries regarding SLA compliance, active ticket counts, agent capacity, and auto-drafting empathetic responses.

📊 4. Agent Performance & CSAT Analytics

• Team Workload Leaderboard: Visual progress bars monitoring active agent queue load (Tier 1 vs. Tier 2 Specialists).
• CSAT Review System: 1-5 Star customer rating modal with feedback submission and Net Promoter Score (NPS +78) analytics.

📥 5. One-Click Data Export

• Instant CSV dataset exporter for support ticket audit trails.

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🏗️ System Architecture

graph TD
    A[Client Web App - Next.js 14] -->|REST API Requests| B[Serverless Route Handlers]
    B -->|Keyword Vectorization| C[Python ML Engine - TF-IDF]
    C -->|Classified Intent & Priority| B
    B -->|Agent Matching & Capacity Score| D[In-Memory MongoDB Store]
    D -->|Real-Time SLA & Tickets Data| A

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🛠️ Tech Stack

Component	Technology Used
Frontend Framework	Next.js 14 (App Router, React 18)
Styling & UI Design	Vanilla CSS Tokens (Stitch & Dribbble CoreLoop AI Glassmorphism)
Machine Learning Engine	Python 3.11 (TF-IDF Keyword Vectorization & Sentiment Scoring)
Backend API	Node.js / Next.js Serverless API Route Handlers
Data Store	In-Memory / MongoDB Dataset Store
Deployment & Hosting	Vercel Edge Cloud

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🚀 Local Quick Start Guide

Prerequisites

• Node.js 18+ installed
• Python 3.9+ installed

Installation & Setup

1. Clone the Repository:

   git clone https://github.com/ByteBySway/resolvai.git
   cd resolvai

2. Install Frontend Dependencies:

   cd frontend
   npm install

3. Run Next.js Local Development Server:

   npm run dev

   Open http://localhost:3000 in your browser to view ResolvAI!

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📡 API Endpoint Reference

Method	Endpoint	Description
GET	/api/tickets	Retrieve list of all support tickets
POST	/api/tickets	Create new support ticket with AI auto-routing
POST	/api/ai/classify	Run live AI classification on subject and description
POST	/api/ai/suggest-reply	Generate AI auto-drafted response
GET	/api/sla/metrics	Fetch SLA compliance rate and target stats
GET	/api/agents	Fetch support agent team availability and workload
GET	/api/analytics/csat	Fetch CSAT score and review statistics

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📄 License

Distributed under the MIT License. See LICENSE for details.

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Crafted with ❤️ for Internship Project Deliverables.