🌱 Rayeva AI Dashboard

Intelligent Automation for Sustainable E-Commerce

AI-powered automation platform built for Rayeva World Pvt Ltd 🌍

Features • Quick Start • API Docs • Tech Stack • Demo

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📋 Table of Contents

• About
• Features
• Tech Stack
• Architecture
• Quick Start
• Module Details
• API Reference
• Database Schema
• Environment Setup
• Project Structure
• Demo

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🎯 About

Rayeva is revolutionizing sustainable e-commerce with eco-friendly products. This dashboard automates their most time-intensive operations using Google Gemini AI, reducing manual work by 80% while improving accuracy and customer experience.

💡 Built as an internship project to demonstrate real-world AI integration in sustainable business operations.

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✨ Features

🏷️ Smart Product Tagger Automatically categorize products and generate SEO-optimized tags with sustainability filters. Key Benefits: ⚡ Instant categorization 🎯 95%+ accuracy 🔍 SEO tag generation ♻️ Sustainability scoring	💼 B2B Proposal Generator Create customized bulk purchase proposals that maximize budget utilization. Key Benefits: 💰 Budget optimization (90-100%) 📊 Impact calculations 🎨 Professional formatting 🌱 ESG alignment
🌍 Impact Report Generator Calculate environmental impact with precision — plastic saved, carbon avoided, and local sourcing metrics. Key Benefits: 📈 Real-time calculations 🌊 Plastic waste tracking 🌿 Carbon footprint analysis 📝 Human-readable reports	💬 WhatsApp Support Bot Intelligent customer support via WhatsApp with automatic intent detection and routing. Key Benefits: 🤖 24/7 availability 🎯 Intent classification 📦 Order tracking 🚨 Smart escalation

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🛠️ Tech Stack

Backend

Frontend

AI & Integration

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🏗️ Architecture

graph TB
    A[React Frontend<br/>Vite + CSS Variables] -->|HTTP/JSON| B[FastAPI Backend<br/>Python 3.11]
    B --> C[Module 1: Product Tagger<br/>/api/categorize-product]
    B --> D[Module 2: Proposal Generator<br/>/api/generate-proposal]
    B --> E[Module 3: Impact Report<br/>/api/generate-impact-report]
    B --> F[Module 4: WhatsApp Bot<br/>/api/whatsapp/webhook]
    C --> G[Google Gemini AI]
    D --> G
    E --> G
    F --> G
    C --> H[(SQLite Database<br/>7 Tables)]
    D --> H
    E --> H
    F --> H
    
    style A fill:#00c4a7,stroke:#009688,color:#fff
    style B fill:#00c4a7,stroke:#009688,color:#fff
    style G fill:#00c4a7,stroke:#009688,color:#fff
    style H fill:#00c4a7,stroke:#009688,color:#fff

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System Flow: React frontend communicates with FastAPI backend via REST API. Each module leverages Google Gemini AI for intelligent processing, with all data persisted in SQLite.

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🚀 Quick Start

Prerequisites

• Python 3.11+
• Node.js 18+
• Google Gemini API Key (Get one free)

Backend Setup

# 1️⃣ Clone the repository
git clone https://github.com/YOUR_USERNAME/rayeva-ai-modules.git
cd rayeva-ai-modules

# 2️⃣ Create and activate virtual environment
python -m venv venv

# Windows
venv\Scripts\activate

# Mac/Linux
source venv/bin/activate

# 3️⃣ Install dependencies
pip install -r requirements.txt

# 4️⃣ Configure environment variables
cp .env.example .env
# Edit .env and add your GEMINI_API_KEY

# 5️⃣ Seed database with test data
python seed_data.py

# 6️⃣ Start the server
uvicorn main:app --reload

✅ Backend running at: http://127.0.0.1:8000
📚 API Documentation: http://127.0.0.1:8000/docs

Frontend Setup

# 1️⃣ Navigate to frontend directory
cd frontend

# 2️⃣ Install dependencies
npm install

# 3️⃣ Start development server
npm run dev

✅ Dashboard running at: http://localhost:5173

🎉 You're all set! Open the dashboard and start exploring the modules.

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🤖 Module Details

🏷️ Module 1 — Smart Product Tagger

🎯 Purpose: Automatically categorize products and generate SEO-optimized tags with sustainability scoring.

📥 Input: Product name + description

📤 Output: Category, sub-category, SEO tags, sustainability filters, confidence score

Example Request

{
  "product_name": "BambooFresh Toothbrush",
  "product_description": "Biodegradable bamboo, plastic-free packaging"
}

Example Response

{
  "category": "Personal Care",
  "sub_category": "Oral Hygiene",
  "seo_tags": ["bamboo toothbrush", "plastic-free", "eco toothbrush"],
  "sustainability_filters": ["plastic-free", "biodegradable"],
  "confidence_score": 0.95
}

🧠 AI Strategy

• Role-based prompting with predefined category taxonomy
• Strict JSON output enforcement
• Temperature: 0.3 for consistency
• Validation: Confidence scoring for quality assurance

💼 Module 2 — B2B Proposal Generator

🎯 Purpose: Generate customized bulk purchase proposals that maximize budget utilization while meeting client preferences.

📥 Input: Client details, budget, employee count, sustainability preferences

📤 Output: Product recommendations, pricing breakdown, impact summary, ESG positioning

Example Request

{
  "client_name": "GreenTech Pvt Ltd",
  "industry": "Technology",
  "budget": 50000,
  "num_employees": 50,
  "preferences": ["plastic-free", "recycled"]
}

Example Response

{
  "recommended_products": [
    {
      "product_name": "Bamboo Desk Organizer",
      "category": "Office & Stationery",
      "quantity": 50,
      "unit_price": 299,
      "total_price": 14950,
      "sustainability_features": ["plastic-free", "biodegradable"]
    }
  ],
  "total_cost": 49850,
  "budget_utilization_percent": 99.7,
  "impact_summary": "Eliminates approximately 600 single-use plastic items",
  "impact_positioning": "Perfect for ESG goals and CSR reporting"
}

🧠 AI Strategy

• Role: B2B sales consultant persona
• Budget constraint: Strict adherence with 90-100% utilization target
• Temperature: 0.5 for balanced creativity
• Output: Professional proposal format with impact metrics

🌍 Module 3 — Impact Report Generator

🎯 Purpose: Calculate precise environmental impact metrics and generate human-readable sustainability reports.

📥 Input: Order ID + product list with sustainability attributes

📤 Output: Plastic saved, carbon avoided, local sourcing %, impact statement

Two-Step Processing

Step 1: Python Calculations (No AI guessing)

plastic_saved_grams = weight × quantity × 0.8   # plastic-free items
carbon_avoided_kg   = weight × quantity × 0.002 # local/organic items
local_sourcing_%    = local_items / total × 100

Step 2: AI Communication (Gemini writes engaging statement)

"Your order saved 144g of plastic — like removing
 96 straws from the ocean! 🌊"

Example Response

{
  "plastic_saved_grams": 144.0,
  "carbon_avoided_kg": 0.36,
  "local_sourcing_percent": 50.0,
  "impact_statement": "Amazing! Your order saved 144g of plastic — equivalent to removing 96 plastic straws from the ocean! 🌊 You also avoided 0.36kg of carbon emissions. Keep making a difference! 🌱"
}

🧠 AI Strategy

• Hybrid approach: Python for math, AI for communication
• Temperature: 0.7 for warm, engaging tone
• Max tokens: 500 for concise statements
• Validation: Math verified before AI processing

💬 Module 4 — WhatsApp Support Bot

🎯 Purpose: Provide 24/7 intelligent customer support via WhatsApp with automatic intent detection and routing.

📥 Input: Twilio webhook POST (customer WhatsApp message)

📤 Output: TwiML XML response sent back to customer

System Flow

graph LR
    A[Customer WhatsApp] --> B[Twilio]
    B --> C[POST /api/whatsapp/webhook]
    C --> D{AI Intent Detection}
    D -->|order_status| E[Query Database]
    D -->|return_policy| F[Return Policy Text]
    D -->|refund_escalation| G[Create Escalation]
    D -->|general| H[AI Response]
    E --> I[Format TwiML]
    F --> I
    G --> I
    H --> I
    I --> B
    B --> A
    
    style D fill:#00c4a7,stroke:#009688,color:#fff
    style I fill:#00c4a7,stroke:#009688,color:#fff

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Intent Categories

• order_status → Query database for order tracking
• return_policy → Return hardcoded policy text
• refund_escalation → Log to database, alert team
• general → AI-generated response

Test Commands (with seed data)

"Where is my order ORD-001?" → Order found, status returned
"What is your return policy?" → Policy text returned
"I want a refund now!"        → Escalation created, team alerted

🧠 AI Strategy

• Strict classification: Single-word intent output
• Temperature: 0.3 for consistent routing
• Fallback: Always defaults to "general" on failure
• Logging: All conversations stored for analysis

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📡 API Reference

Module 1: Product Tagger

Method	Endpoint	Description
POST	/api/categorize-product	Tag a product with AI
GET	/api/products	List all tagged products

Module 2: Proposal Generator

Method	Endpoint	Description
POST	/api/generate-proposal	Generate B2B proposal
GET	/api/proposals	List all proposals

Module 3: Impact Report

Method	Endpoint	Description
POST	/api/generate-impact-report	Calculate order impact
GET	/api/impact-reports	List all impact reports

Module 4: WhatsApp Bot

Method	Endpoint	Description
POST	/api/whatsapp/webhook	Twilio webhook handler
GET	/api/whatsapp/logs	View conversations
GET	/api/escalations	View escalations

📚 Interactive API Docs: Visit http://127.0.0.1:8000/docs for full Swagger documentation with live testing.

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🗄️ Database Schema

7 SQLAlchemy Tables:

Table	Purpose	Key Fields
product_tags	Module 1 outputs	category, sub_category, seo_tags, sustainability_filters
b2b_proposals	Module 2 outputs	client_name, recommended_products, total_cost, budget_utilization
impact_reports	Module 3 outputs	plastic_saved_grams, carbon_avoided_kg, impact_statement
orders	Seed data for testing	order_id, customer_name, products, status
whatsapp_logs	Module 4 conversations	message, intent, response, timestamp
escalation_logs	Flagged customer issues	customer_message, status (pending/resolved)
ai_logs	AI call tracking	module, prompt, response, success, timestamp

💾 Database: SQLite for simplicity. Production-ready with easy migration to PostgreSQL/MySQL.

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⚙️ Environment Setup

Required Variables

# .env file

# 🔑 Google Gemini API Key (Required)
# Get your free key: https://aistudio.google.com/app/apikey
GEMINI_API_KEY=your_api_key_here

# 📱 Twilio Configuration (Optional - only for live WhatsApp testing)
TWILIO_ACCOUNT_SID=your_account_sid
TWILIO_AUTH_TOKEN=your_auth_token
TWILIO_WHATSAPP_NUMBER=whatsapp:+14155238886

# 🌐 Frontend Configuration
VITE_API_BASE_URL=http://127.0.0.1:8000

⚠️ Important: Never commit your .env file. Use .env.example as a template.

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📁 Project Structure

rayeva-ai-dashboard/
│
├── 📂 modules/                      # AI Module Implementations
│   ├── module1_tagger.py           # 🏷️ Product categorization & tagging
│   ├── module2_proposal.py         # 💼 B2B proposal generation
│   ├── module3_impact.py           # 🌍 Environmental impact calculations
│   └── module4_whatsapp.py         # 💬 WhatsApp bot with intent routing
│
├── 📂 frontend/                     # React Dashboard
│   ├── 📂 src/
│   │   ├── 📂 pages/
│   │   │   ├── Home.jsx            # Landing page
│   │   │   ├── ProductTagger.jsx   # Module 1 interface
│   │   │   ├── ProposalGenerator.jsx # Module 2 interface
│   │   │   ├── ImpactReport.jsx    # Module 3 interface
│   │   │   └── WhatsAppBot.jsx     # Module 4 interface
│   │   │
│   │   ├── 📂 components/
│   │   │   ├── Navbar.jsx          # Navigation with teal theme
│   │   │   └── JsonDisplay.jsx     # Formatted JSON viewer
│   │   │
│   │   ├── 📂 api/
│   │   │   └── client.js           # Axios API client
│   │   │
│   │   ├── App.jsx                 # Main app component
│   │   └── index.css               # Global styles (CSS Variables)
│   │
│   ├── index.html
│   ├── package.json
│   └── vite.config.js
│
├── 📄 main.py                       # FastAPI app with all routes + CORS
├── 📄 models.py                     # SQLAlchemy table definitions (7 tables)
├── 📄 database.py                   # SQLite engine + session management
├── 📄 ai_client.py                  # Google Gemini API client wrapper
├── 📄 seed_data.py                  # Test data generator (5 sample orders)
│
├── 📄 requirements.txt              # Python dependencies
├── 📄 .env.example                  # Environment template
├── 📄 .gitignore
└── 📄 README.md                     # You are here! 👋

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🎬 Demo

Test Data Available

The system comes pre-seeded with 5 sample orders for testing the WhatsApp bot:

Order ID	Customer	Product	Status	Test Query
ORD-001	Priya Sharma	Bamboo Toothbrush × 2	✅ Delivered	"Where is my order ORD-001?"
ORD-002	Rahul Mehta	Reusable Water Bottle × 1	📦 Shipped	"Track order ORD-002"
ORD-003	Ananya Singh	Organic Cotton Tote × 3	⏳ Processing	"Status of ORD-003?"
ORD-004	Vikram Patel	Compostable Plates × 10	✅ Delivered	"Where is ORD-004?"
ORD-005	Sneha Joshi	Beeswax Food Wraps × 5	📦 Shipped	"Check ORD-005 status"

Live Demo

🚀 https://rayeva-ai-modules.vercel.app/

Backend runs locally — clone the repo and run uvicorn main:app --reload to connect the AI modules.

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🤝 Contributing

This project was built as an internship assignment, but contributions are welcome!

Areas for improvement:

• 🎨 Enhanced UI/UX designs
• 🧪 Unit and integration tests
• 📊 Analytics dashboard
• 🔐 Authentication system
• 🌐 Multi-language support
• 📱 Mobile app integration

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📝 License

This project is part of an internship assignment for Rayeva World Pvt Ltd.

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👨‍💻 Author

Rushikesh Randive
Full Stack / AI Intern
Rayeva World Pvt Ltd • 2026

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🌱 Built with passion for sustainable commerce

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Automating sustainability, one AI module at a time 🚀

Built by Rushikesh Randive · Rayeva World Pvt Ltd Internship · 2026