🔍 AI-Powered Lead Recommendation System

A full-stack application that combines machine learning with sales automation to prioritize and engage high-quality leads.

🌟 Key Features

🧠 Intelligent Lead Processing

• Predictive Scoring: ML model (Random Forest) generates 0-100 quality scores
• Real-Time Verification: Email validation using Hunter.io API
• Adaptive Learning: Incorporates conversion feedback to improve scoring

💼 Sales Productivity Tools

• Smart Filtering and Organisation: Sort by industry.Get leads arranged by best scores automatically.
• Bulk Actions: Export CSV for selected leads of choice or straightaway export verified leads.
• Template Engine: Dynamic email personalization ({name}, {company})

🛠️ Technology Stack

Component	Technology
Frontend	Streamlit (Python)
Backend API	FastAPI
Machine Learning	Scikit-learn
Data Processing	Pandas/Numpy
Email Delivery	SMTP (TLS)
Deployment	Docker

🚀 Quick Start

Prerequisites

• Python 3.9+
• Docker (optional)

Local Development

# Clone the repository
git clone https://github.com/Romit23/Lead-Recommendation-MVP.git
cd Lead-Recommendation-MVP

# Set up virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate    # Windows

# Install dependencies
pip install -r requirements.txt

# Launch services
uvicorn main:app --reload & streamlit run app.py

Docker Deployment

docker-compose up --build

Access:

• Frontend: http://localhost:8501 (Please refresh the page a few times because the Hunter API has reached it's monthly free quota)
• Backend API: http://localhost:8000/docs