Investor-Entrepreneur Connection System

This project simulates a multi-database investment platform that manages investors, entrepreneurs, meetings, and smart recommendations — by combining PostgreSQL, MongoDB, and Neo4j.

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📚 Tech Stack

• PostgreSQL – stores structured data (investors, entrepreneurs, investments)
• MongoDB – logs flexible meeting feedback
• Neo4j – models relationships and generates graph-based recommendations
• Python 3.12+ – connects and orchestrates all three databases
• Docker – spins up PostgreSQL, MongoDB, and Neo4j with minimal setup

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🔧 Core Features

✅ Match investors to entrepreneurs
✅ Log investor-entrepreneur meetings
✅ View personalized dashboards
✅ Search startups by industry & ratings
✅ Generate platform-wide insights
✅ Permanently delete users and clean data

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🔧 Features Implemented

• Schedule and log investor-entrepreneur meetings
• Analyze meeting feedback and generate follow-up steps
• Match investors with startups based on shared industry, stage, and history
• Visualize relationship network using Neo4j
• Combine queries across all 3 databases

📁 Project Structure

  |-- project\
        |backend\
        |     |-- data\ -------------------------------- CSV and JSON data
        |     |-- db\ ---------------------------------- Database connection scripts
        |     |-- functions\ --------------------------- Core logic touching 3 data models
        |     |-- main.py ------------------------------ Entry point to demo
              |-- requirements.txt --------------------- #All Python dependencies 
  all features
  |     |-- .env # Environment config (NOT committed)
  |     |-- README.md
        |-- .gitignore # Ignore DB volumes, .env, temp files
        |-- docker-compose.yml # Launches PostgreSQL, MongoDB, and Neo4j

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⚙️ Setup Instructions

1. Start the Databases via Docker

docker-compose up -d