🔍 Data Finder — Company Intelligence Platform

Data Finder is a full-stack AI-powered platform that fetches, verifies, and manages company information at scale — search by city & industry, get real-time verified results, and export everything to Excel in one click.

🚀 Getting Started · 📖 API Docs · ✨ Features · 🤝 Contributing

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📋 Table of Contents

• Overview
• Features
• Architecture
• Tech Stack
• Prerequisites
• Installation
• Configuration
• Usage
• API Documentation
• Project Structure
• Contributing
• Security
• Future Enhancements
• License

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🌟 Overview

Data Finder solves a real-world problem: gathering verified, up-to-date company data at scale is slow, expensive, and error-prone. This platform combines OpenAI's GPT models with intelligent filtering and a clean React UI to deliver high-quality company intelligence — including operational status, location, website, and industry — in seconds.

Whether you're a researcher, sales team, or business analyst, Data Finder turns hours of manual research into an automated, reliable pipeline.

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✨ Features

Feature	Description
🤖 AI-Powered Extraction	Leverages OpenAI GPT to intelligently extract and verify company data with high accuracy
🌍 City + Industry Search	Filter companies by city and industry through a clean, intuitive form
✅ Smart Verification	Every result is tagged — Active, Acquired, or Closed
🚫 Duplicate Prevention	Built-in exclusion list management keeps your dataset clean
📊 One-Click Excel Export	Export formatted .xlsx files using Apache POI — CRM-ready
📁 Drag-and-Drop Upload	Batch-process companies via drag-and-drop file input
⚡ Real-Time Table View	Live-updating interactive data table with filtering & sorting
🔒 Secure by Design	All secrets stored in environment variables — never hardcoded

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🏗 Architecture

┌──────────────────────────────────────────────────────────┐
│                      CLIENT LAYER                        │
│                                                          │
│        ┌─────────────────────────────────────┐           │
│        │     React 18 Frontend (Port 3000)   │           │
│        │  Search Form · Data Table · Export  │           │
│        └──────────────────┬──────────────────┘           │
└─────────────────────────── │ ────────────────────────────┘
                             │  HTTP REST (JSON)
                             ▼
┌──────────────────────────────────────────────────────────┐
│                      SERVER LAYER                        │
│                                                          │
│     ┌───────────────────────────────────────────────┐    │
│     │    Spring Boot 3.5.3 Backend (Port 8081)      │    │
│     │  Controllers · Services · JPA Repositories   │    │
│     └─────────────────┬─────────────┬──────────────┘    │
└───────────────────────│─────────────│────────────────────┘
                        │             │
             ┌──────────▼───┐   ┌─────▼────────────┐
             │  MySQL 8.0   │   │  OpenAI GPT API  │
             │  (Persist)   │   │  (Extraction)    │
             └──────────────┘   └──────────────────┘

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🛠 Tech Stack

Layer	Technology	Version
Frontend	React	18.x
Frontend Lang	JavaScript ES6+	—
Backend	Spring Boot	3.5.3
Backend Lang	Java	17
Build Tool	Maven	3.8+
Database	MySQL	8.0
ORM	Spring Data JPA / Hibernate	—
AI Integration	OpenAI API (GPT)	Latest
File Processing	Apache POI	—
Security	Spring Security + Env Vars	—

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📋 Prerequisites

Requirement	Version	Link
JDK	17+	Download
Node.js	16+	Download
MySQL	8.0+	Download
Maven	3.8+	Download
OpenAI API Key	—	Get Key

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🚀 Installation

Step 1 — Clone the Repository

git clone https://github.com/Tushargg1/Data-Finder.git
cd Data-Finder

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Step 2 — Database Setup

CREATE DATABASE company_extractor;

CREATE USER 'df_user'@'localhost' IDENTIFIED BY 'your_secure_password';
GRANT ALL PRIVILEGES ON company_extractor.* TO 'df_user'@'localhost';
FLUSH PRIVILEGES;

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Step 3 — Backend Setup

cd company-backend

Set environment variables (Linux/macOS):

export DB_USERNAME=df_user
export DB_PASSWORD=your_secure_password
export OPENAI_API_KEY=sk-...your_key...

Set environment variables (Windows PowerShell):

$env:DB_USERNAME="df_user"
$env:DB_PASSWORD="your_secure_password"
$env:OPENAI_API_KEY="sk-...your_key..."

Build & Run:

mvn clean install
mvn spring-boot:run

✅ Backend running at: http://localhost:8081

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Step 4 — Frontend Setup

cd ../frontend
npm install
npm start

✅ Frontend running at: http://localhost:3000

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⚙ Configuration

Variable	Description	Required
DB_USERNAME	MySQL username	✅
DB_PASSWORD	MySQL password	✅
OPENAI_API_KEY	OpenAI secret key	✅
DB_URL	JDBC connection URL	Optional
SERVER_PORT	Backend port (default: 8081)	Optional

⚠️ Never commit credentials to version control. Add .env to .gitignore.

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📖 Usage

🔍 Search Companies

1. Open http://localhost:3000
2. Enter a City (e.g., Mumbai) and Industry (e.g., FinTech)
3. Click Extract Data — live results populate immediately

📊 Export to Excel

• Click Export to Excel — a formatted .xlsx file downloads automatically

📁 Batch Upload

• Drag and drop a company list file into the upload area
• Backend enriches each entry and displays results in the live table

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📡 API Documentation

Base URL: http://localhost:8081/api

Method	Endpoint	Description
POST	/companies/extract	Extract companies by city & industry
GET	/companies	Retrieve all stored companies
GET	/companies/{id}	Get a specific company by ID
DELETE	/companies/{id}	Delete a company record
GET	/companies/export	Download all data as Excel
POST	/companies/upload	Batch upload via file

Example Request

curl -X POST http://localhost:8081/api/companies/extract \
  -H "Content-Type: application/json" \
  -d '{
    "city": "Bangalore",
    "industry": "FinTech",
    "limit": 20
  }'

Example Response

{
  "status": "success",
  "count": 20,
  "data": [
    {
      "id": 1,
      "name": "Razorpay",
      "city": "Bangalore",
      "industry": "FinTech",
      "website": "https://razorpay.com",
      "status": "Active",
      "extractedAt": "2025-07-16T10:30:00Z"
    }
  ]
}

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📁 Project Structure

Data-Finder/
├── 📂 company-backend/                  # Spring Boot backend
│   └── src/main/java/com/company/
│       ├── controller/                  # REST Controllers
│       ├── service/                     # Business logic + AI calls
│       ├── repository/                  # JPA Repositories
│       ├── model/                       # Entity classes
│       └── config/                      # App & security config
│
├── 📂 frontend/                         # React frontend
│   └── src/
│       ├── components/                  # Reusable UI components
│       ├── pages/                       # Page views
│       ├── services/                    # Axios API service layer
│       └── App.js
│
└── 📄 README.md

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🤝 Contributing

Contributions are welcome and appreciated! 🎉

1. Fork the repository
2. Create your feature branch: git checkout -b feature/my-feature
3. Commit your changes: git commit -m "feat: add my feature"
4. Push to the branch: git push origin feature/my-feature
5. Open a Pull Request

Commit Convention

Prefix	Purpose
feat:	New feature
fix:	Bug fix
docs:	Documentation
refactor:	Code cleanup
test:	Tests
chore:	Maintenance

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🔒 Security

• API keys and DB credentials are never hardcoded — environment variables only
• Database access uses a scoped user with minimal privileges
• CORS is restricted to the frontend origin
• Found a vulnerability? Please open a private issue or contact the maintainer directly

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🔮 Future Enhancements

• 🔐 JWT-based user authentication & role management
• 📈 Analytics dashboard for extraction trends
• 🐳 Docker + Docker Compose for one-command deployment
• 📧 Scheduled email digest reports
• 🔗 CRM integrations (Salesforce, HubSpot)
• 🧪 Full test coverage (JUnit + React Testing Library)
• 📱 Progressive Web App (PWA) support
• 🌐 Multi-language UI support

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

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Made with ❤️ by Tushar