🛡️ Intelligent Compliance Assistant

An AI-powered compliance automation system that analyzes regulatory documents and data to help organizations ensure policy and regulatory adherence. Built with a modern microservice architecture, scalable backend APIs, and containerized deployment.

📋 Table of Contents

Overview
Key Features
Architecture
Tech Stack
Project Structure
Getting Started
API Documentation
Future Roadmap
Contributing
Author

🎯 Overview

The Intelligent Compliance Assistant automates the complex process of regulatory compliance checking by:

Automating compliance checks using AI-driven logic and rules engines
Processing both structured and unstructured regulatory data from multiple sources
Providing scalable REST APIs for seamless integration with existing systems
Ensuring reliable deployment through Docker containerization

Perfect for: Financial institutions, healthcare organizations, legal firms, and any enterprise dealing with complex regulatory frameworks.

✨ Key Features

🤖 AI-Powered Analysis

Intelligent document parsing and classification
Automated policy violation detection
Natural language processing for regulatory text
Extensible architecture for ML/NLP enhancements

🔧 Robust Backend

RESTful API design following industry best practices
Modular microservice architecture for horizontal scaling
Dual database support (SQL + NoSQL) for optimal data handling
Comprehensive error handling and logging

🎨 User-Friendly Frontend

Intuitive React-based dashboard
Real-time compliance status monitoring
Interactive data visualization
Responsive design for desktop and mobile

🐳 DevOps Ready

Fully containerized with Docker
Environment-agnostic deployment
Easy scaling and orchestration
Production-ready configurations

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐
│                     Frontend Layer                       │
│                   (React.js Dashboard)                   │
└────────────────────┬────────────────────────────────────┘
                     │ HTTP/REST
┌────────────────────▼────────────────────────────────────┐
│                   API Gateway Layer                      │
│              (Spring Boot Backend APIs)                  │
└────────────────────┬────────────────────────────────────┘
                     │ Internal API
┌────────────────────▼────────────────────────────────────┐
│                AI/ML Service Layer                       │
│        (Python-based Compliance Intelligence)            │
└────────────┬───────────────────────┬────────────────────┘
             │                       │
┌────────────▼────────┐   ┌─────────▼──────────┐
│   PostgreSQL DB     │   │    MongoDB         │
│  (Structured Data)  │   │  (Document Store)  │
└─────────────────────┘   └────────────────────┘
             │                       │
             └───────────┬───────────┘
                         │
                ┌────────▼─────────┐
                │  Docker Engine   │
                │  (Orchestration) │
                └──────────────────┘

Architecture Highlights

Frontend: React.js with modern UI/UX patterns
API Layer: Spring Boot microservices with RESTful endpoints
AI Engine: Python-based intelligent processing (ready for LLM integration)
Data Storage: Hybrid approach using PostgreSQL (relational) + MongoDB (documents)
Deployment: Docker containerization for consistent environments

⚙️ Tech Stack

Layer	Technologies
Frontend	React.js, JavaScript, CSS3, HTML5
Backend	Spring Boot (Java), RESTful APIs
AI/ML	Python 3.x, NumPy, Pandas
Database	PostgreSQL, MongoDB
DevOps	Docker, Docker Compose
Version Control	Git, GitHub

📂 Project Structure

intelligent-compliance-assistant/
│
├── frontend/                 # React.js dashboard application
│   ├── src/
│   ├── public/
│   └── package.json
│
├── backend/                  # Spring Boot REST APIs
│   ├── src/
│   ├── pom.xml
│   └── application.properties
│
├── ai-service/              # Python AI/ML services
│   ├── models/              # ML models and algorithms
│   ├── services/            # Business logic
│   ├── utils/               # Helper functions
│   └── requirements.txt
│
├── data/                    # Sample datasets and documents
│   ├── regulations/         # Regulatory documents
│   └── test-cases/          # Test compliance scenarios
│
├── docker/                  # Docker configurations
│   ├── docker-compose.yml
│   ├── Dockerfile.backend
│   ├── Dockerfile.frontend
│   └── Dockerfile.ai
│
├── .gitignore
└── README.md

🚀 Getting Started

Prerequisites

Docker (version 20.10+)
Docker Compose (version 1.29+)
Node.js (version 16+ for local development)
Java 11+ (for backend development)
Python 3.9+ (for AI service development)

Quick Start with Docker

Clone the repository

git clone https://github.com/M1325-source/intelligent-compliance-assistant.git
cd intelligent-compliance-assistant

Build and run with Docker Compose
```
cd docker
docker-compose up --build
```
Access the application
- Frontend: http://localhost:3000
- Backend API: http://localhost:8080
- AI Service: http://localhost:5000

Local Development Setup

Backend (Spring Boot)

cd backend
./mvnw spring-boot:run

Frontend (React)

cd frontend
npm install
npm start

AI Service (Python)

cd ai-service
pip install -r requirements.txt
python app.py

📚 API Documentation

Core Endpoints

Compliance Analysis

POST /api/v1/compliance/analyze
Content-Type: application/json

{
  "documentId": "string",
  "regulationType": "string",
  "content": "string"
}

Document Upload

POST /api/v1/documents/upload
Content-Type: multipart/form-data

file: <binary>

Compliance Report

GET /api/v1/compliance/report/{documentId}

Full API documentation available at: http://localhost:8080/swagger-ui.html

🔮 Future Roadmap

Phase 1 (Q2 2026)

LLM integration for advanced regulatory reasoning (RAG architecture)
Real-time compliance monitoring dashboard
Multi-language support for international regulations

Phase 2 (Q3 2026)

CI/CD pipeline with GitHub Actions
Role-based access control (RBAC)
Audit trail and compliance history tracking

Phase 3 (Q4 2026)

Cloud deployment (AWS/GCP/Azure)
Integration with popular compliance tools
Advanced analytics and reporting features
Mobile application support

Long-term Vision

AI-powered regulatory change detection
Predictive compliance risk assessment
Industry-specific compliance templates
Enterprise SSO integration

🤝 Contributing

Contributions are welcome! Please follow these steps:

Fork the repository
Create a feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

Please ensure your code follows the project's coding standards and includes appropriate tests.

📝 License

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

👩‍💻 Author

Manisha Priya
Fullstack Developer | DevOps | AI/ML engineer | Cloud Architect

Passionate about building production-ready, scalable systems that solve real-world problems.

📧 Email: your-email@example.com
🐙 GitHub: @M1325-source

🙏 Acknowledgments

Thanks to all contributors who have helped shape this project
Inspired by the need for automated compliance in modern enterprises
Built with modern open-source technologies

📞 Support

For support, please:

Open an issue on GitHub
Contact the maintainer via email
Check the Wiki for documentation

⭐ If you find this project useful, please consider giving it a star!

Last Updated: February 2026

Name		Name	Last commit message	Last commit date
ai-service		ai-service
backend		backend
data		data
docker		docker
frontend		frontend
.gitignore		.gitignore
README.md		README.md

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