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diff --git a/.DS_Store b/.DS_Store
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diff --git a/docs/index.html b/docs/index.html
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+<!DOCTYPE html>
+<html>
+<head>
+    <title>AML Monitoring Engine</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            line-height: 1.6;
+            margin: 0;
+            padding: 20px;
+            background-color: #f4f4f4;
+        }
+        h1, h2 {
+            color: #333;
+        }
+        nav {
+            background: #333;
+            color: #fff;
+            padding: 10px;
+        }
+        nav a {
+            color: #fff;
+            margin: 0 10px;
+            text-decoration: none;
+        }
+        nav a:hover {
+            text-decoration: underline;
+        }
+        section {
+            margin-bottom: 20px;
+        }
+    </style>
+</head>
+<body>
+    <nav>
+        <a href="#overview">Overview</a>
+        <a href="#architecture">System Architecture</a>
+        <a href="#modules">Modules</a>
+        <a href="#technologies">Technologies</a>
+        <a href="#interface">User Interface</a>
+        <a href="#testing">Testing</a>
+        <a href="#maintenance">Maintenance</a>
+    </nav>
+
+    <h1>AML Monitoring Engine</h1>
+    <p>Welcome to the documentation for the AML Monitoring Engine, a deep learning-based system for anti-money laundering.</p>
+
+    <section id="overview">
+        <h2>Overview</h2>
+        <p>The AML Monitoring Engine leverages deep learning to detect and combat suspicious financial transactions.</p>
+    </section>
+
+    <section id="architecture">
+        <h2>System Architecture</h2>
+        <p>Our system comprises six key components: Data Collection, Model Training, Real-Time Monitoring, Risk Assessment, Compliance, and Integration.</p>
+    </section>
+
+    <section id="modules">
+        <h2>Modules</h2>
+        <p>Explore detailed descriptions of each module, including their functionalities and designs.</p>
+    </section>
+
+    <section id="technologies">
+        <h2>Technologies</h2>
+        <p>We use cutting-edge deep learning algorithms, including CNNs and RNNs, for superior pattern recognition.</p>
+    </section>
+
+    <section id="interface">
+        <h2>User Interface</h2>
+        <p>Our dashboards provide real-time insights and detailed transaction reports for enhanced usability.</p>
+    </section>
+
+    <section id="testing">
+        <h2>Testing</h2>
+        <p>Our system undergoes rigorous unit, integration, performance, and security testing to ensure reliability.</p>
+    </section>
+
+    <section id="maintenance">
+        <h2>Maintenance</h2>
+        <p>Regular updates ensure continued compliance with regulations and optimal system performance.</p>
+    </section>
+</body>
+</html>
+
diff --git a/docs/index.md b/docs/index.md
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+# AML Monitoring Engine  
+
+Welcome to the **AML Monitoring Engine** documentation website! Explore the various components and features of our deep learning-based anti-money laundering system.
+
+## Table of Contents  
+- [Overview](#overview)  
+- [System Architecture](#system-architecture)  
+- [Modules](#modules)  
+  - [Data Collection and Preprocessing](#data-collection-and-preprocessing)  
+  - [Feature Extraction](#feature-extraction)  
+  - [Model Training](#model-training)  
+  - [Early Warning and Risk Assessment](#early-warning-and-risk-assessment)  
+- [Technologies](#technologies)  
+- [User Interface](#user-interface)  
+- [Database Design](#database-design)  
+- [Testing](#testing)  
+- [Software Maintenance](#software-maintenance)  
+
+---
+
+## Overview  
+The **AML Monitoring Engine** leverages deep learning to detect suspicious transactions and combat money laundering activities. 
+
+[Learn More](#system-architecture)
+
+---
+
+## System Architecture  
+Explore how the engine works across its six main modules:  
+1. Data Collection and Preprocessing.  
+2. Deep Learning Model Training.  
+3. Real-Time Monitoring and Anomaly Detection.  
+4. Decision Support and Risk Assessment.  
+5. Compliance and Privacy Protection.  
+6. Integration and Interfaces.
+
+[View Details](#modules)
+
+---
+
+## Modules  
+### Data Collection and Preprocessing  
+Processes raw financial data from various systems.
+
+[Learn More](#data-collection-and-preprocessing)
+
+### Feature Extraction  
+Extracts meaningful insights for model training.
+
+[Learn More](#feature-extraction)
+
+### Model Training  
+Builds predictive deep learning models.
+
+[Learn More](#model-training)
+
+### Early Warning and Risk Assessment  
+Detects anomalies and supports decision-making.
+
+[Learn More](#early-warning-and-risk-assessment)
+
+---
+
+## Technologies  
+Explore the technologies powering our system, including CNNs, RNNs, and other deep learning techniques.
+
+---
+
+## User Interface  
+User-friendly dashboards provide real-time insights and reporting tools.
+
+---
+
+## Database Design  
+An optimized schema supports high-volume transaction data efficiently.
+
+---
+
+## Testing  
+Detailed testing plans ensure system reliability and performance.
+
+---
+
+## Software Maintenance  
+Guidelines for ongoing updates and regulatory compliance.
+
+---
+
+### License  
+This project is proprietary software. All rights reserved.
+