README.md

---
license: other
language: en
tags:
- cybersecurity
- grc
- compliance
- rag
- vector-database
- chroma
- nca
---

# NCA ECC Compliance Vector Database (VDB)

<p>
    This repository hosts a high-quality, pre-processed **Vector Database (VDB)**, specifically structured to support 
    Retrieval-Augmented Generation (RAG) applications in the domain of Cybersecurity Governance, Risk, and Compliance (**GRC**). 
</p>
<p>
    The VDB serves as the authoritative knowledge base for the **AI-GRC-Assistant** project, providing context on official regulatory requirements.
</p>

## 🌟 Dataset Overview

| Detail | Value |
| :--- | :--- |
| **Dataset Name** | NCA ECC Compliance Vector Database (VDB) |
| **VDB Technology** | Chroma DB (Persistent Client) |
| **Embedding Model** | `sentence-transformers` (Generic model type) |
| **Data Source** | National Cybersecurity Authority (NCA) of Saudi Arabia |
| **File Asset** | `chroma_db` (Contains persistent Chroma DB files) |
| **Primary Use Case** | RAG-based AI Advisory for GRC compliance. |

## 📜 Data Sourcing and Public Availability

<p>
    All textual data used for embedding is derived from the official public document: 
    <strong>"Guide to Essential Cybersecurity Controls (ECC) Implementation"</strong>.
    This document is publicly available on the NCA website and is intended for use by national organizations, ensuring the assistant’s advice is based on open and verifiable regulatory standards.
</p>

- **Official Source Link:** [ECC Implementation Guide (NCA)](https://nca.gov.sa/en/regulatory-documents/controls-list/ecc/)

## 🛠️ Usage and Integration

<p>
    This asset is designed to be loaded into a Python RAG pipeline using <strong>Chroma DB</strong> and the specified sentence-transformer embedding method. Ensure the Python environment has <code>chromadb</code> and <code>sentence-transformers</code> installed.
</p>

## 📧 Contact

* **Author:** Meshal Qushaym (MQushaym)
* **Email:** [email protected]