RuleGraph: From Policies to SQL Compliance Checks Using LLM, RAG & Knowledge Graphs

Description

🚀 **RuleGraph** is an end-to-end AI pipeline that transforms **policy documents** into **automated SQL compliance checks** — powered by **Large Language Models (LLMs)**, **Graph-RAG**, and **Knowledge Graphs (Neo4j)**. This video walks through the **complete notebook implementation**, showing how unstructured text is converted into machine-executable rules, stored in a Neo4j graph, and used to generate context-aware SQL for real-time compliance validation. --- ### 🔍 **What You’ll Learn** * How to extract structured rules from policy PDFs using LLMs (Gemini 1.5 Flash) * How to encode rules into a Neo4j knowledge graph * How Graph-RAG retrieves contextually relevant rules * How Mistral generates executable SQL queries from retrieved rules * How to run compliance checks automatically against real databases --- ### 💾 **Resources** 📘 **GitHub (Notebook & Code):** 👉 [https://github.com/mmahin/RuleGraph-From-Policies-to-SQL-Compliance-Checks-Using-LLM-RAG-and-Context-Learning](https://github.com/mmahin/RuleGraph-From-Policies-to-SQL-Compliance-Checks-Using-LLM-RAG-and-Context-Learning) ✍️ **Medium Article (Full Explanation):** 👉 [https://medium.com/@mdmahin3/rulegraph-from-policies-to-sql-compliance-checks-using-llm-rag-and-context-learning-ec54f0921198](https://medium.com/@mdmahin3/rulegraph-from-policies-to-sql-compliance-checks-using-llm-rag-and-context-learning-ec54f0921198) --- ### ⚙️ **Tech Stack** * **LLMs:** Gemini 1.5 Flash, Mistral * **Knowledge Graph:** Neo4j Aura * **Database Layer:** SQLAlchemy + MySQL * **Retrieval:** Graph-RAG + Tabular-RAG * **Framework:** Python + Jupyter/Colab --- ### 🧩 **Keywords / Tags** `LLM` • `RAG` • `Neo4j` • `Compliance` • `Knowledge Graph` • `SQL Automation` • `AI Governance` • `Policy AI` • `Gemini` • `Mistral` • `Colab Project` • `Machine Learning`