Knowledge Graph Compliance Search With AI Chatbot Navigation
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Solution Overview
Problem
Existing methods for managing and complying with complex regulatory, standards, and requirements are inefficient and error-prone, particularly for entities navigating these standards for the first time or adapting to their rapid evolution.
Innovation Solution
A system utilizing an object-oriented knowledge graph data structure integrated with advanced neural networks and artificial intelligence mechanisms to convert regulatory documents into a JSON format, represent them as a knowledge graph, and provide a user-centric search experience with an AI chatbot for streamlined compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If regulatory documents are stored in traditional text-based formats with hierarchical structures, then the documents can be easily stored and retrieved, but the complexity of navigating and understanding the regulations increases significantly
Solution Approach 1:
The patent introduces an intermediary layer between the raw regulatory text and the user interface. This intermediary processes the hierarchical regulatory structure and presents it in a simplified, user-friendly format, thereby reducing the perceived complexity while maintaining the underlying structure for reference.
Solution Approach 2:
The system combines multiple data structures and processing methods to create a composite representation of regulatory documents. By integrating hierarchical parsing, keyword indexing, and relationship mapping, the system creates a multi-layered approach that simplifies navigation while preserving the full complexity of the original regulations when needed.
2Reliability
If advanced neural networks and AI mechanisms are integrated into the system, then the accuracy and adaptability of compliance assistance improves, but the device complexity and computational requirements increase
Solution Approach 1:
The AI system is divided into distinct functional modules including natural language processing components, knowledge graph construction modules, and compliance recommendation engines. Each module handles specific tasks independently, which manages complexity while collectively providing high accuracy through their coordinated operation.
Solution Approach 2:
The system performs preliminary processing of regulatory documents during ingestion, pre-computing knowledge graphs, entity relationships, and potential compliance issues. This advance preparation reduces the complexity of real-time query processing and enables faster, more accurate responses when users seek compliance assistance.
3Ease of operation
If the system processes and adapts output dynamically based on user needs, then the ease of use and user satisfaction improves, but the processing time and computational resources increase
Solution Approach 1:
The system pre-processes regulatory documents and builds knowledge structures in advance, so that when users submit queries, the system can quickly retrieve and adapt pre-computed information rather than processing everything from scratch. This significantly reduces response time while maintaining dynamic adaptation capabilities.
Solution Approach 2:
The system applies dynamic processing selectively based on user needs and query types. Not all queries require the same level of computational adaptation - simple lookups use pre-computed results while complex compliance questions trigger more intensive processing, optimizing the balance between responsiveness and accuracy.
Data Source
AI summary
Computerized system and method for facilitating compliance with regulations, standards and/or requirements employ graph database systems and knowledge graph (KG) structures and storage in JavaScript Object Notation (JSON) format for executing searches and displaying requested information in a manner that preserves the hierarchy of the regulatory, standards and/or requirements documents, Artificial intelligence (AI) chatbot components are also implemented which allow for receipt of prompts relating to a the regulatory, standards and/or requirements documents, and provide the prompt to the AI chatbot, and providing an answer to the prompts.