LLM Cloud Configuration Assistant for Distributed Data Retrieval
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Solution Overview
Problem
Managing and querying configuration data in cloud environments is complex due to their distributed nature and scale, often requiring manual processes or specialized tools, and there is a need for efficient data retrieval and analysis to support informed decision-making.
Innovation Solution
An AI assistant utilizing Large Language Models (LLMs) processes natural language queries to provide responses on cloud environment configurations, including comparisons and generating application segments based on transactional and location data, without accessing enterprise data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes or specialized tools are used to query configuration data, then data retrieval can be performed, but the complexity of cloud environments makes the process inefficient and time-consuming
Solution Approach 1:
The patent introduces an AI assistant as an intermediary layer between users and complex cloud configuration data. The assistant processes natural language queries, translates them into appropriate search operations, and retrieves relevant configuration information, thereby simplifying the interaction with complex cloud environments without requiring users to directly manage the complexity
Solution Approach 2:
The patent replaces manual mechanical processes of querying configuration data with an automated AI-based system. Instead of requiring users to manually navigate through complex cloud interfaces or write specialized queries, the system uses natural language processing and AI models to automatically retrieve and present relevant configuration information, significantly improving efficiency
2Adaptability or versatility
If specialized tools tailored for specific cloud platforms are used, then data retrieval can be performed, but adaptability to different cloud environments and services is limited
Solution Approach 1:
The patent implements a universal AI assistant that can query configuration data across multiple different cloud platforms and services. The system maintains a comprehensive knowledge base of cloud services and configurations, enabling it to understand and retrieve information from various cloud providers without requiring separate specialized tools for each platform, thereby achieving multi-functionality and broad adaptability
3Loss of information
If detailed configuration data is retrieved and analyzed, then informed decision-making is enabled, but the volume of data and processing requirements increase
Solution Approach 1:
The patent applies information extraction techniques to selectively retrieve only the relevant configuration data needed to answer user queries. Instead of returning entire datasets, the AI assistant analyzes the query, identifies pertinent configuration parameters, and extracts only those specific pieces of information from the cloud environment, significantly reducing the quantity of data transmitted and processed while maintaining complete information accessibility for the user's specific needs
Solution Approach 2:
The system performs preliminary analysis of configuration data before presenting it to users. The AI assistant pre-processes and organizes configuration information, indexing and structuring it in advance so that when queries are received, the system can quickly retrieve and present only the relevant pre-organized information, reducing the processing burden and data volume required for each query while ensuring comprehensive information availability
Data Source
AI summary
Systems and methods for a cloud environment configuration Artificial Intelligence (AI) assistant include receiving a query from a user associated with an enterprise in natural language, the query being associated with one or more configurations within a cloud environment of the enterprise; processing the query via one or more Large Language Models (LLMs); and providing a response to the query, wherein the response comprises data associated with the one or more configurations based on the query and a feedback mechanism for obtaining feedback from the user based on the response.