Automated Answering System for Enterprise Query Integration
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Solution Overview
Problem
Current automated answering systems for enterprise-related queries are inefficient in providing relevant and contextual responses, especially in mobile messaging contexts, where they fail to effectively retrieve and present information in a user-friendly manner.
Innovation Solution
A computer-implemented automated answering system (AAS) that receives client-side application messages, parses user queries for enterprise-related information, determines relevant information sources, and generates natural-language text messages or voice responses, incorporating user identification and permissions to provide single, contextually relevant answers, with optional user feedback to refine responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If automated answering systems retrieve information from multiple enterprise applications, then the quantity and comprehensiveness of information increases, but the complexity of integrating and presenting information from multiple sources increases
Solution Approach 1:
The patent introduces an automated answering system as an intermediary layer between users and multiple enterprise applications. This system receives user queries, automatically retrieves information from relevant enterprise applications through integrated interfaces, processes the retrieved data, and presents unified responses to users. The intermediary handles the complexity of multi-source integration internally while providing simplified access to users.
Solution Approach 2:
The automated answering system is designed as a universal platform capable of interfacing with multiple different enterprise applications simultaneously. It performs multiple functions including query parsing, information retrieval from diverse sources, data integration, and response generation, thereby reducing the need for separate systems for each application.
2Loss of information
If the system provides detailed and comprehensive responses, then the information completeness improves, but the readability and user-friendliness of responses deteriorates
Solution Approach 1:
The system extracts and presents only the most relevant information from comprehensive data sources. It identifies key facts and details that directly answer user queries while filtering out extraneous information. This extraction process maintains information completeness for the essential elements while improving readability by eliminating unnecessary complexity.
Solution Approach 2:
The response generation applies local quality by adapting the level of detail and presentation style to the specific needs of each query. Different types of questions receive appropriately tailored responses - some more detailed, others more concise - based on the nature of the inquiry and the importance of various information elements.
3Adaptability or versatility
If the system integrates with multiple enterprise applications, then the versatility and scope of answerable queries improves, but the difficulty of system implementation and maintenance increases
Solution Approach 1:
The system architecture is segmented into modular components: query reception module, information retrieval module with separate interfaces for each enterprise application, processing module, and response generation module. This segmentation allows independent development, testing, and maintenance of each component while maintaining overall system versatility through standardized integration interfaces.
Data Source
AI summary
In one embodiment, a computer-implemented method of a designated automated answering system (AAS) includes receiving a client-side application message to an AAS. The AAS includes a server-side entity managed by an enterprise. The client-side application message comprises a user's query for enterprise-related information. The client-side application message are parsed to identify user-identification data. A step includes determining one or more information sources relevant to the query for enterprise-related information. At least one or more information sources are queried. A step includes receiving a query information from the at least one or more information sources. The query information is relevant to the user's query. A natural-language text message that responds to the user's query is generated. The natural-language text message includes a single response.