Issue Queue Recommendations Using Generative Output Panels
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Solution Overview
Problem
Existing issue tracking systems fail to provide efficient interfaces for managing and generating content that can mitigate the technical deficiencies of some traditional interfaces and systems.
Innovation Solution
A graphical user interface that includes a recommendation panel for an issue tracking platform with a recommendation method, which includes a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional issue tracking interfaces are used to manage and access issue data, then the system can store and organize issues, but the information becomes difficult to access efficiently and compile when managing large quantities of issues
Solution Approach 1:
The patent replaces manual mechanical search and compilation processes with an automated generative output engine that uses natural language processing and machine learning to automatically retrieve, synthesize, and present issue information, transforming the manual information gathering process into an automated intelligent system
Solution Approach 2:
The system enables self-service by automatically generating comprehensive issue summaries, recommendations, and insights without requiring users to manually search through databases or compile information, allowing the system to serve itself in organizing and presenting issue data
2Loss of information
If manual methods are used to compile and access issue information from disparate locations, then all issue data can be accessed, but the process becomes inefficient and time-consuming
Solution Approach 1:
The generative output engine serves multiple functions simultaneously: it searches disparate data sources, compiles information, generates summaries, provides recommendations, and presents results in a unified interface, replacing multiple separate manual processes with a single multi-functional system
Solution Approach 2:
The patent introduces an intermediary generative output engine that acts as a mediator between disparate issue data sources and users, automatically retrieving and synthesizing information from multiple locations and presenting it in a consolidated, easy-to-access format
3Quantity of substance
If a large system stores extensive issue data, then comprehensive information is available, but the information becomes difficult to access in an efficient interface
Solution Approach 1:
The system extracts only the most relevant and essential issue information from the large stored database, pulling out key details, patterns, and insights while filtering out unnecessary data, and presents this extracted information in a concise, easily accessible format
Data Source
AI summary
Embodiments described herein are directed to systems and methods for modifying issue groups for a graphical user interface of an issue tracking platform. An issue dashboard graphical user interface can include multiple sets of issue tickets, where each set of issue tickets is grouped in accordance with a queue definition. A prompt can be generated and include predetermined prompt text including a recommendation criteria, data extracted from the multiple sets of issue tickets including an issue title and assignee, and data associated with a current user account authenticated with respect to the frontend application. A group modification interface can be displayed and include at least a portion of a generative response. In response to a user input, a new issue ticket group can be created by performing a structured query on issues managed by the issue tracking platform and saving the structured query as a new queue definition.