Change Reconciliation Platform for Auditing Server Change Steps
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Solution Overview
Problem
Existing change management systems lack accountability and transparency in confirming the actual actions performed on a server, leading to potential vulnerabilities and inefficiencies due to missed or incorrectly sequenced steps.
Innovation Solution
A computer system employing a task mining agent, intelligence reconnaissance service, and insight service to passively log, filter, and analyze actions against prescribed steps, generating real-time reconciliation insights and notifications to ensure correct and efficient change implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If laborious manual reviews are used to confirm actual steps versus prescribed steps, then accountability and transparency are improved, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The patent replaces manual mechanical review processes with automated task mining agents that use machine learning to capture, analyze, and reconcile task execution data. The system automatically compares prescribed tasks against actual user actions using AI/ML algorithms, eliminating the need for laborious human reviews while maintaining or improving accountability.
Solution Approach 2:
The patent introduces task mining agents as intermediaries between users and the change management system. These agents passively capture user actions, process them through intelligence reconnaissance services, and provide automated reconciliation insights, serving as a mediator that automates the verification process without requiring manual intervention.
2Measurement precision
If detailed logging of all user actions is implemented, then measurement precision and insight quality are improved, but system resource consumption and complexity increase
Solution Approach 1:
The patent implements partial logging by focusing task mining agents on capturing only relevant task-related actions rather than all possible user activities. The system selectively monitors and logs actions that are pertinent to change management processes, reducing data volume and processing complexity while maintaining sufficient measurement precision for reconciliation purposes.
Solution Approach 2:
The patent segments the logging and analysis functions into modular components: task mining agents for data collection, intelligence reconnaissance services for processing, and insight services for reconciliation. This segmentation reduces system complexity by dividing the monolithic logging system into manageable, independently configurable modules.
3Speed
If real-time analysis and notification services are deployed, then risk identification speed is improved, but computational resource usage increases
Solution Approach 1:
The patent implements periodic or event-triggered analysis rather than continuous real-time monitoring. The task mining agents and intelligence services analyze captured actions at strategic intervals or when specific events occur, reducing computational resource usage while maintaining effective risk identification speed through targeted analysis bursts.
Data Source
AI summary
A computer system for a change management intelligent reconciliation platform configured to support the change management process. The computer system includes a task mining agent, an intelligence reconnaissance service, an insight service, and a notification service. The task mining agent is programmed to passively log user actions related to a change request. The intelligence reconnaissance service filters the logged actions and identifies patterns and anomalies in user behavior. The insight service analyzes the differences between the filtered actions and one or more prescribed actions related to the change request, and generates one or more reconciliation insights based on the results of the analysis. The notification service generates one or more notifications regarding the generated reconciliation insights to provides valuable insights into user behavior data and to aid in identifying potential risks or issues during the change implementation process.