AI Software Onboarding Detection and Remediation Before Deployment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
There is a need for a secure and efficient method to onboard software into a networked computing environment, addressing issues such as performance, compatibility, and security vulnerabilities during the onboarding process, which are often difficult to identify and time-intensive.
Innovation Solution
An artificial intelligence (AI)-based system that analyzes the target computing environment and software parameters to detect potential issues, predicts their effects, and automatically generates remediation processes, including code changes and updates, to prevent and resolve these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual onboarding and deployment processes are used, then flexibility and control are maintained, but time consumption and resource requirements increase significantly
Solution Approach 1:
The system performs preliminary analysis of the target computing environment and software packet parameters before actual deployment. The AI engine proactively identifies potential compatibility issues, security vulnerabilities, and performance problems in advance, allowing remediation to be prepared beforehand rather than reacting to issues after deployment occurs.
Solution Approach 2:
The patent replaces manual mechanical review processes with an automated AI-based analysis system. The AI engine automatically compares software parameters against environment parameters, detects issues, and generates remediation recommendations without requiring manual inspection, thereby significantly reducing time consumption while maintaining thoroughness.
2Reliability
If comprehensive security scanning and analysis are performed during onboarding, then security vulnerabilities are detected, but the onboarding process becomes more time-consuming
Solution Approach 1:
The system replaces time-consuming manual security scanning with automated AI-based analysis. The AI engine rapidly processes software packets, compares them against known vulnerability patterns, and identifies security issues without the time constraints of manual review, thereby maintaining high detection accuracy while reducing overall onboarding time.
Solution Approach 2:
Security analysis is performed as a preliminary step during the onboarding process rather than as a separate post-deployment activity. The AI engine identifies security vulnerabilities before the software is fully deployed, allowing for proactive remediation and avoiding the need for time-consuming security patches after deployment.
3Measurement precision
If detailed parameter comparison and AI analysis are conducted, then issue detection accuracy improves, but system complexity and computational resources increase
Solution Approach 1:
The system segments the analysis process into distinct functional modules: environment parameter extraction, software packet parameter extraction, AI-based comparison engine, and remediation generation. This modular segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining high detection accuracy through comprehensive parameter comparison.
Data Source
AI summary
A system is provided for artificial intelligence-based detection and remediation of issues during software onboarding and deployment. In particular, the system may comprise an artificial intelligence (“AI”) engine that may be configured to identify gaps and/or potential issues in an onboarding and/or integration process for a computing software solution. In this regard, the AI engine may identify the variables and/or parameters of the target computing environment and the variable and/or parameters of the incoming software. Based on the variables and/or parameters, the AI engine may determine the potential issues that may arise during onboarding, how such issues may affect the target computing environment, and/or the remediation processes that may be required to resolve the issues. In this way, the system may provide an efficient way to identify and remediate potential issues during the software onboarding process.