Detect Reoccurring Issue
This action allows Neo to identify whether an incoming ticket is part of a larger, recurring issue. Neo analyzes recent ticket patterns, recognizing common themes, such as multiple “can’t access Outlook” tickets that might be related to an underlying DNS problem. You can configure Neo to consider specific time frames, similarity thresholds, and the minimum number of incidents needed to flag a recurring issue.
How it Works?
Set the time period, similarity level, and minimum number of incidents that Neo should use to identify recurring issues.
Neo scans incoming tickets and compares them with recent ticket data to find patterns that suggest a broader problem.
When a recurring issue is detected, Neo flags it for review, suggesting that related tickets should be bundled or merged to avoid redundant work by different technicians.
Benefits
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Efficient Problem ManagementIdentifies recurring issues early, reducing redundant efforts across multiple tickets.
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Improved Resource AllocationAllows technicians to focus on resolving the root cause rather than repeatedly addressing similar issues.
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Faster ResolutionsHelps streamline ticket bundling, leading to quicker and more consistent problem resolutions.
FAQs
Neo uses AI models to analyze ticket content, descriptions, and resolution steps. It groups similar tickets together when patterns suggest a broader underlying issue.
Yes, you can customize the time frame, similarity threshold, and minimum number of incidents that trigger a recurring issue flag. This ensures Neo’s detection aligns with your operational needs.
Neo can notify the team by email or in Microsoft Teams, or can also put an internal note in the flagged ticket with the ticket id of similar tickets that can be part of the same issue.
Absolutely. Neo can identify complex patterns, including issues with different descriptions but related root causes. This helps avoid fragmented problem-solving efforts across teams.
Neo performs continuous monitoring based on your set parameters as new tickets come in.
