Knowledge Suggestion Engine
Surfaces relevant knowledge articles and past incident resolutions for active IT service tickets based on contextual analysis.
Capabilities
- • Searches knowledge base articles using semantic understanding, not just keywords
- • Retrieves past incident resolutions with similar symptoms, affected systems, or root causes
- • Ranks suggestions by relevance, recency, and resolution success rate
- • Provides resolution confidence scores to help technicians prioritize approaches
Overview
The Knowledge Suggestion Engine surfaces the most relevant solutions for active IT service tickets — drawing from both formal knowledge base articles and past incident resolutions. It reduces the time technicians spend searching for solutions and ensures institutional knowledge is applied consistently.
How It Works
When a ticket is classified and assigned, the suggestion engine analyzes the ticket description, affected systems, error codes, and user context to find relevant solutions. It searches both the knowledge base and historical ticket resolutions using semantic understanding — finding relevant content even when the terminology differs from the current ticket. Suggestions are ranked by relevance, recency, and past resolution success rate.
The engine learns from technician actions — which suggestions led to successful resolutions — continuously improving its ranking to surface the most helpful content first.