The Tickets tab serves as ServiceAI's comprehensive ticket analysis center, transforming raw ticketing/PSA ticket data into actionable intelligence that drives AI deployment readiness and service desk optimization.
This section provides ServiceAI users with deep insights into individual ticket patterns, agent performance, and documentation gaps that directly impact both current service delivery and future AI automation capabilities.
- The Strategic Purpose of Ticket Analysis
- Understanding the Tickets Grid
- Individual Ticket Analysis and Intelligence
- Available Actions and Business Impact
The Strategic Purpose of Ticket Analysis
The Tickets tab converts historical ticket data from your connected PSA system into forward-looking insights that help MSPs identify which support scenarios are ready for AI automation and which require continued human expertise. It allows you to:
Enable Data-Driven Service Desk Management
- Rather than managing by intuition, MSPs can use ticket-level RPS analysis to make informed decisions about agent training priorities, documentation gaps, and client relationship management strategies.
Accelerate AI Deployment Readiness
- By analyzing individual tickets, MSPs can systematically identify and address the specific documentation and process improvements needed to achieve higher Ticket RPS scores, directly improving their readiness for AI-powered support automation.
Support Quality Assurance and Training
- Ticket analysis provides concrete examples for agent coaching, highlighting both successful interactions that can be replicated and problematic patterns that need improvement.
Understanding the Tickets Grid
The main tickets grid displays all tickets imported from your connected ticketing/PSA system in a filterable, sortable format that provides at-a-glance visibility into your support workload.
About the Ticket Grid Columns
- Opened At: Ticket creation timestamp for trend analysis
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Ticket ID: Direct reference to PSA system ticket numbers. ServiceAI now displays the PSA-native ticket number throughout the UI — Autotask's
T20250123.0001format, Kaseya BMS numeric IDs, Syncro numbers, ConnectWise numbers, and HaloPSA numbers — instead of internal ServiceAI IDs. The number you see in ServiceAI is the same number your technicians see inside their PSA, so cross-referencing a ticket between the two systems no longer requires translation. PSA-native ticket numbers appear in chat references, the ticket detail page, and related-ticket lists throughout the application. - Subject: Brief description of the support request
- Status: Current status from your PSA system
There are many more grid columns that you can customize to your preference to set the portal to look exactly the way you want, providing the most valuable data to you at a glance.
Customizing the Tickets Grid to Your Preferences
MSPs can personalize the tickets grid to match their workflow needs:
Adjust Columns: Click the Settings icon to edit the standard view and add, remove, or reorder columns based on the information most relevant to your analysis needs.
Create Custom Views: Click on the Settings icon and select the New View button to create specific column configurations and combinations for different types of analysis (e.g., "High Priority Review" or "Training Examples").
Show Excluded Tickets: A Show Excluded Tickets toggle sits above the grid. Excluded tickets (those struck through in red because they match a Subject Line, Technician, Company, or Channel exclusion) are shown by default so existing behavior is preserved. Turn the toggle off to hide the strikethrough rows for a cleaner training-data view, then turn it back on when you want to audit what is being excluded.
Note that custom views are user-specific and not shared between team members, allowing each person to optimize their individual workflow.
Individual Ticket Analysis and Intelligence
Clicking on any ticket opens ServiceAI's comprehensive ticket intelligence interface, providing five key analysis areas:
Ticket Details Pane
This pane provides high-level ticket information with four action buttons:
- Share Ticket: Email ticket analysis or create a to-do for colleagues with an optional message context
- Refresh from PSA: Re-pull the latest copy of this ticket from your PSA on demand. Useful when comments or status updates were posted in the PSA after the last sync. While the refresh is in flight, the button is disabled and shows a spinner; a toast confirms when the refresh succeeds.
- AI Chat: A dropdown that launches AI Chat with the ticket already loaded as context. Choose Agent mode for a technician-focused conversation (full ticket data, internal reasoning, agent-style answers) or User mode to see what the end user would experience. When the Ticket Details pane is opened from a PSA pod-embedded view (Autotask or ConnectWise), the persona is locked to Agent and the toggle is hidden.
- View in Help Desk: Navigate directly to the original ticketing system/PSA ticket for quick reference
AI Analysis Pane
This pane provides the core intelligence section showing specific RPS scores and AI-generated insights:
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Ticket RPS Scores: RPS scores on the ticket, specifically:
- Ticket RPS: How viable the specific ticket is for automation in its current state based on available ticket history to reference, as well as existing documentation.
- Requester RPS: Outcome satisfaction of the user, based on AI-interpreted interaction tone, responsiveness, and volume of back-and-forth.
- Agent RPS: AI-interpreted rating of the agent assigned to the ticket based on their interaction with the client, determined by the chat transcript, responsiveness, and overall resolution.
- AI Insights: Contains several AI-interpreted sections, such as a summary of the ticket, keywords detected in the ticket, predicted CSAT, and more. This section gives a myriad of AI insights into the ticket to help the agent and service desk manager understand the big picture view of the ticket.
Agent Information Pane
This pane provides information on the assigned technician, including:
- Agent Name: The name of the individual agent assigned to resolve the ticket.
- AI Agent Score: The AI-given score to the agent's performance on the ticket on a scale of 1-10, with 10 being the best.
- AI Agent Evaluation: The evaluation of the agent's performance on the ticket, from improvement suggestions to positive remarks.
Requester Information Pane
This pane provides end-user analysis, including:
- Requester Name: The name of the individual user (requester) who submitted the ticket.
- AI Requester Score: The AI-given score to the user's satisfaction on the ticket on a scale of 1-10, with 10 being the best.
- AI Requester Evaluation: The AI's interpretation of the user's tone, satisfaction, and overall mood during the ticket interaction with the agent.
Comments Pane
Full ticket conversation with visual coding:
- Gray Boxes: Agent responses to the user, pulled directly from the PSA/ticketing system.
- Blue-tinted Boxes: Customer responses to the agent, pulled directly from the PSA/ticketing system.
Available Actions and Business Impact
Insights can be valuable on their own, but ServiceAI goes the extra mile by offering quick ways to improve the service desk experience as a whole with several actions that agents can take.
Generate Article from Ticket Analysis
When ServiceAI identifies knowledge gaps, agents can immediately create documentation to address these issues:
How to Use: Click Generate Article in the AI Analysis pane to create targeted documentation based on the ticket's resolution pattern. You can (and should) enhance the prompt as much as possible to make a relevant article to add to your knowledge base, as well as linking off any source URLs to further enhance the context for the article.
Business Impact: Directly improves future Ticket RPS scores by filling documentation gaps, accelerating AI deployment readiness while reducing resolution time for similar future issues.
Share Ticket Intelligence
Distribute ticket analysis and insights to team members for training or escalation purposes:
How to Use: Use the Share Ticket button to email the ticket analysis link with optional contextual notes. Or, create a to-do within the application to assign the ticket for review for an existing team member.
Business Impact: Enables collaborative problem-solving, supports agent training initiatives, and ensures knowledge transfer for complex issues.
Launch AI Chat from a Ticket
Open AI Chat with this ticket pre-loaded as context, so you can ask follow-up questions, test how AI would respond, or draft a reply:
How to Use: Click the AI Chat dropdown in the Ticket Details pane and choose either Agent mode (technician view with full ticket data and internal reasoning) or User mode (what the end user would see). Inside an Autotask or ConnectWise pod-embedded ticket page, the persona is locked to Agent and the toggle is hidden so the conversation always reflects the technician experience.
Business Impact: Provides concrete validation of how AI would handle specific ticket types before client-facing deployment, and lets agents quickly draft tailored responses without leaving the ticket.
Track Performance Patterns
Use individual ticket RPS scores to identify trends in agent performance, client satisfaction, and automation readiness:
How to Use: Review RPS patterns across multiple tickets to identify coaching opportunities, client relationship issues, or documentation needs.
Business Impact: Enables proactive management decisions about training, client relationship management, and strategic AI deployment planning.
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