HaloPSA

HaloPSA Guides

Documentation to assist with the setup and configuration of the HaloPSA platform

Guides > AI Insights

AI Insights

In this lesson we will cover:

- What are AI insights?

- Configuring AI insights

- Sentiment Analysis & Emotion Detection

- See AI insights when hovering over a ticket



What are AI insights?

AI insights use AI to analyse a ticket to give further insights into the ticket, such as customer tonality, summarise the Ticket conversation, create a search term and suggest a priority. Insights can be created for any 'AI' system fields, this means if any of these fields are present on a ticket type they will be populated with AI insight data. 


AI insights can assist agents in managing and resolving tickets by automating various ticket processing procedures. Instead of requiring agents to manually read through ticket details and determine the summary and priority, AI can handle these tasks for them. Additionally, AI insights can enhance the user experience by reducing interpretation discrepancies between agents and providing consistent, data-driven recommendations. AI can also be utilized in resolution analysis to identify recurring patterns in logged issues, helping to improve overall service delivery and user satisfaction.


AI insights will automatically populate one of the following fields when the ticket is opened:

  • AI Tonality
  • AI Generated Summary
  • AI Satisfaction Level
  • AI Sentiment Analysis
  • AI Suggested Priority
  • AI Suggested Resolution
  • AI Suggested Type (Incident vs Request)

All you need to do is add the desired fields to the ticket type. 

Fig 1. AI insights fields


Dollar variables are also available for these fields (e.g. $-AITonality) so data from these fields can be pulled through to PDF/email templates. 


Configuring AI insights

AI insights can run either via Integration Runbooks or the Built-in functionality (recommended). Switching between the options above with automatically download and enable/disable the relevant runbooks. With 'Built-in-functionality selected, an AI Insights area will appear within the AI module. Head to configuration > AI > AI insights section.

Fig 2. AI insights configuration


This is already configured out-of-the-box but can be customised. 


AI Insights Context - Here you can give the AI model the context in which it is working, this improves the accuracy of the insights it returns. 

AI Insights Field - This determines the ticket fields AI insights are based on, data from this field will be sent to the AI model to run the evaluation. You can either use the 'Details' ticket field or customise what fields this is based on using $- variables. If customising with $-variables a free text box will appear next to this setting, here you can enter the $-variables for the fields you would like the insights to be based on. To see the $-variables for ticket fields head to https://YOURHALODOMAIN/variables . 

 Allow AI Insights to summarise the conversation - When checked, AI insights will be able to provide a summary of the conversation on the ticket. Once enabled you will be able to specify what ticket data is sent to the AI integration for it to summarise using $-variables.

Conversation AI Insights Data - Here, you can specify what ticket data is summarised by the AI, here you will need to enter $-variables. Using the variable $-ALLACTIONS will result in all actions on the ticket being summarised, but different variables can be used to limit what actions are summarised,  e.g. $ACTIONLISTPRIVATE will only summarise private actions.


Run AI insights using runbooks

To run AI insights using runbooks you can customise what data is analysed and how it is analysed by your AI model by editing the runbook. To edit the runbook head to configuration > integrations > custom integrations > integration runbooks > select the relevant runbook. The runbook will then either need to be triggered using an action or an event. To have the runbook trigger automatically after a particular event you will need to edit the runbook. To have the runbook be triggered by an action set the system use of the action to 'Send Webhook/Queue Integration Runbook' then in the 'Webhook/Integration Runbook' field choose the runbook you would like to trigger. 

Fig 3. Action configuration to trigger runbook


If running insights using runbooks the insights will be re-calculated each time the runbook is triggered. If you have the runbook set to trigger with the use of an action, this action will need to be used each time you would like the insights to be re-calculated. 


Re-running insights (Built in functionality)

When using the built in functionality insights will be calculated when the ticket is opened, however, they can be re-calculated manually against a ticket or using a ticket action. Allowing you to update the insights once there is more data available against the ticket/the ticket has progressed. Useful in giving insights into the ticket at point of closure. 


To re-calculate insights manually against any ticket hover over the '...' in the top right and select 'Re-index and re-run AI insights'.

Fig 4. Re-run AI insights in ticket details


To configure an action that will re-run insights head to configuration > tickets > actions > new > details tab. Here check 'Is a Quick Action' (as no fields are required). Then under the defaults tab enable 'Run AI Insights' and save the action.

Fig 5. Re-run AI insights 


Now ensure this action is added to the relevant workflows. When used AI insights and suggestions will be re-calculated based on the current data. 


Alternatively if you would like insights to be re-calculated after certain actions are used (such as email user, private note), just enable the setting highlighted in figure 5 against the action and each time this action is used the insights will be re-calculated. 


Sentiment Analysis and Emotion Detection

Sentiment analysis and emotion detection takes into consideration every message from the user on the ticket and summarises how they are feeling, as well as estimating a satisfaction level from 1 to 10. The result of the analysis will then show in the closure details of the ticket in the following fields when the ticket is closed:

  • AI Satisfaction Level
  • AI Sentiment Analysis 

Fig 6. Sentiment analysis and satisfaction level fields against ticket


All you will need to do to set this up is add the above fields to the ticket type. The fields will not be populated or show in ticket details until the ticket is closed, but once the ticket is in a closed status these insights will appear. 


If you would like these fields to be populated prior to ticket closure, you will need to edit the runbook that carries out this analysis, setting the event that will cause the runbook to trigger. 


See AI insights when hovering over a ticket

When a ticket is hovered over in a list by default you will see the a summary of the ticket details. However, this can be changed so instead the AI generated summary or AI conversation summary appears here.


To this head to configuration > Tickets > General Settings and toggle 'Ticket List Hover Text' . This can either be the default ticket details, the AI Details Insights, or the AI Conversation Insights. If the AI fields are not set for a ticket, then it will fall back to the details. 

Fig 7. Ticket list hover text default 

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