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

Guides > AI Suggestions

AI Suggestions

In this lesson we will cover:

- Ticket matching

- AI ticket suggestions 

- AI Article suggestions



Before configuring AI functionality ensure you have first configured your AI connection, see our lesson on how to do this here.


AI can be used to match a ticket to an existing ticket in your database and suggest values that should be applied to your current ticket based on historical ticket data. This can be used to automate ticket processing. In this lesson we will cover how to configure AI suggestions and what these can be used for. 


Ticket Matching

Before AI suggestions can be made ticket matching must first be configured so embeddings and embedding scores are created for ticket data. Tickets will be 'scored' on similarity and will then be assigned a numerical value (embedding score) based on how similar they are, the more similar two tickets are the higher the score will be. 


Embedding scores are required to allow suggestions to be made, as suggestions will be given based on data from tickets that have a high embedding score with the new ticket. That is, if two tickets have a high embedding score suggestions will be made on the new ticket using data against the old ticket.


To set up ticket matching head to configuration > AI > ticket matching section. Here, enable 'Create Embedding Scores for Tickets'. 

Fig 1. AI ticket matching


Set the 'Ticket matching and AI insights method' field to be 'Built-in-functionality'. Then choose the vector search database that will be used to store the vectors (ticket data), Azure AI search is recommended if you have connected using Azure OpenAI. 


Note: AI suggestions can only be used when 'Built-in-functionality' is selected. 


Now you can configure the embeddings.


Embeddings

Use the 'AI Embedding Field' field to choose the field data that will be used to create an embedding. The data from this field will be passed to your AI connection to create the embedding. The field you choose here will be depend on the fields you use on your ticket types, the field selected must be present on the ticket types you would like AI suggestions to be used on. 

Fig 2. AI Embedding field 


Now choose the ticket types that embeddings will be created for in the 'Ticket Types with AI embeddings and insights enabled' field. Only the ticket types selected here will be able to have AI suggestions. 


Set the 'Minimum vector match score (Tickets)', this will be the minimum embedding score two tickets will need to have in order to be deemed a 'match'. Only data from 'matched' tickets will be used in suggestions. 


Embeddings will be created and indexed automatically each time a new ticket is created since enabling 'Create Embedding Scores for Tickets'. Before using AI functionality it is good practise to leave the embedding/indexing running for a while so suggestions are based on up to date accurate data. However, historical ticket data can be indexed using the 'Index tickets' button. When used you will be able to choose which ticket types embeddings are created for and indexed and schedule when the indexing will run. 

Fig 3. Creating embeddings for and indexing tickets


Configuring Ticket Suggestions

Ticket suggestions are essentially a set of rules that are run after AI Insights and AI Matching. The matches are evaluated and if they contain similar values for fields like estimate, agent, and linked problem ticket, a prompt to set the fields to the same value will be shown, or they can be applied automatically. 


To configure the suggestions that can be made hit the 'configure AI suggestions' button to take you the suggestions page. We have some suggestions configured out-of-the-box but these can be customised and new ones can be made. An example suggestion is shown in figure 4. 

Fig 4. Example suggestion - Assigned agent


AI Suggestions have a precedence, only one of each type of suggestion that matches can apply. Suggestions will be checked in order of precedence, once a ticket meets criteria for a suggestion type this suggestion will be made/applied, no further suggestions of this type will be made. 


The following types of suggestion are available:

Set Estimate to the Estimate of matched tickets - This will allow you to set the estimate of the ticket based on the average, maximum or minimum estimate on the matching tickets.

Set the assigned Agent based on matched tickets - This will allow you to assign the ticket to the same agent as the matched tickets based on the agent's default team if multiple of the matching tickets are assigned to the same agent.

Set Category based on matched tickets - This will allow you to set the category (1, 2, 3 or 4) of the ticket if the matches have a frequently used category.

Set Priority based on matched tickets - This will allow you to set the priority of the ticket if the matches share a similar priority level.

Set Priority to the AI suggested priority - This will allow you to set the priority to what the AI interprets the priority as.

Run an automation if AI suggests the ticket is an incident - This will allow you to trigger an action automation if the AI evaluates the ticket as an incident, allowing you to triage it as such.

Run an automation if AI suggests the ticket is a request - This will allow you to trigger an action automation if the AI evaluates the ticket as a request, allowing you to triage it as such.

Create a problem ticket for incident matches - If the matching tickets are incidents that are not linked to a problem, you can set a threshold to automatically create a problem ticket and link them to it.

Link to an existing problem ticket based on the problem ticket of incident matches - Similar to creating a problem ticket, if the majority of matches are linked to the same problem already, it will identify that the current ticket should be linked to the problem ticket as well.

Run an automation if there are Ticket matches - If there are any ticket matches above a certain match score, run an action automation.

Run an automation if there are Articles matches - If there are any article matches above a certain match score, run an action automation. Link this to action that can write a response using the article suggestions from the recently added AI Knowledge matching feature to easily generate a response based on the matched articles.


In the 'Suggestion Information' field you will need to set what you would like to appear in the suggestion information field, this tells the agent what the suggestion is for. You will need to include $-SUGGESTEDVALUE  here to ensure the field is populated with the value that is being suggested. 


You can also set conditions against each suggestion, these restrict when this suggestion will be made. 

Fig 5. Suggestion conditions


Suggestions can be restricted by ticket type, end user of the ticket and strength of match. 


The field 'Include Open/Closed/All Tickets' is used to determine what ticket data will be used for the suggestion. If 'All tickets' is selected suggestions can be made based on data from both open and closed tickets. If you are including closed tickets in your suggestion database you can also set which closed tickets will be used based on when they were closed, allowing you to filter out ticket data that is outdated.  


These conditions are especially useful when the setting 'Automatically apply this suggestion' is enabled. As this ensures suggestions are only applied automatically when strict criteria are met, such has having a very high minimum score and high number of matches.


Using AI Ticket Suggestions

Once AI ticket suggestions are configured a new tab will be available against the ticket types that AI embeddings and insights are enabled for, called 'AI Insights'.

Fig 6. AI Insights tab against ticket


In addition to this tab, if a ticket has AI suggestions a pop-up notification will appear at the bottom of the ticket, when this notification is selected you will be taken to the AI insights tab. If you would rather not have a pop-up notification and instead have notifications available in the problem/resolution finder, head to configuration > AI and toggle the 'AI suggestion notification' setting. 

Fig 7. AI suggestion notification


The AI insights tab will contain all the suggestions that can be made for the ticket. The 'Apply suggestion' button is used to apply the suggestion to the ticket. Once a suggestion is applied the date/time the suggestion was applied will show. 


Article Suggestions

AI can be used to suggest relevant knowledge base  articles for tickets. This can assist agents in resolving tickets, saving them having to find relevant articles themselves to read/send to users. 


Article suggestions require Azure AI search to be enabled and configured due to the way article suggestions are returned. When a ticket is logged a search term is created based off the matched tickets, this search term is used to perform a vector search on indexed knowledge base articles.


In order to use this functionality:

  • Ticket matching and AI insights method must be set to "Built-in functionality"
  • AI knowledge search - Vector search database must be set to "Azure AI Search"


To set this up head to configuration > AI > AI Knowledge search section. Set the 'Vector search database' to be 'Azure AI Search', you will need to configure an Azure AI search connection for this. Details on how to obtain connection details from Azure can be found here.  Now ensure 'Enable AI Article Suggestions' is enabled. 

Fig 8. AI knowledge search settings


If you would like to restrict which articles can be indexed based on their FAQ list enable this setting, a field will then appear against each FAQ list to determine if this FAQ list can be indexed. 


Articles will be indexed each time a new article is created but the 'Index articles' button can be used to index historical article data. 


Now AI article suggestions are active, when a ticket is logged article suggestions for the ticket will appear in the problem/resolution finder. 

Fig 9. AI article suggestions in the problem/resolution finder


Article suggestions will also appear under the 'AI insights' tab against the ticket with a matched score. 

Fig 10. Matched articles








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