Auto-Categorization in Console

The Schema system

Console’s categorization framework is called the Schema. The Schema combines request types and custom fields into a single unified system.

Rather than requiring users to select a category from a dropdown, Console reads the natural language request and infers the request type automatically. Setting a request type automatically pulls in the relevant custom fields for that type.

This flips the traditional Jira model. Instead of users filling out a form that defines what kind of request it is, the AI reads the message and does it for them.

Request types are fully customizable. Teams can rename, add, or edit them to match their own nomenclature. Examples include:

• Laptop refresh

• Access request

• Salesforce issue

• Security incident

• Onboarding

If Jira is the backend ticketing system, request types can map directly to Jira issue types and fields.

Custom fields

Each request type has its own associated custom fields that are relevant only to that type. Custom fields are dynamic. A laptop refresh might show device type and serial number fields. An access request might show app name, access level, and justification.

Custom fields support multiple data types:

• Freeform text

• Dropdowns

• Booleans

All custom fields are fully editable and renameable by admins.

Because the Schema automatically applies the correct custom fields when a request type is identified, agents receive structured context upfront without manual information gathering. Custom fields are also the underlying data powering analytics filtering and reporting.

AI Fill for custom fields

Console can auto-populate custom fields by querying connected systems. This functionality is called AI Fill.

AI Fill is configured per field using natural language instructions, for example: pull device info from Jamf for the requester. Admins use a hashtag (#) to reference specific actions from connected integrations inside the AI Fill prompt.

Examples of AI Fill include:

• Populating an assigned laptop field by calling the hardware asset action from Omnissa or Jamf

• Pulling account name, account owner, and open opportunities from Salesforce when a RevOps ticket mentions a deal

• Retrieving relevant user data from connected systems

Console parses the API response and maps the relevant data to the correct custom field automatically.

AI Fill functions like a step inside a playbook. Multiple fields on the same ticket can each have their own 

AI Fill logic pulling from different systems simultaneously. As the conversation between the user and agent evolves, AI Fill data can update in real time to reflect new context.

Categorization-driven analytics

Because every ticket is consistently categorized on arrival, the underlying data is structured and ready for reporting.

Console provides out-of-the-box analytics with no custom setup required. Tickets can be filtered and sorted by:

• Request type

• Assignee

• SLA status

• Channel source

• Playbook triggered

Custom dashboard views can be saved and shared so teams open the view most relevant to their work.

Consistent categorization enables trend analysis over time, such as comparing how many laptop refresh requests came in last quarter versus this quarter. Both Kanban view and table view are available so teams can choose the visualization that fits their workflow.