A support desk wants AI to sort incoming tickets by fault type. The model needs a description such as “the warehouse label printer jams after the first page”. It usually does not need the sender’s mobile number, email signature or customer account number. Define what the classification step receives before connecting it to the full ticket feed.
Start with the fields you can leave out
Map the information needed to assign a queue. A category list, a short fault description and a non-sensitive routing reference may be enough. Exclude unnecessary contact fields and attachments before building the model request. Keep the original ticket in the support system with its existing access controls. Use a ticket ID to attach the proposed category to the original record.
Test detection on the text that remains
Free text can still include names, phone numbers or identifiers pasted into a description. Microsoft’s Azure Language PII detection documentation describes identifying and redacting supported categories of personal information. Check the supported languages and categories for the capability you use. Test Arabic, English and mixed-language samples that resemble your intake, including signature blocks and local number formats. Add controls for internal account codes or other values a general detector may miss.
The detector itself receives the text it analyses. Include that service, its logs and any later classification service in your data-flow review. Masking known identifiers reduces exposure, but context can still identify someone. Set a review path for messages the workflow cannot safely process, including unreadable text and unexpected attachments.
Measure classification quality after masking
Use synthetic or appropriately prepared tickets with expected categories. Record both missed identifiers and over-redaction that removes a useful fault detail. Test that the agent receiving the ticket can find the original through authorised access. If AI also talks to customers, the support handoff guide covers the separate decision of what information an operator should receive.
ITZ’s AI integration service can help map the fields a classifier needs and test your redaction rules. Describe the queues and fields your ticket workflow uses.
Review your AI ticket intake
Bring your queue list, field names and synthetic sample tickets. Use the form to discuss data minimisation, redaction and a controlled classification pilot. Review Your AI Ticket Intake
