Data licensing guide
By system

Licensing Jira and ticketing data for AI

By Ade Molajo · Updated · How we check figures

Quick answer

Ticket systems are among the most valuable company records to license: each ticket is a problem, the work done on it, and an outcome. micro1 asks for project histories and ticket workflows, and Mode names Jira and Zendesk among its sources. Include tickets with clear outcomes, workflows and post-mortems. Strip customer personal data and secrets from ticket text, and leave out client tickets under NDA.

Problem → outcome
is what makes ticket data valuable
micro1 + Mode
both ask for ticket or project history
Years
of history beat volume alone
Scrub
personal data and secrets from ticket text

01Why ticket history is valuable

A ticket is a small, complete record of work: what the problem was, who picked it up, what they tried, and how it ended. Thousands of them, over years, show how a team actually solves problems. That's the "how work gets done" data AI companies are paying for, and it's why micro1 asks for project histories and ticket workflows, and Mode names Jira and Zendesk among its sources.

Where these records usually live

Engineering and projects

  • Jira
  • Linear
  • Asana
  • ClickUp
  • Trello

Service desk

  • Zendesk
  • ServiceNow
  • Intercom
  • Freshdesk

Examples of common tools, to help you find your records. Product names and logos belong to their owners; no affiliation or endorsement.

02What to include, and what to leave out

Jira and ticketing: usually licensable (Tickets with clear outcomes; Workflows, statuses and SLAs; Runbooks and post-mortems; Sprint and release history) versus check first or leave out (Client tickets under NDA; Security vulnerabilities and credentials; Customer personal data in ticket text; Attachments you can’t vouch for).Usually licensableTickets with clear outcomesWorkflows, statuses and SLAsRunbooks and post-mortemsSprint and release historyCheck first, or leave outClient tickets under NDASecurity vulnerabilities and credentialsCustomer personal data in ticket textAttachments you can’t vouch for
A starting point for scoping, not a legal test.

03What makes ticket data worth more

  • Clear outcomes. Resolved tickets with a resolution note beat open or abandoned ones.
  • The reasoning in comments. The back-and-forth is where the method lives.
  • Linked context. Tickets connected to commits, runbooks or wiki pages show the full chain.
  • Years of history on the same kind of work.

04Scrubbing ticket data

Ticket text is where personal data and secrets hide:

  1. Customer details: names, emails, phone numbers and account IDs in descriptions and comments.
  2. Secrets: passwords and tokens pasted into tickets during troubleshooting.
  3. Attachments: logs, screenshots and exports. Leave them out unless you can check them.
  4. Client tickets: if you work for clients, their contracts may restrict this data. See IT services and MSPs.

Programmes say they de-identify data, but responsibility for what you hand over starts with you. See UK GDPR.

05Scoping your ticket system

Scoping ticket data in four steps: list projects (internal vs client), keep resolved (clear outcomes), scrub text (people and secrets), link context (commits, wiki pages).01List projectsInternal vs client02Keep resolvedClear outcomes03Scrub textPeople and secrets04Link contextCommits, wiki pages
Four steps before anything is shared. Agree the scope with the programme in writing.

List projects or queues, ticket counts and date ranges, and mark which are internal versus client-facing. That inventory is also what programmes ask for when you apply.

Take our free fit check to see which programmes you're likely to match. The programme decides.

06Questions people ask

Why do AI companies want ticket data?

Tickets record real problems and how they were solved, step by step, with an outcome. That's the kind of work AI agents are being trained to do.

Do we include comments and attachments?

Comments carry most of the reasoning, so yes, once scrubbed. Attachments are riskier: logs and screenshots often hold personal data or secrets.

What about customer support tickets?

They're valuable but full of customer personal data. Remove or anonymise it, and check your customer terms.

Sources

Check which programmes you’re likely to matchA few short questions, about a minute. Free, no sign-up. The programme decides who qualifies.trackimpact.io/data →