Selling ticket and support data
A ticket contains a task, the steps to resolve it and the outcome. That makes it suitable for training and testing AI agents. We anonymise customer service, service desk and bug tracker data and license it to vetted buyers.
At a glance
- A ticket contains a task, the resolution and the outcome. That makes it suitable for training AI agents and checking their results.
- Labelbox expressly looks for support histories of at least six months.
- In demand are data from customer service, IT service and bug trackers, ideally linked to CRM and email.
- Customer data in tickets are anonymised, and confidential content of business customers is excluded.
Why is ticket data valuable for AI training?
Because every ticket is a completed task with a verifiable outcome. That is exactly what AI agents are trained and evaluated on.
AI agents learn in training environments in which their result is checked automatically. A Scale AI case study shows that training on real company data works: an agent trained on an insurer's data executed 46.9% of database queries correctly, compared with 21.9% for the best off-the-shelf model.[1] Support histories provide such tasks in large numbers. Labelbox therefore specifically looks for histories of at least six months and rates cross-system data with timestamps and roles as urgently needed.[2]
Which systems and data qualify?
All systems in which requests are documented with their resolution and outcome.
| Type of system | Examples | What interests buyers |
|---|---|---|
| Customer service | Zendesk, Freshdesk, Zammad | Request, replies, resolution, outcome |
| IT service | ServiceNow, Jira Service Management | Incident, diagnosis, fix |
| Bug tracker | Jira, GitLab, GitHub | Bug report, reproduction, correction |
Tickets linked to CRM, email and accounting via customer or order numbers are particularly valuable. One example is the dataset of a branch network with 2.6 million service tickets on our marketplace.
What is ticket data worth?
Ticket data are usually licensed as part of a company's overall dataset. For companies with 50 to 250 employees, buyers quote US$100,000 to US$1 million.
The figure comes from the buyer Replay and covers a company's entire dataset.[3] An extensive, well-documented customer service history over many years raises the value considerably. More prices are covered in the article What is company data worth?
What needs to be considered legally?
Tickets contain customer data. Only an anonymised copy is therefore licensed, and confidential content of business customers stays out.
- Anonymised data are outside the scope of the GDPR (Recital 26).[4]
- For business customers, we check confidentiality clauses in the contracts and exclude affected content.
- In opened German insolvency proceedings, the administrator decides on the realisation (§ 80 InsO).[5]
How does the sale work?
In four steps. No data leave the company until a buyer has been found.
- 1
Initial call and estimate
You answer nine questions on industry, software, data volume and history, or talk to us directly. We do not need access to the data for this and give you a first estimate.
- 2
Data sheet and buyer search
We describe the dataset without names, agree the data sheet with you and approach vetted buyers. Company and proceedings remain confidential.
- 3
Fee and anonymisation
As soon as a buyer has been found, we agree a success-based fee. Under a data processing agreement we anonymise the dataset locally at the seller; the buyer receives a sample under NDA.
- 4
Licence and handover
You approve the buyer, we hand over the anonymised data and then delete the mapping.
Frequently asked questions
Why is ticket data in demand for AI training?
Because every ticket is a completed task with a verifiable outcome: request, resolution and result. That makes it possible to train AI agents and assess their results.
Which systems can ticket data come from?
From customer service systems such as Zendesk, Freshdesk or Zammad, from IT service systems such as ServiceNow or Jira Service Management, and from bug trackers such as Jira, GitLab or GitHub.
What happens to customer data in the tickets?
Names, email addresses, phone numbers and customer numbers are replaced with consistent pseudonyms so that histories remain traceable. Confidential content of business customers is excluded beforehand.
How many tickets are needed?
There is no fixed minimum. Labelbox looks for support histories of at least six months. The longer the period and the more tickets with a documented outcome, the higher the value.
Sources
- [1]Scale AI Labs: “Scaling Enterprise Agent Performance with Reinforcement Learning via Verifiable Feedback Loops”, 17 November 2025
- [2]Labelbox: “Prism: Data licensing”, accessed 20 October 2026
- [3]Replay: “Value my data”, accessed 20 October 2026
- [4]EUR-Lex: “Regulation (EU) 2016/679 (General Data Protection Regulation)”
- [5]Federal Ministry of Justice (Germany): “§ 80 InsO, transfer of the right to manage and dispose”
This overview is no substitute for legal advice in the individual case.
What is your dataset worth?
Nine questions, no data needed, no upfront costs. You receive a first estimate.
Other data types
- Email archivesLicense company emails and team chats as training data, anonymised under the GDPR.
- Source codeLicense your own repositories with commit and review history for coding agents.
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