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How Atlassian protects contributed customer data

Understand what it means to contribute data and what that looks like for your organization.

Data protection at every layer

We apply the same practices we use today to protect your data, along with additional safeguards to ensure contributed data is handled responsibly.

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Sicherheit

Schütze deine Daten mit fortschrittlichen Kontrollen, Verschlüsselung und kontinuierlicher Überwachung.

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Transparency

We provide clear, accessible documentation on how data is collected, protected, and used.

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Data residency

We apply relevant data residency configurations to contributed in-app data.

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Restricted access

We ensure our teams only access contributed data for approved purposes.

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De-identification

We de-identify and aggregate contributed data before using it to improve apps for all customers.

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Data contribution settings

We give you control over your organization’s data contribution in Atlassian Administration.

See how contributed data powers enhanced AI experiences

Learn how we respect your data contribution preferences with a step-by-step example illustrating how safeguards apply to metadata and in-app data.

Step ONE

Managing data contribution

You configure your data contribution settings to determine what metadata and in‑app data are contributed to improve apps and AI experiences for all customers. Default settings are based on your highest active plan.

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Step two

Creating and classifying work

When you add data to our apps – like creating a work item in Jira – we automatically process eligible content into two data types: metadata (e.g., Story points: 3) and in‑app data (e.g., Fix login error on iOS after the latest mobile update).

Screenshot of automatic metadata

Step three

Protecting contributed data

Before we use contributed data, we apply data protection safeguards and remove personal data that directly identifies individuals, such as names and email addresses.

Data safeguards within product

Step four

Processing contributed data

We analyze de‑identified data – such as work item type - from across customers to identify patterns that become available for future product improvements.

Examples of de-identified data

Step five

Powering AI experiences

When you contribute data, you help shape what we build next. For example, we already surface intelligent recommendations – like suggesting possible root causes based on patterns – and your contributions help improve these insights over time.

Looking to go deeper?

Get an in‑depth view of how contributed data is processed, protected, and used to safely improve Atlassian apps and experiences for all customers.

Responsible by design

Learn more about how we design and build trustworthy AI experiences into all our apps and experiences.