Platform preparation

Linear data exports: preparation and rights review

Prepare Linear records for an AI data licensing review: export scope, content risks, provenance, and a bounded pilot.

Sources and guidance · Reviewed October 2026

What the export does and does not establish

Linear supports workspace and issue-view CSV exports, with role-based limits and options that affect scope. Its documentation distinguishes CSV issue fields from other export methods and notes that attachment files are not included in CSV exports. A link in a description is not the same as possessing or clearing the linked asset.

Content boundaries to review

Issues and projects may contain unreleased product plans, customer requests, internal estimates, incident details, and copied material from connected tools. Private teams deserve explicit scoping. The person assigned an issue is responsible for the work, not necessarily the author or rights owner of the request, screenshot, or technical description.

Prepare a narrow candidate collection

Build a pilot around an approved team and a specific task, such as prioritization explanations or issue-to-resolution examples. Separate customer-originated requests from internal descriptions and machine-generated summaries. Inspect text for account identifiers and confidential roadmap commitments. Keep links as provenance references in restricted records until the target content has been reviewed independently.

Evidence to preserve

Preserve issue IDs, team and project scope, export timestamp, filters, field meanings, and private-team selection. Record whether comments, customer requests, documents, and attachments were actually collected by the chosen method. Keep source links and review decisions aligned with each example. Document whether statuses and estimates reflect the current snapshot or a historical point in the workflow.

Validate before offering a sample

Have product and engineering reviewers check whether a completed issue truly demonstrates a successful outcome. A short title and closed status rarely provide enough evidence on their own. Test that anonymization has not removed the reason for a priority decision. Export features intended for analysis or AI tools should not be read as a blanket right to resell workspace content.

Before any external sample or sale, have the responsible rights and privacy reviewers assess the proposed recipient, training or evaluation purpose, retention, redistribution, and deletion obligations. Preserve the relevant contract versions and written decisions. These preparation steps are a review framework, not a legal conclusion or a statement that the platform endorses commercialization.

Sources & further reading

Exporting Data ↗
Use this as a preparation framework. It is not legal advice, a valuation or a promise that a buyer will accept your data.