If you pay for a DeepL Pro subscription, the text you submit for translation will not be used to improve or train DeepL's AI models. DeepL states it only processes your text to deliver the translation itself.
This analysis describes what DeepL's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
This commitment is particularly important for users who translate confidential, proprietary, or sensitive documents, as it limits how DeepL can use the content they submit.
Interpretive note: The commitment applies to paid Pro subscribers; the document does not clearly specify whether equivalent protections apply to free-tier users or to content submitted via third-party integrations, creating scope uncertainty.
Paid Pro subscribers receive a contractual assurance that their submitted text is not used for AI training purposes, which meaningfully limits DeepL's use of potentially sensitive content. This protection is stated as contractual and is not independently audited or verified within the document itself.
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"Texts submitted for translation by customers with a paid DeepL Pro subscription are not used to train DeepL's AI systems. DeepL processes submitted texts only to provide the translation service.— Excerpt from DeepL's DeepL Terms and Conditions
REGULATORY LANDSCAPE: This provision engages GDPR, particularly around lawful basis for processing (Article 6), purpose limitation (Article 5(1)(b)), and data minimisation principles. For enterprise customers processing personal data of employees or clients through DeepL, this commitment is relevant to the scope of any Data Processing Agreement under Article 28. The EU AI Act may also be relevant depending on how DeepL's translation models are classified, as training data sourcing is a regulated consideration under that framework. GOVERNANCE EXPOSURE: Medium. The commitment is contractual and meaningful, but the document does not specify audit rights, independent certification, or technical controls that verify compliance with this commitment. This creates a governance gap for enterprise customers who need to demonstrate vendor compliance to their own regulators or clients. JURISDICTION FLAGS: EU/EEA enterprise customers processing personal data through DeepL should ensure a GDPR-compliant DPA is in place and that this no-training commitment is reflected in the DPA's purpose limitation clauses. US customers in regulated industries such as healthcare and financial services should assess whether this contractual commitment satisfies sector-specific data handling requirements. CONTRACT AND VENDOR IMPLICATIONS: Procurement and vendor management teams should confirm that this no-training commitment is incorporated into any executed DPA or master services agreement. The absence of specified audit rights means enterprise customers cannot independently verify compliance, which may be a gap for high-risk data categories. Customers should request written confirmation or supplementary assurances if their data classification policies require it. COMPLIANCE CONSIDERATIONS: Data mapping exercises should reflect this purpose limitation for Pro subscriber content. If an organization's data protection impact assessment (DPIA) covers use of translation services, this commitment should be documented as a mitigating control. Free-tier users should separately review whether equivalent protections apply to their submitted content.
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This commitment is particularly important for users who translate confidential, proprietary, or sensitive documents, as it limits how DeepL can use the content they submit.
Paid Pro subscribers receive a contractual assurance that their submitted text is not used for AI training purposes, which meaningfully limits DeepL's use of potentially sensitive content. This protection is stated as contractual and is not independently audited or verified within the document itself.
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