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Free-Tier Translation Input Used for AI Model Training

Medium severity High confidence Explicitdocumentlanguage Unique · 0 of 325 platforms
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Document Record

What it is

If you use DeepL without paying, the sentences and documents you translate can be saved and used by DeepL to train and improve its AI translation system.

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

ConductAtlas Analysis

Why it matters (compliance & governance perspective)

Any text you paste into the free DeepL translator, including potentially sensitive personal, legal, medical, or business content, may be retained and used to improve DeepL's AI, which is a meaningful privacy consideration many users may not anticipate.

Consumer impact (what this means for users)

Free users' translation inputs, which may include confidential or personal text, can be stored and incorporated into AI model training processes. Users who routinely translate sensitive content on the free platform may be inadvertently contributing that content to DeepL's training data.

What you can do

⚠️ These actions may provide transparency or partial mitigation but may not fully address the underlying issue. Effectiveness varies by jurisdiction and individual circumstances.
  • Delete Your Data
    Send an email to privacy@deepl.com requesting deletion of your personal data, including any stored translation inputs submitted via the free tier. Reference your right to erasure under GDPR or applicable law.

How other platforms handle this

Ideogram Medium

We may use the content you provide to us, including prompts and generated images, to train and improve our AI models and services.

Windsurf Medium

We may leverage OpenAI models independent of user selection for processing other tasks (e.g. for summarization). We may leverage Anthropic models independent of user selection for processing other tasks (e.g. for summarization). We may leverage these models independent of user selection for processi...

Character.AI Medium

Users under 18 years old interact with an age-appropriate model specifically designed to reduce the likelihood of exposure to sensitive or suggestive content. Our under-18 model has additional and more conservative classifiers than the model for our adult users so we can enforce our content policies...

See all platforms with this clause type →

Monitoring

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▸ View Original Clause Language DOCUMENT RECORD
"
When you use the free version of DeepL (i.e. the website and apps without a subscription), we store the texts you submit for translation and use them to improve the quality of our services, which includes improving our machine learning models.

— Excerpt from DeepL's DeepL Privacy Policy

ConductAtlas Analysis

Institutional analysis (Compliance & governance intelligence)

(1) REGULATORY LANDSCAPE: This provision directly engages GDPR, particularly Articles 5, 6, and 13, which govern lawful basis for processing and transparency obligations. DeepL's use of user-submitted text for model training requires a valid legal basis; the policy asserts legitimate interest or consent as applicable. For EU/EEA users, the German supervisory authority and relevant national data protection authorities have enforcement jurisdiction. The provision also engages CCPA/CPRA for California residents, who have the right to opt out of certain uses of their personal information. (2) GOVERNANCE EXPOSURE: High. Organizations in regulated sectors (legal, healthcare, financial services) whose employees use the free DeepL interface may inadvertently expose privileged, confidential, or protected data to retention and AI training use. This could conflict with professional secrecy obligations, HIPAA requirements for covered entities, or attorney-client privilege protections. The policy does not specify how long free-tier inputs are retained or how they are anonymized before model training use. (3) JURISDICTION FLAGS: EU/EEA users are protected by GDPR's data minimization and purpose limitation principles, which may constrain how broadly this provision can be applied in practice. California residents may have CPRA rights regarding the use of their information for AI training. Employers in jurisdictions with strict data protection laws (e.g., Germany, France) should assess whether employee use of the free tier constitutes a compliant processing activity under works council or labor law requirements. (4) CONTRACT AND VENDOR IMPLICATIONS: Organizations procuring DeepL services should ensure their employees are directed to paid or enterprise plans rather than the free tier if translation of confidential content is foreseeable. Procurement teams should request data processing agreements under GDPR Article 28 for any paid tier usage. The free tier's training data use may not be compatible with standard corporate data handling or confidentiality clauses in client contracts. (5) COMPLIANCE CONSIDERATIONS: Compliance teams should implement an acceptable use policy specifying that confidential, privileged, or regulated content must not be entered into free-tier translation tools. Data mapping exercises should reflect the possibility that free-tier DeepL usage constitutes a third-party processing relationship. Employee training on AI tool usage policies should address the distinction between free and paid translation services.

Full compliance analysis

Regulatory citations, enforcement risk, and due diligence action items.

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Applicable agencies

  • FTC
    The FTC has jurisdiction over unfair or deceptive data practices affecting US consumers, including undisclosed use of user content for AI training purposes.
    File a complaint →

Applicable regulations

EU AI Act
European Union
Colorado AI Act
US-CO
GDPR
European Union
Texas AI Act
Texas, USA

Provision details

Document information
Document
DeepL Privacy Policy
Entity
DeepL
Document last updated
May 5, 2026
Tracking information
First tracked
May 9, 2026
Last verified
May 9, 2026
Record ID
CA-P-007201
Document ID
CA-D-00448
Evidence Provenance
Source URL
Wayback Machine
Content hash (SHA-256)
07120b424b50bb749364b07cb13cfa607ebe8a0b00588ea5d3a6f8f1f029b2b0
Analysis generated
May 9, 2026 16:04 UTC
Methodology
Evidence
✓ Snapshot stored   ✓ Hash verified
Citation Record
Entity: DeepL
Document: DeepL Privacy Policy
Record ID: CA-P-007201
Captured: 2026-05-09 16:04:20 UTC
SHA-256: 07120b424b50bb74…
URL: https://conductatlas.com/platform/deepl/deepl-privacy-policy/free-tier-translation-input-used-for-ai-model-training/
Accessed: May 13, 2026
Permanent archival reference. Stable identifier suitable for legal filings, compliance documentation, and research citation.
Classification
Severity
Medium
Categories

Other risks in this policy

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Frequently Asked Questions

What does DeepL's Free-Tier Translation Input Used for AI Model Training clause do?

Any text you paste into the free DeepL translator, including potentially sensitive personal, legal, medical, or business content, may be retained and used to improve DeepL's AI, which is a meaningful privacy consideration many users may not anticipate.

How does this clause affect you?

Free users' translation inputs, which may include confidential or personal text, can be stored and incorporated into AI model training processes. Users who routinely translate sensitive content on the free platform may be inadvertently contributing that content to DeepL's training data.

Is ConductAtlas affiliated with DeepL?

No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by DeepL.