The policy states that code inputs submitted to the AI assistant by free-tier users may be used to improve Tabnine's AI models by default, while paid-plan users have access to telemetry controls that can prevent this use.
This analysis describes what Tabnine'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 provision establishes a default data use practice for free-tier users that includes their submitted code in AI training pipelines, with opt-out access tied to subscription tier. Enterprise compliance teams should evaluate whether this default treatment is compatible with confidentiality obligations over employee-submitted code.
Interpretive note: The exact verbatim language of this provision could not be fully extracted from the truncated document; the description is inferred from available policy text and standard Tabnine public disclosures.
The updated privacy policy no longer includes explicit language stating that Tabnine respects user privacy and the user's right to control how personal data is collected, used, and shared. This language removal does not necessarily change what data practices are authorized under other sections of the policy, but it does remove an aspirational commitment that was previously stated. The policy may continue to describe specific data practices, collection methods, and user controls elsewhere, but readers will no longer see this opening commitment to privacy and user control.
View change record →Current version simplifies the provision, removes mention of Enterprise customers, and adds that paid plan users can disable telemetry to opt out of model training (shifting from Enterprise-only protection to user-configurable settings).
View full change record →Under this clause, free-tier users' code submissions are subject to AI model training use by default unless opt-out steps are taken. Paid plan holders have access to a telemetry setting that, when disabled, restricts this processing.
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"We may use code snippets that are submitted by users as part of the AI assistant functionality to improve and train our AI models. Free tier users' code snippets may be used for this purpose by default. Users on paid plans may disable telemetry to prevent their code from being used for model training.— Excerpt from Tabnine's Tabnine Privacy Policy
1. REGULATORY LANDSCAPE: This provision may require evaluation under GDPR Article 6(1)(f) if legitimate interests is the asserted legal basis, as processing of potentially sensitive or proprietary code for model improvement requires a balancing test against user interests. EU data protection authorities have scrutinized AI training data use practices. CCPA may also apply to the extent code submissions constitute personal information used for commercial model development. 2. GOVERNANCE EXPOSURE: High. The default inclusion of free-tier code in AI training without affirmative opt-in consent raises questions under GDPR's transparency and purpose limitation principles. Enterprise organizations whose developers use free-tier accounts may not be aware that submitted code is processed for training, creating confidentiality and IP exposure. 3. JURISDICTION FLAGS: EU/EEA users face heightened exposure given GDPR requirements for clear lawful basis and the right to object to processing under legitimate interests. UK GDPR imposes similar requirements. California residents may have CCPA rights regarding use of their submitted data for commercial model development. 4. CONTRACT AND VENDOR IMPLICATIONS: Enterprise procurement teams should confirm whether a DPA with Tabnine restricts AI training use of submitted code at the organizational level. The policy's distinction between free and paid tier treatment creates procurement pressure to evaluate whether free-tier deployment is appropriate for developer workforces handling sensitive codebases. 5. COMPLIANCE CONSIDERATIONS: Compliance teams should audit whether telemetry opt-out is available and enforceable at the organizational/admin level, not only per individual user. Data mapping exercises should categorize code snippet submissions as a distinct data category given their potential to contain credentials, business logic, or PII. Privacy impact assessments may be warranted for enterprise deployments.
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This provision establishes a default data use practice for free-tier users that includes their submitted code in AI training pipelines, with opt-out access tied to subscription tier. Enterprise compliance teams should evaluate whether this default treatment is compatible with confidentiality obligations over employee-submitted code.
Under this clause, free-tier users' code submissions are subject to AI model training use by default unless opt-out steps are taken. Paid plan holders have access to a telemetry setting that, when disabled, restricts this processing.
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