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
The clause establishes a differentiated data practice based on customer tier: standard users' code may be retained for model training purposes, while Teams and Enterprise customers receive default non-retention of code post-processing, with retention available only through affirmative configuration. This structure creates distinct operational scopes for model development across customer segments.
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 →Standard users operate under terms authorizing their code snippets and telemetry data to be used in AI model training. Teams and Enterprise customers operate under a default configuration where code is not retained after processing, though they may affirmatively elect to permit retention through explicit configuration.
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To improve the quality of our services, we analyse texts submitted for translation. We ensure that this analysis cannot be traced back to individual users by anonymising the data before analysis. DeepL Pro subscribers' texts are not used to train our machine translation systems.
Only models with a post-mitigation score of "medium" or below can be deployed. Only models with a post-mitigation score of "high" or below can be developed further.
engage in any of the foregoing in connection with any use, creation, development, modification, prompting, fine-tuning, training, testing, benchmarking or validation of any artificial intelligence or machine learning tool, model, system, algorithm, product or other technology ("AI Tool").
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"We may use the information we collect, including code snippets and telemetry data, to train, evaluate, and improve our AI models and services. For Teams and Enterprise customers, code is not retained after processing unless explicitly configured otherwise.— Excerpt from Tabnine's Tabnine Privacy Policy
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The clause establishes a differentiated data practice based on customer tier: standard users' code may be retained for model training purposes, while Teams and Enterprise customers receive default non-retention of code post-processing, with retention available only through affirmative configuration. This structure creates distinct operational scopes for model development across customer segments.
Standard users operate under terms authorizing their code snippets and telemetry data to be used in AI model training. Teams and Enterprise customers operate under a default configuration where code is not retained after processing, though they may affirmatively elect to permit retention through explicit configuration.
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