This analysis describes what Cohere'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 has operational significance because it defines the scope of permitted data use for model development. The restriction creates a distinct data handling framework for enterprise customers compared to other service tiers.
Interpretive note: The exact scope of 'enterprise customer data' and whether carve-outs exist for anonymized or aggregated data is not defined in the visible document text.
Under this provision, enterprise customers operate under terms that exclude their inputs and outputs from Cohere's model training pipeline. This defines what data processing activities Cohere authorizes itself to conduct with enterprise customer information.
How other platforms handle this
Data publicly available on the Internet. Our artificial intelligence models are trained on data that is publicly available on the Internet by third parties, which may contain personal data, even if we use good practices to filter out such personal data. [...] Training Datasets. In some cases, we acc...
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.
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"Cohere does not train on enterprise customer data. Inputs and outputs from enterprise customers are not used to train Cohere's models.— Excerpt from Cohere's Cohere Enterprise Data Commitments
How Meta, TikTok, and Supabase restructured governance language across documents, jurisdictions, and consent frameworks through incremental document updates.
How 10 AI platforms describe the use of user data for model training, improvement, and development, based on archived governance provisions.
Compliance Governance Intelligence
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Compliance includes provision-level monitoring, governance timelines, regulatory mapping, and audit-ready analysis.
Built from archived source documents, structured governance mappings, and historical version tracking.
This commitment has operational significance because it defines the scope of permitted data use for model development. The restriction creates a distinct data handling framework for enterprise customers compared to other service tiers.
Under this provision, enterprise customers operate under terms that exclude their inputs and outputs from Cohere's model training pipeline. This defines what data processing activities Cohere authorizes itself to conduct with enterprise customer information.
No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by Cohere.