AI Sovereignty and Data Protection

2 posts · Jul 2026

What this trail covers

This post details the evolution of strategies for maintaining AI sovereignty and protecting proprietary data when using hosted AI model providers. It focuses on contractual protections like Zero Data Retention (ZDR), restricting data usage, and ensuring adequate liability caps. It also outlines operational best practices for tracking and permitting only services covered by contractual protections, including managing beta services, handling safety classifier triggers, and addressing ZDR exceptions. This iteration adds guidance on managing prompt caching configurations and ensuring that terms from model creators are honored by the hosting platform.

All Palantir trails

Jul 2026AI Sovereignty is Your Alpha: How to Avoid Transferring Your Alpha to a Hosted Model ProviderThis post extends the AI Sovereignty and Data Protection feature thread by detailing specific contractual traps and operational best practices for mitigating risks when using hosted AI model providers. It elaborates on securing robust Zero Data Retention (ZDR) by defining its key components (no storage, no human review, no training use, ephemeral memory only). It also provides best practices for restricting the use of 'alpha' (proprietary data) by hosted model providers, ensuring adequate liability caps, and meticulously tracking and permitting only services covered by contractual protections. Specific operational guidance is provided for ZDR-ineligible services (beta/preview), data storage triggered by safety classifiers, prompts with images/files, and prompt caching configurations. It emphasizes the importance of vetting specific terms for the platform and model used, and ensuring that custom terms with model creators are honored by the hosting platform.
Jul 2026AI Sovereignty is Your Alpha: How to Avoid Transferring Your Alpha to a Hosted Model ProviderThis post introduces the concept of 'AI Sovereignty' and outlines a framework for protecting proprietary data ('alpha') when utilizing hosted AI model providers. Key technical and contractual strategies discussed include: defining robust Zero Data Retention (ZDR) with specific exclusions for storage, human review, and model training; restricting data usage to only providing the service; negotiating high liability caps; creating allow-lists for ZDR-eligible services (excluding beta features); configuring accounts to disable abuse monitoring and safety classifiers; ensuring ZDR applies to image inputs/outputs; and vetting prompt caching configurations. It also emphasizes the importance of ensuring consistent data handling terms across different providers and AI labs.
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