Most AI platforms keep what you send them, and most privacy controls depend on a setting someone has to get right and keep right. This white paper lays out a different approach: zero-retention AI that is built so it cannot keep your content, paired with prompt-driven detection and de-identification of PII and PHI. Together, they let regulated organizations use AI on their most sensitive documents without the AI vendor ever storing them.
Inside, you’ll learn:
- Why retention by default and configuration-dependent privacy controls stall AI adoption in regulated organizations
- How a zero-retention architecture removes entire classes of exposure, from stored-content breaches to legal-hold production, and what it honestly does not cover
- How Elixir Muse turns a sensitive document into a HIPAA Safe Harbor-targeted de-identified draft with a coverage report, and why human review stays in the loop
Download the white paper to see why the safest data is the data you never kept, and how to keep using AI on your most sensitive content anyway.
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Policy says "we won't." Architecture says "we can't."
A deletion policy is only as durable as the next bug, misconfigured setting, or court order. Recent industry incidents, from shared AI chats indexed by search engines to court-ordered retention of deleted logs, share one root cause: the data was being kept.
This paper argues the answer is not to block AI. It is AI on an architecture that legal and security can actually approve: content processed in memory and never retained, with de-identification running on the same zero-retention path.
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Use AI on your most sensitive content.
Discover how Elixir pairs zero-retention AI with prompt-driven PII and PHI de-identification so sensitive documents can be analyzed, rewritten, or de-identified without the AI vendor storing them.
See the reference architecture, an honest threat model, and a worked example that turns a PII-laden breach-notification letter into a training template in minutes, with a documented coverage report and a human making the final call.
Download the white paper to see how provably private AI works.