Clinical documentation
Inspect structured sensitive data before note-generation or summarization requests leave the application boundary.
Interdict sits between healthcare applications and supported AI providers so teams have one runtime checkpoint for sensitive-data handling, prompt-injection controls, provider/model policy, response inspection, budgets, and audit metadata.
Data can be well protected in source systems and still be assembled into prompts, tool arguments, retrieved context, or model responses. Interdict focuses on the runtime handoff where the application is about to send that context outside its own boundary.
Inspect structured sensitive data before note-generation or summarization requests leave the application boundary.
Apply one runtime policy to AI-assisted support workflows that can receive patient or account context.
Keep raw identity fields away from the model when an approved verification path can handle them separately.
Inspect supported structured PII types in the request path before forwarding to the provider.
Choose a model action and, where configured, a separate approved verification destination for sensitive identity data.
Apply response-side inspection and protected streaming controls before model output returns to the application.
Keep policy and audit metadata without putting the raw prompt or response into the audit record.
Evaluate a representative request path before deciding whether Interdict belongs in production.