Before the Prompt
Classifying, minimizing, and authorizing information before it reaches an AI service.
Coming soonTDG Publication Series
A practical eight-part series for federal and regulated organizations seeking to use AI while preserving privacy, protecting sensitive information, and maintaining operational accountability.
Explore the roadmapWhy this series
A secure model can still support an inappropriate use of information. A privacy policy can still fail if identities, retrieval paths, connected tools, logs, and downstream actions are not technically controlled.
Each article connects privacy intent to architecture, delivery, operations, and evidence so that safeguards become usable decisions rather than abstract principles.
Eight-part sequence
Published articles are linked automatically. Upcoming topics remain visible so readers can follow the complete privacy and security operating model.
Classifying, minimizing, and authorizing information before it reaches an AI service.
Coming soonPractical rules for prompts that may involve personal, controlled, proprietary, or security-sensitive information.
Coming soonApplying authorization, source governance, isolation, and leakage controls across retrieval systems.
Coming soonConstraining delegated authority, tools, credentials, approvals, and downstream actions.
Coming soonManaging privacy exposure in prompts, outputs, chat history, telemetry, logs, caches, and evaluation data.
Coming soonUnderstanding where masking, tokenization, synthetic data, differential privacy, and federated approaches fit.
Coming soonExamining retention, secondary use, training, subprocessors, location, deletion, incidents, and audit rights.
Coming soonTesting, monitoring, incident response, control evidence, and recurring reassessment for operational AI.
Coming soonDesigned for
Privacy and Secure AI
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