Privacy Protocol &
Data Protection
At TakeTwo, we treat clinical data as a sacred trust. Our AI governance framework ensures the highest standards of de-identification, sovereignty, and security in high-stakes diagnostic environments.
security Clinical Data Security
Our multi-layered security architecture utilizes **Luminous Layering** protocols. Every data point ingested into the TakeTwo Fabric undergoes immediate PHI scrubbing and structural validation before entering the Clinical Activation engine.
Biometric Auth
AES-256 AES
Air-Gapped Ops
AI Auditing
Core Compliance
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HIPAA / HITECH
Full adherence to Protected Health Information standards.
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SOC2 Type II
Validated security, availability, and processing integrity.
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GDPR & CCPA
Global data sovereignty and user rights management.
1.0 Data Collection Protocols
TakeTwo collects data through secure ingestion gateways designed for the Clinical AI Governance framework. This includes metadata from EMR (Electronic Medical Records), PACS (Picture Archiving and Communication Systems), and diagnostic telemetry. Our platform utilizes Observability Lenses to ensure only the strictly necessary parameters are ingested for clinical validation.
We do not aggregate personal identifiers across disparate clinical environments without explicit, auditable consent through our Governance Engine.
2.0 Clinical De-identification
Our "Ground Truth" engine implements a proprietary k-anonymity and differential privacy model for all medical imagery and textual reports. The process follows these technical stages:
- Stage 01: Ingestion Scrubbing - Automated removal of DICOM tags containing PHI.
- Stage 02: Semantic Masking - AI-driven masking of names, dates, and locations in free-text clinical notes.
- Stage 03: Synthetic Perturbation - Adding statistical noise to large datasets to prevent re-identification through cross-referencing.
3.0 Data Sovereignty
Data processed within the TakeTwo Fabric remains under the jurisdiction and control of the originating clinical institution. We utilize a Decentralized Governance Framework where AI models travel to the data, rather than the data traveling to a centralized cloud. This ensures that clinical institutions maintain total physical and logical sovereignty over their patient populations' data assets.
4.0 Technical User Rights
Right to Erasure
The immediate and cryptographic deletion of specific model contribution weights associated with an entity's data.
Portability Audit
Full transparency logs detailing exactly how clinical data was utilized for AI training or validation cycles.
Governance Contact
Queries regarding the Privacy Protocol or clinical data activation cycles should be directed to our Chief AI Governance Officer.