Sovereign Privacy Mandate: The Zero-Trust Forensic Protocol

1. Introduction to Sovereign Custody

1.1. The Zero-Trust Foundation

Radsam Academy rejects the modern digital standard of "convenient exposure." Our Privacy Mandate is built on a Zero-Trust Architecture, specifically designed for the 0.1% of Canadian legal and public sector elite who cannot risk the "probabilistic leakage" inherent in cloud-based AI. We operate on the principle that digital encryption is a "Hearsay Security Illusion"; only physical isolation provides true sovereignty.

1.2. Jurisdictional Authority

As a Federal Corporation established in 2016, Radsam Trade Inc. operates strictly under the laws of Ontario and the federal statutes of Canada. This mandate outlines our forensic commitment to data custody, ensuring that your privileged information remains a Sovereign Asset, never a cloud liability. This policy applies to all mandates within the Toronto-Manhattan Legal Axis.

2. Regulatory Alignment & Statutory Compliance

2.1. Federal Compliance (Bill C-27 & AIDA)

We natively align with the principles of the Artificial Intelligence and Data Act (AIDA) and the Consumer Privacy Protection Act (CPPA). While we do not offer external compliance consulting, our internal forensic operations are categorized under "High-Impact" governance protocols, ensuring that risk mitigation is a hard-coded requirement for every Shadow Audit and Expert Witness mandate.

2.2. Provincial Mandates (Ontario Bill 194)

In accordance with Ontario’s Strengthening Cyber Security and Building Trust in the Public Sector Act, we provide the requisite transparency for institutional data handling. Our Forensic AI Auditor protocols are designed to satisfy the Information and Privacy Commissioner of Ontario (IPC) regarding the use of automated systems in the public interest.

2.3. Privacy Professional Standards (CIPP-C & AIGP)

Our data lifecycle management is engineered by professionals holding CIPP-C (Certified Information Privacy Professional/Canada) and AIGP (AI Governance Professional) designations. This ensures that every byte of data processed during a Joint Retainer or Court Appointment is mapped to Canadian privacy principles.

3. The Air-Gapped Protocol: Ontario Landed Offline Servers

3.1. Physical Decoupling (The No-Cloud Policy)

The most significant threat to privacy is the "Cloud." Radsam Academy utilizes a strict No-Cloud Architecture. Your data never traverses the public internet once it enters our intake vault. We do not use third-party APIs (OpenAI, Azure, AWS) for processing sensitive audit data.

3.2. Ontario Landed Hardware

All forensic data is processed on Ontario Landed Offline Servers. These are physical, high-compute machines located within our secure, undisclosed Ontario facilities. By anchoring data to a physical, offline location, we eliminate extraterritorial risks such as the US CLOUD Act, ensuring that Canadian sovereign data remains beyond the reach of foreign subpoenas.

3.3. Isolation of Sovereign RAG

Our Retrieval-Augmented Generation (RAG) systems operate in a "Cold Room" environment. The AI models used for forensic analysis are loaded locally; they are physically incapable of reaching an external server to "call home" or leak proprietary case logic.

4. Forensic Transparency & Chain of Logic

4.1. Source Traceability

To satisfy the Treasury Board of Canada Secretariat (TBS) and the IPC standards for transparency, every output generated during our audit is linked to a deterministic statutory vector. We do not provide "Black Box" answers; we provide a verifiable Chain of Logic.

4.2. Disclosure of Logic

Transparency is the antidote to the "Black Box" problem. Upon request by the Mandating Counsel or the Court, we provide a Technical Transparency Report that explains the mathematical weights and retrieval parameters used in your specific Forensic AI Audit.

5. Data Lifecycle & Forensic Custody

5.1. Collection and Minimization

We adhere to strict Data Minimization. We only ingest the specific statutory or evidentiary files required for the forensic mandate. Data transfer is conducted via encrypted physical media (SSD) or secure, point-to-point encrypted tunnels (The "Black Box" Protocol) that bypass commercial cloud storage.

5.2. Processing Without Training (Zero-Training Guarantee)

We provide a Zero-Training Guarantee. Your data is used exclusively for forensic retrieval and hallucination triage. Your intellectual property and solicitor-client privileged documents are never used to "fine-tune" a model for other clients or third-party vendors.

5.3. Cryptographic Destruction (The "Burn" Protocol)

Once the audit is concluded and the "Sovereign Certificate of Fact" is issued, we initiate a Terminal Node-Destruction Sequence. We do not maintain "shadow copies." We execute a multi-pass cryptographic wipe of your data from our offline servers, ensuring the total cessation of the data lifecycle.

6. Human-in-the-Loop (HITL) & Competencies

6.1. Forensic Oversight

AI is a tool of the expert, not a replacement. Our Forensic AI Auditor oversees every stage of the data lifecycle. A human expert validates the retrieval accuracy before any report is finalized for institutional use, ensuring that no "machine hallucinations" enter the judicial record.

6.2. Professional Competency

Our team maintains continuous education in Ontario Province Laws and Regulations. This competency ensures that our "Technical Advice" regarding AI Sovereign Governance remains aligned with the latest amendments to the Planning Act, AODA, and other critical statutes.

7. Accessibility & AODA Mandates

7.1. Accessibility for Ontarians with Disabilities Act (AODA)

Transparency must be accessible. Our reports and forensic findings are prepared in accordance with AODA standards.

7.2. Algorithmic Inclusivity

As part of our forensic triage, we audit systems to ensure they do not exhibit bias against individuals with disabilities. We ensure that AI Sovereign Governance promotes equitable access to institutional justice.

8. Rights of the Data Sovereign

8.1. Right of Access and Explainability

Under Bill C-27, you have the right to a "plain language explanation" of how your data was used to generate an AI output. We provide this through our Forensic Logic Trace.

8.2. Data Portability

Should you choose to move your data to a different sovereign vault, we provide secure, offline transfer protocols to ensure the "Chain of Logic" remains unbroken.

8.3. Correction and Withdrawal

Clients may withdraw their data from the offline processing queue at any time. Upon withdrawal, the "Burn" protocol (Section 5.3) is immediately triggered.

9. Professional Boundaries & Disclaimers

9.1. Technical Advice Only

Radsam Academy provides Technical Advice regarding AI Sovereign Governance. We are forensic auditors and technical architects.

9.2. No Legal Advice

It is a common misconception that AI Governance is a legal service. It is not. We do not provide legal advice, legal opinions, or the practice of law. Our reports are Technical Evidence to be used by your legal counsel in litigation or arbitration.

9.3. No Guarantees of Outcome

While we guarantee Air-Gapped Protocols and Deterministic Accuracy (0% Hallucination within the provided dataset), we provide no guarantees regarding the legal or political outcome of your case.

10. Breach Notification & Accountability

10.1. Physical Security Breach Protocol

In the unlikely event of a physical security breach at our Ontario Landed facility, Radsam Academy will notify the affected institution and the IPC within 24 hours of discovery, as mandated by Bill 194.

10.2. Accountability Log

We maintain an immutable Accountability Log for all internal data access. Only the Lead Forensic AI Auditor assigned to your case has the physical "Key" to access your air-gapped data volume.

11. Contact and Inquiry

For inquiries regarding our Sovereign Privacy Protocols or to request a Chain of Custody audit, contact the Privacy Office:

Radsam Trade Inc.
Attn: Privacy & AI Governance Department Toronto, Ontario, Canada
Email: audit@radsamacademy.com

Effective Date: February 18, 2026
Last Revised: February 18, 2026
Approved by: Mohammadreza (Pouya) Shafabakhsh Nezam, Chief Forensic AI Auditor