Privacy is not a policy link in the footer
When a system works with patients, clients, case files, prospects, calls, documents or images, the question is not only whether data is encrypted. It also matters what is collected, why, who can access it, what external provider participates, how long it is retained and how the organization can prove what happened.
GDPR — European Union
The General Data Protection Regulation establishes principles including minimization, purpose limitation, security and demonstrable accountability. Health, biometric and other special-category data receive heightened protection. European Commission →
UK GDPR — United Kingdom
The United Kingdom operates under UK GDPR together with the Data Protection Act 2018. Privacy, special-category data, security and rights must be designed for the actual UK operation rather than added as a translation after launch. ICO →
HIPAA — United States
HIPAA is not a universal badge for every healthcare company. Applicability depends on organizational role, covered transactions and the handling of protected health information. Architecture must be able to separate data, permissions, third parties and evidence when a flow falls within scope. U.S. HHS →
Law 25.326 — Argentina
Argentina protects personal and sensitive data under Law 25.326 and its data-protection authority. OrvixLabs does not design international systems around the lowest level of enforcement pressure; controls follow the real jurisdiction where the client operates. AAIP →
LGPD — Brazil
Brazil’s Lei Geral de Proteção de Dados establishes rules for personal data and identifies sensitive categories including health and biometric data. ANPD →
Varexis as a technical boundary
Varexis contributes controls that can be part of a regulated architecture: detection, minimization, transformation, residual scanning, separate permissions, evidence and blocking when policy cannot be satisfied. It does not by itself make an organization compliant. Regulation also depends on purpose, lawful basis, contracts, consent where required, retention, human processes and professional validation.
Privacy is designed before the model is connected.