Automation-first privacy workflows, compliant data handling, measurable privacy outcomes.
Syncpoly OÜ builds automation tools for privacy: consent governance, data minimization, DPIAs, access controls, and auditable privacy pipelines that run in production environments.
Policy intake
Automation
Controls
Regulatory landscape
Privacy automation should align with global requirements. We map automation capabilities to regulatory controls and penalties to help you stay in compliance while scaling operations.
Key requirements: privacy by design, data subject rights, lawful bases for processing, data minimization, breach notification within 72 hours.
Penalties: up to 20 million EUR or 4% of worldwide annual turnover, whichever is higher. Non-compliance can trigger investigations and enforcement actions.
Rights include access, deletion, and opt-out of sale; non-discrimination provisions for exercising rights.
Penalties: civil penalties can be significant per violation; enforcement by attorney general offices and potential class actions in some cases.
DROP is an upcoming privacy compliance framework scheduled to be introduced Aug 1. It will impose governance, DPIA, and auditability requirements for automated privacy workflows across data lifecycles.
Automation impact: prepare with policy engines, DPIA orchestration, access controls, and auditable change history to meet DROP requirements.
Penalties & enforcement
Regulatory penalties can be severe for data breaches, improper data handling, or failing to honor user rights. Our automation platform provides auditable trails, real-time policy enforcement, and DPIA orchestration to reduce risk and speed remediation.
Versioned policies, immutable logs, and end-to-end policy enforcement across systems.
Automated rights handling, DPIA workflows, and risk scoring to meet regulatory expectations.
Automated monitoring, alerting, and containment to minimize penalties and harm.
Privacy automation toolkit
Consent governance, data minimization, DSAR automation, and policy enforcement integrated with compliance requirements.
Automated consent capture, preferences, and revocation across touchpoints.
Policy-driven data retention, anonymization, and role-based access enforcement.
Automated subject rights requests handling, verification, export, and deletion workflows.
Automated policy checks, data labeling, and audit trails across systems.
Platform
A production-grade set of automation tools for privacy: consent, DPIA workflows, data minimization, policy enforcement, and auditable governance that stay in sync with live systems.
A scalable, auditable policy engine that enforces privacy rules in real time.
End-to-end consent capture, preference management, and rights requests automation.
Automated data flow catalogs and DPIA workflows that stay in sync with systems.
Comprehensive logs, versioned policies, and rollback paths for incidents.
The privacy problem
Companies have policies, tools, and compliance requirements, yet they lack automated, auditable privacy pipelines that ensure data handling is compliant, visible, and recoverable within live systems.
Organizations report regular privacy practices in at least one function, yet comprehensive automation is limited.
McKinsey State of Privacy 202581%Leaders expect privacy controls to be integrated into AI and automation initiatives.
Industry Privacy Trends 202580%Organizations are prioritizing governance, observability, and rollback in privacy implementations.
Privacy by Design 2024Privacy automation services
A credible privacy program needs an operating model: automated consent, data lifecycle, rights handling, policy enforcement, and auditable controls that stay in sync with your systems.
Transform scattered privacy workflows into governed, auditable production processes with owners and monitoring.
Treat privacy rules and policies as governed actors with identity, approvals, and rollback.
Build data and DPIA pipelines that support privacy rights while controlling cost.
Reduce blast radius with least privilege, temporary credentials, and threat modeling.
Document privacy models, data flows, tools, and rights workflows with governance.
Prioritize technical debt so privacy automation can scale safely.
Practical outcomes
Transform scattered privacy workflows into governed, auditable production processes with owners and monitoring.
Treat privacy rules and policies as governed actors with identity, approvals, and rollback.
Build data and DPIA pipelines that support privacy rights while controlling cost.
Reduce blast radius with least privilege, temporary credentials, and threat modeling.
Document privacy models, data flows, tools, and rights workflows with governance.
Prioritize technical debt so privacy automation can scale safely.