PrivIQ Data Privacy Management

46 reviews

Data Privacy is one of the most important topics of the decade as we move to a digital economy. Our purpose is building Trust for our clients, between them and their stakeholders by providing clear, concise data privacy compliance management software under a SAAS model. The problem we solve: - Organizations need to be trusted by their clients, employees, suppliers / stakeholders. - This trust has been forced on them by laws and sentiment about data privacy. - Complex and difficult to understand. - Need a collaborative solution. - Expensive without use of guiding technology. - Requires frequent review to ensure ongoing compliance. What you need in order to solve the problem: - Organization-wide data privacy and protection - Demonstrable and proportionate - Employee awareness and understanding - Governance policies - Privacy notices - Compliance in various areas marketing, HR, IT and security, Privacy by design - Service provider and third-party agreements - Subject Access request and breach management - Immutable Consent Records - Ongoing review – weekly / quarterly / bi-annual / annual A flexible framework to address ever evolving data privacy regulatory requirements and market demands. Software features: - Easy to use - Configurable - Collaboration and notification - Dashboards - Reporting Tools - SAAS Service How we are differentiated: Global privacy law compliance service. Multi-lingual. English, Dutch, Greek, Portuguese, Brazilian Portuguese Multiple-legislation Collaborative White labelling for channel partners For: Mid-Tier Enterprise Current Regulations: EU / UK / USA / Turkey / South Africa / Nigeria / Brazil / Thailand / California / Kenya Immutable consent management. PCI DSS – Control Checklists. ISO27001 (2013) – Control Checklists. CIS 8.0 IG1, IG2, IG3 – Control Checklists.

PrivIQ Operational Risk Management

0 reviews

Navigating Risk Frameworks can be a maze of complexity, and resistant to adaptation. PrivIQ's AI-assisted Risk Management Framework does the heavy lifting while you sit in the driving seat. It transforms complex, manual risk management processes into a streamlined, user-friendly experience. By intelligently automating the creation of assessments, policies, and checklists, you save valuable time while ensuring that you remain robustly compliant and ahead of potential risks.

PrivIQ AI Governance

0 reviews

PrivIQ AI Governance helps organisations establish structured oversight for AI systems, vendors, and associated operational risk using a framework aligned to the NIST AI Risk Management Framework (AI RMF). The platform brings AI governance, data privacy, and vendor risk management into a unified environment designed to support responsible AI adoption, regulatory preparedness, and board-level accountability. Core functionality includes AI system mapping, governance policy management, internal and third-party AI risk assessments, governance maturity scoring, policy distribution and acknowledgement tracking, and evidence-based reporting. Organisations can define and tailor governance controls, workflows, assessment methodologies, and reporting structures to align with their own operational, regulatory, or consulting requirements. PrivIQ supports the full AI governance lifecycle across Govern, Map, Measure, and Manage functions. Teams can document AI usage, assess risk exposure, evaluate vendors, maintain oversight records, track remediation activities, and demonstrate governance readiness through structured reporting and audit trails. Key differentiators include: NIST AI RMF-aligned governance structure Fully tailorable governance frameworks, controls, and methodologies Integrated AI vendor risk assessments alongside internal governance workflows AI-assisted generation of policies, controls, assessments, and remediation tasks with editable and verifiable outputs Centralised governance evidence and stakeholder acknowledgement tracking Support for governance maturity measurement and ongoing reassessment processes PrivIQ is designed for organisations needing practical, adaptable AI governance processes that can evolve alongside increasing AI adoption, changing regulations, and growing oversight expectations.