Make privacy accountability defensible across assessments, AI reviews, profiling, retention, deletion, exceptions, incidents, evidence, reporting, and regulatory change.
Structure privacy reviews for initiatives, products, campaigns, vendors, data sharing, high-risk processing, and business changes.
Assess privacy risks from AI systems, ML models, generative AI workflows, training data, automated decisions, and AI vendors.
Govern automated decision-making, profiling, eligibility logic, significant effects, review rights, notices, opt-outs, and decision evidence.
Map retention rules to systems, records, processing activities, owners, legal holds, exceptions, execution workflows, and evidence.
Coordinate deletion and suppression across systems, vendors, backups, apps, data stores, processors, and downstream platforms.
Track privacy risks, unresolved issues, accepted risks, exceptions, blockers, mitigation plans, owners, deadlines, and reviews.
Manage personal data incidents through intake, impact assessment, affected data analysis, legal review, notifications, and decision records.
Collect and link evidence across rights, assessments, consent, vendors, incidents, retention, transfers, policies, and approvals.
Provide operational, executive, and board visibility into privacy requests, assessments, consent, retention, transfers, incidents, risks, and evidence.
Track privacy laws, jurisdictional requirements, obligations, enforcement trends, rule changes, and operational impact areas.
Prepared privacy risk, exception, incident, retention, transfer, and evidence packages for regulated review.
Evidence records are permissioned, time-stamped, linked to the originating workflow, and designed for defensible review.