Sensitive data exposure
Detect and reduce exposure of PII, PHI, PCI, confidential business data, and restricted client data before it reaches AI or external systems.
DigiTrans PrivacyIQ
Govern privacy risk across enterprise data and AI workflows.
DigiTrans PrivacyIQ is an AI-assisted privacy control plane that helps organizations classify sensitive data, enforce purpose-aware policies, govern AI usage, and produce audit-ready evidence.
Policy Enforcement
AI Governance
Data Minimization
Audit Evidence
Why PrivacyIQ
AI is moving faster than traditional privacy controls.
Enterprises need a repeatable way to approve, enforce, monitor, and prove privacy controls across data pipelines, SaaS applications, AI assistants, model workflows, and regulated data environments.
Purpose and consent drift
Map data usage to consent, lawful basis, purpose limitations, contractual restrictions, and internal policy requirements.
Audit readiness gaps
Capture policy decisions, transformations, approvals, model paths, user actions, and evidence packages for compliance review.
Platform
Privacy intelligence, deterministic enforcement, and evidence in one operating layer.
1
Control Plane Core
Policy engine, consent and purpose controls, data contracts, access controls, retention rules, and audit logging.
2
Intelligence Layer
Data classification, privacy risk scoring, policy gap detection, anomaly detection, and DPIA/PIA assistance.
3
Agentic Workflow Layer
Agent-assisted investigation, remediation drafting, evidence generation, policy recommendations, and case routing.
4
Human Approval Layer
Privacy Ops, Legal, Security, Compliance, and Business Owners approve sensitive decisions and policy exceptions.
5
Enforcement Layer
Approved decisions are enforced across APIs, data lakes, pipelines, access brokers, AI apps, and workflow logs.
AWS Reference Architecture
Built for AWS-native privacy, AI, and data governance.
PrivacyIQ can be deployed as an AWS-aligned control plane using managed services for policy, identity, AI workflows, sensitive data discovery, observability, and immutable evidence.
Request AWS Architecture Review
Amazon Bedrock
Bedrock Agents
Bedrock Guardrails
Verified Permissions
AWS IAM
Lake Formation
Amazon Macie
AWS Glue
API Gateway
AWS Lambda
Step Functions
CloudTrail
AWS Config
Audit Manager
S3 Object Lock
Service Offerings
Start with readiness. Expand into managed PrivacyIQ operations.
1. PrivacyIQ Readiness Assessment
Assess AI privacy risk, data exposure, AWS architecture readiness, policy maturity, and audit gaps.
2. Strategy and Reference Architecture
Define the target operating model, AWS service map, governance controls, architecture roadmap, and implementation plan.
3. PrivacyIQ MVP
Implement priority data flows, policy checks, classification, agent-assisted investigation, approvals, and audit evidence.
4. Platform Modules
Add AI use-case review, consent-purpose enforcement, runtime gateway controls, tokenization, and evidence dashboards.
5. Managed PrivacyIQ Operations
Operate monitoring, policy changes, exceptions, evidence requests, agent governance, and compliance reporting.
Core principle
PrivacyIQ is agent-assisted, not agent-controlled.
Agents can investigate and recommend. The PrivacyIQ control plane validates. Humans approve material decisions. Enforcement executes only approved policy actions and logs every step.
Next Step
Schedule a PrivacyIQ Readiness Assessment.
Use the form to request a 30–45 minute discussion focused on your AI privacy risk, sensitive data exposure, AWS architecture, compliance evidence, and target operating model.
Prefer email? Contact [email protected].