Skip to main content
New · Covered by TechCrunch: MELURNA traces hidden third-party data flows.Read the research
Request Intelligence
Menu
Platform
Solutions

Enterprise

For EnterprisesUnify cyber, privacy, AI, and third-party risk around observed data movement.

Insurance

For Cyber InsurersSupport underwriting, portfolio, claims, cyber, privacy, AI, and risk-engineering decisions.

By team

Security & Enterprise RiskPrioritize threats by the sensitive data, vendors, and business impact they can reach.Privacy, Legal & ComplianceCompare sensitive-data behavior with consent, disclosures, contracts, and obligations.AI GovernanceGovern AI by connecting every service to its data, purpose, recipient chain, and change history.

By industry

FinanceMap customer and transaction data across vendors and regulated boundaries.HealthcareVisualize PHI journeys across apps, devices, analytics, and vendors.View All IndustriesExplore how Melurna applies across regulated and data-intensive industries.
Company
Research
Request Intelligence

Privacy, legal, and compliance

See where behaviordiverges from policy.

Compare sensitive-data movement with consent, GPC signals, disclosures, contracts, approved purposes, and regulatory obligations.

Compare policy with behavior
Product evidence
Policy Gap Review
Illustrative Melurna policy-gap review comparing stated policy with observed downstream data recipients
Policy ↔ Behaviordisclosure alignment
GPC + Consentcontrol validation
Recurringchange detection

Decision view

Policy says one thing. The recipient chain shows another.

Place the documented promise beside the observed request, recipient, and consent state so counsel can focus review on the material difference.
Documented promiseSharing limited to service providers

Consent and purpose defined in policy.

Observed behaviorRecipient chain extends downstream

Additional service receives sensitive data.

Review requiredDisclosure and consent alignment

Focus counsel on the material difference.

Map sensitive-data behavior

Follow personal, account, health, transaction, session, device, and credential data through direct and downstream recipients.

  • Raw and transformed data
  • Recipient ownership and role
  • Purpose and geography context
Illustrative Melurna vendor-chain record showing an approved vendor, a downstream AI service, sensitive data, disclosure status, and preserved evidence
Vendor Chain

Validate consent controls

Compare what happens before and after reject, accept, no-action, and GPC states to determine whether privacy mechanisms change data sharing as intended.

  • Consent-state comparison
  • GPC signal response
  • Pre-consent transmission
Illustrative Melurna compliance drift view comparing approved statements with current observed data journeys and material changes
Compliance Drift

Compare behavior with obligations

Review observed paths against disclosures, contracts, approved uses, retention expectations, data-residency requirements, and regulatory frameworks.

  • Stated-versus-observed gaps
  • Vendor and subprocessor review
  • Regulatory context
Illustrative Melurna privacy-risk register showing material findings, severity, remediation steps, and change evidence
Privacy Risk Register

Preserve the decision record

Keep each issue connected to its supporting observation, owner, remediation decision, policy update, and evidence refresh.

  • Review-ready evidence
  • Accountable remediation
  • Historical change record
Illustrative Melurna remediation verification view showing changed recipients, workflow ownership, and evidence-backed confirmation
Remediation Verification

Continue exploring

Enterprise risk intelligenceFollow sensitive data wherever it goes.Security and enterprise riskPrioritize the risk the data can reach.Enterprise AI governanceGovern AI by following the data.

Data Risk Review

See where data movement diverges from policy.

Request a privacy and compliance evidence review.

Compare policy with behavior Start with one policy, customer journey, or vendor relationship.