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New · Covered by TechCrunch: MELURNA traces hidden third-party data flows.Read the research
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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.
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For enterprises

One data path.Every risk team.

Give security, privacy, legal, compliance, AI governance, and enterprise risk teams the same observed facts with decision-specific context.

Review enterprise exposure
Product evidence
Evidence Methodology
Illustrative Melurna evidence methodology showing observation, recipient resolution, policy comparison, risk context, and preserved proof
Cyber, Privacy & AIconnected enterprise risk
1st → nth partyrecipient-chain visibility
Shared evidencecross-functional decisions

Decision view

The evidence stays shared. The decision changes by role.

Use one recipient chain to prioritize a security issue, review a privacy promise, govern AI use, route remediation, or brief enterprise leadership.
Observed recipient chainOne shared evidence record
SecurityPrioritize material exposure
Privacy + LegalCompare behavior with policy
AI GovernanceReview observed AI use
Enterprise RiskSee shared dependencies

Connect enterprise risk

Bring cyber, privacy, AI, compliance, and third-party risk into a shared operating view grounded in the same observed data movement.

  • Common risk vocabulary
  • Shared evidence records
  • Clear ownership and escalation
Illustrative Melurna journey change monitor comparing a current sensitive-data path with the previously observed recipient chain
Journey Change Monitor

Reveal the extended enterprise

See direct vendors, embedded services, AI systems, subprocessors, and nth-party recipients connected to public-facing data journeys.

  • Vendor and recipient ownership
  • Sensitive-data paths
  • Cross-border and concentration risk
Illustrative Melurna finance data-lineage view following payment data from a public journey to a downstream fraud model
Finance Data Lineage

Detect material change

Compare recurring observations with prior behavior, consent choices, disclosures, approved uses, and enterprise policy.

  • New recipient relationships
  • AI and policy drift
  • Risk-prioritized change
Illustrative Melurna healthcare data-lineage view following patient data from intake to a downstream AI service
Healthcare Data Lineage

Move from evidence to action

Give operators and executives the context they need to prioritize remediation, govern exceptions, and communicate material exposure.

  • Team-specific workflows
  • Executive and board reporting
  • Verified remediation
Illustrative Melurna vendor-chain record showing an approved vendor, a downstream AI service, sensitive data, disclosure status, and preserved evidence
Vendor Chain

Continue exploring

Security and enterprise riskPrioritize the risk the data can reach.Privacy, legal, and complianceSee what the policy cannot show.Enterprise AI governanceGovern AI by following the data.

Data Risk Review

Give every enterprise risk team the same view of the data.

Start with one company, domain, vendor relationship, or portfolio.

Review enterprise exposure Bring one company, application, vendor, or customer journey.