Melurna
Melurna provides continuous, evidence-based monitoring of sensitive data movement across websites, applications, and customer journeys, revealing hidden vendors, AI services, and downstream recipients beyond the first vendor hop. The platform observes actual network traffic without requiring agents or integrations, mapping complete data journeys and surfacing gaps between stated privacy disclosures and observed behavior. It connects these findings to enterprise risk, regulatory compliance, and cyber insurance underwriting decisions.
- Cybersecurity
- Regulatory & Compliance Technology
- Data & Analytics
- Software Only
- Insurance Technology
- Artificial Intelligence
Funding
Founders
Founder details are not available yet.
Product
Problem
Organizations lack visibility into where their sensitive data actually travels after it is shared with third-party vendors. Vendors may pass data to downstream recipients, AI services, or fourth parties without the organization's knowledge, creating hidden privacy, cyber, and regulatory exposure that self-reported questionnaires fail to capture.
Solution
Melurna provides continuous, evidence-based monitoring of sensitive data movement across websites, applications, and customer journeys. The platform observes actual network traffic from AI agents, applications, and browsers to map complete data journeys—including hidden recipients beyond the first vendor hop. It identifies stated-versus-observed gaps between privacy disclosures, consent behavior, AI usage, and actual data flows. The platform connects these findings to enterprise risk, regulatory frameworks, and underwriting decisions, enabling organizations to prioritize remediation based on observed data exposure rather than vendor self-attestation. No agents or integrations are required, and the platform preserves request and initiator context for each data transfer.
Target Audience
Primary customers are enterprise security, privacy, legal, compliance, and AI governance teams, as well as cyber insurers needing underwriting, portfolio, claims, and risk-engineering support based on observed data flows.
Features
- Real-time monitoring of AI agent, application, and browser traffic with request and initiator context preserved
- Sensitive-data journey mapping for user, session, device, transaction, health, and credential data across domains
- Hidden recipient chain discovery revealing first-, third-, and fourth-party data destinations
- Stated-versus-observed gap analysis surfacing discrepancies between disclosures, consent, AI use, and residency
- AI third-party risk management with continuous vendor monitoring, downstream provider tracking, and evidence gap identification
- Shadow AI discovery finding unapproved models, agents, and AI-enabled vendors with their sensitive-data paths
- Regulatory framework mapping that continuously aligns observed vendor behavior to compliance obligations
- Remediation workflows that turn prioritized findings into accountable tasks with verified closure