Cyberhaven Data Protection vs MIND Autonomous DLP: Side-by-Side Comparison (2026)

Cyberhaven Data Protection

Mid-market and enterprise security teams drowning in shadow SaaS and generative AI sprawl will get immediate value from Cyberhaven Data Protection because it maps data movement across endpoints, cloud, and AI tools without requiring you to inventory everything first. The autonomous risk detection using Large Lineage Models reduces the manual classification burden that kills most DLP deployments, and the built-in investigation agent actually closes cases instead of just surfacing alerts. Skip this if your organization lacks the API connectivity across your SaaS stack or if you need network-based DLP that doesn't touch endpoints; Cyberhaven is endpoint and cloud-centric, leaving blind spots on the wire.

MIND Autonomous DLP

Mid-market and enterprise security teams drowning in SaaS data sprawl will get the most from MIND Autonomous DLP because it actually finds and classifies sensitive data across GenAI apps, not just legacy file shares. The platform's behavioral analysis of billions of signals catches exfiltration patterns that rule-based DLP misses, and automated response actions mean your team remediates issues instead of triaging alerts all day. Skip this if you need point-in-time compliance scanning for a single repository or your data lives almost entirely on-premise; MIND's real value compounds when you have dozens of SaaS applications and cloud users generating exposure constantly.