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About cyberhaven

Introducing Cyberhaven Flow, an AI-native data security platform for the agentic enterprise. We set high standards, make confident decisions grounded in sound judgment, and pursue meaningful outcomes with conviction. Winning requires disciplined innovation. Take smart risks, learn quickly, and invest in what creates durable advantage without compromising trust or security. Trust is our foundation. As a team, we earn it through secure systems, reliable execution, and transparency in how work gets done. Focus on results-driven activity. Ownership means prioritizing what matters most, moving with urgency, collaborating early as one team, and seeing work through to meaningful customer impact. Cyberhaven Flow traces the full lifecycle and adapts protection to changing context Understand agent risk posture, discover shadow AI usage, and prevent AI-driven leaks without blocking teams from adopting AI. Protect data and stop exfiltration across email, web, cloud devices, and endpoints, while catching insider threats before they escalate. Protect workflows, not just data, and take action when & where it matters with unified Data Security Posture Management (DSPM), Insider Risk Management (IRM), and Data Loss Prevention (DLP) across endpoints, SaaS, PaaS, and IaaS, powered by data lineage and agentic AI. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context. Today, data is fragmented: copied, pasted, captured in screenshots, embedded, and summarized. In the AI era, data has broken free. Limited visibility into shadow AI usage and AI agents makes it impossible to securely increase AI adoption or prevent new forms of data exfiltration. Teams struggle to map sensitive data at rest and in motion, hindering regulatory compliance and driving up data retention costs. Existing data loss prevention (DLP) tools are operationally complex and fail to prevent data exfiltration across modern endpoints and cloud services. Organizations lack the necessary context and control to manage insider threats and accelerate their incident response effectively. More "workers" as AI agents create, transform, and move data at machine speed of alerts from legacy data security tools are false positives of data exfiltration involves fragments and snippets, not complete files A simpler time: discover, classify, and label files to enforce data movement. Democratized data broke the network perimeter, then the file perimeter, creating data fragments that evade controls. AI tools democratize intelligence, creating exponentially more fragments, derivatives, and pat

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