AI-native data security platform combining DLP, insider risk, and data lineage
Cyberhaven combines data loss prevention, insider risk management, and data security posture tools into a unified platform designed for AI workloads. The tech stack reveals a mature, distributed systems operation: React + TypeScript frontend, Go + gRPC backend, Kubernetes orchestration across AWS/GCP/Azure, with BigQuery and Bigtable for scale. Active adoption of EDR, GitHub Actions, Terraform, and ArgoCD indicates DevOps-first deployment culture. The engineering-heavy hiring profile (17 of 37 open roles) paired with projects spanning high-volume event monitoring, real-time graph processing, and macOS endpoint sensing suggests Cyberhaven is scaling detection and telemetry infrastructure to handle the complexity of modern data environments.
Cyberhaven protects sensitive data across endpoints, cloud platforms, and SaaS applications using a unified data security platform. The product covers data loss prevention (DLP), data security posture management (DSPM), insider threat detection, and AI security, with deep data lineage and support for agentic AI systems. Founded in 2016 and headquartered in Palo Alto, the company serves mid-market and enterprise organizations navigating the intersection of data protection and rapid AI adoption. Current hiring spans engineering, sales, security, and support across five countries, reflecting both product expansion and go-to-market scaling.
Frontend: React, TypeScript, Material-UI. Backend: Go, gRPC, Python, Java, C#, Scala, Kotlin. Infrastructure: Docker, Kubernetes, AWS, GCP, Azure. Data: BigQuery, Bigtable, Spanner, Redis. Adopting: EDR, GitHub Actions, Terraform, ArgoCD.
Active projects include high-volume event monitoring optimization, cloud infrastructure scaling, real-time graph processing, data movement tracing for endpoints (macOS focus), distributed systems scaling, and operationalizing AI prototypes. Web-based management console development is underway.
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