Cyberhaven
AI-native data security platform that traces the full lifecycle of data to power DLP, insider-risk management, and shadow-AI detection in one product.
Visit Website ↗Overview
Cyberhaven is an AI-native data security platform, “Cyberhaven Flow,” that combines data loss prevention, insider risk management, and DSPM by tracing the complete lineage of data — where it originated and everywhere it has flowed — rather than inspecting content only at a single point in time. Founded in 2016 by CEO Howard Ting and headquartered in Palo Alto, the platform specifically targets “shadow AI” usage, detecting when employees move sensitive data into tools like ChatGPT or Copilot, and uses AI agents (“Linea”) to automate incident investigation.
Cyberhaven’s funding accelerated sharply through 2025: after earlier Series A ($13M, 2019), B ($33M, 2021), and C ($88M, 2024) rounds, it raised a $250 million Series D in 2025 that pushed its valuation to $1 billion, on reported annual recurring revenue of roughly $52.4 million.
Its differentiator is lineage tracing as the core detection primitive — following data’s full path across endpoints, SaaS, and cloud — versus the static, single-point content inspection most legacy DLP tools rely on.
Innovation Matrix Assessment
Rapid platform expansion combining DLP, insider-risk management, and DSPM with new agentic AI investigation features.
Automated, AI-agent-driven investigation ('Linea') is designed to reduce manual incident-triage workload.
Raised $250M in a single 2025 Series D reaching a $1B valuation, on roughly $52.4M ARR.
Data lineage tracing as the core detection model is genuinely different from static, single-point content pattern matching.
Claims found in this research are entirely vendor-sourced; no independent verification was performed.
Explicitly targets shadow-AI data exfiltration, a fast-growing and forward-looking enterprise risk.
Why CISOs Should Care
Targets the newest blind spot — employees pasting sensitive data into ChatGPT, Copilot, and other AI tools — by tracing data lineage rather than only matching content patterns.
What Makes It Different
Cyberhaven's core technical bet is tracking data lineage (where data came from and everywhere it's flowed) rather than inspecting content at a single point in time, meant to catch exfiltration paths pattern-matching DLP misses.
The Matrix Verdict
67/100 — INCREMENTAL INNOVATOR
A fast-growing, well-funded DLP/DSPM hybrid with real momentum ($250M raised in 2025 alone) and a technically distinct lineage-tracing model; mid-to-upper tier, held back mainly by the absence of independently verified efficacy evidence.
Editorial Note: Claims vs. Verified Findings
Funding rounds and ARR figures are drawn from funding-tracker aggregation rather than primary filings since Cyberhaven is private; lineage-tracing and detection-accuracy claims are vendor-sourced and were not independently verified in this research.
Sources
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