Cyberhaven in 2026: Lineage-First DLP, What It Does Well, and Where It Fits

Short answer: Cyberhaven is a data security platform built on data lineage: it tracks where content came from and how it moved, then uses that history to flag risky flows across endpoints, browsers and cloud apps. It is strong for investigation and insider risk. For most 250 to 5,000 person companies, though, the control that stops the everyday leak is a meaning-based block at the moment of upload or prompt, enforced by the same on-device agent that already handles web security. That is the model dope.security uses, with DLP and the secure web gateway in one agent and one console.

Cyberhaven has had a busy two years: a $1 billion valuation, a unified platform launch, AI agents for detection and investigation, and a new product called Flow. If it is on your shortlist, start with our comparison of the 12 best DLP tools in 2026 for the wider field. This post goes deep on one vendor.

We will cover what Cyberhaven does, what changed in 2026, where lineage shines, where it adds weight, and how it compares with an on-device approach like Dopamine DLP, dope.security's AI-powered endpoint DLP. If you are weighing the architecture question first, our explainer on endpoint DLP vs network DLP is a good primer.

What is Cyberhaven?

Cyberhaven describes itself as an AI and data security platform powered by data lineage. Instead of only inspecting a file when it leaves, it records the chain of events behind that file: where the content was created, which apps touched it, who copied it, and where fragments ended up. When something sensitive heads for an exit, the platform can weigh where it came from as well as what it looks like.

The product is delivered through an endpoint sensor, browser extensions and SaaS connectors, according to third-party reviews. On top of the lineage engine, Cyberhaven sells DLP, insider risk management, data security posture management (DSPM) and AI security, all under one platform name.

The company is growing fast. Cyberhaven reported record revenue and customer growth for its fiscal year ending January 31, 2026, and raised a Series D at a $1 billion valuation in 2025. It is a serious vendor, not a niche startup.

What changed at Cyberhaven in 2026

Three announcements define Cyberhaven's 2026 story. Each one widens the platform, and each one is worth understanding before you sign.

Unified AI and Data Security Platform (February 2026)

In February 2026 Cyberhaven announced general availability of a unified platform combining DSPM, DLP, insider risk and AI security. The pitch is near-real-time lineage across cloud applications, endpoints and on-prem systems, with AI classification and agentic AI to detect risky flows and guide response.

Linea AI agents

Cyberhaven's Linea AI layer includes a Detection Agent, which looks for risky behavior without predefined policies, and an Analyst Agent, which launches investigations using multimodal content understanding. Third-party reviewers note that Linea AI is an optional purchase, so confirm what is in your quote.

Cyberhaven Flow (July 2026)

On July 28, 2026 Cyberhaven introduced Flow, which it calls an AI-native data security platform for the agentic enterprise. Flow discovers AI tools and agents running on endpoints and in the browser, scores them for risk, and records agent activity including prompts, tool calls, file reads and responses. Cyberhaven Labs also claims endpoint-based agentic AI app adoption reached 60 percent in May 2026. That figure is the vendor's own research, so treat it as directional.

Where lineage-first DLP shines

Lineage is a real idea, not a marketing word. It solves a problem pattern matching cannot: content that has been copied, renamed, split or pasted into a new document often loses the signals regex rules depend on. If you know it came from the finance share or the source code repo, you can still treat it as sensitive.

• Investigations: when an incident happens, a full movement history answers "where did this come from and who else touched it" without days of log stitching.
• Insider risk: departing-employee and slow-exfiltration cases benefit from seeing a pattern over weeks, not a single event.
• Fragmented content: lineage can follow a paragraph copied from a sensitive file into a chat window, which content-only rules can miss.

If your program is built around a dedicated insider risk team with analysts who live in investigations, lineage is a strong fit. That is the buyer Cyberhaven serves best.

Where it adds weight for a mid-market team

The same breadth that appeals to a large data security team can be a lot to run for a lean IT and security group. Here is what customers and reviewers raise, and what to ask about.

• Another agent and another console. Cyberhaven is a data security platform, not a secure web gateway. You still need URL filtering, SSL inspection, malware protection and tenant controls from somewhere else, which usually means a second endpoint agent and a second console.
• Modular purchase. DLP, DSPM, insider risk, AI security and the Linea AI agents are presented as one platform, but reviewers report some pieces are optional purchases. Map each requirement to a line on the quote.
• Pricing model. Third-party reviews report enterprise terms billed on endpoint users and/or endpoint usage, invoiced annually in advance. Ask how agent and AI-tool activity affects usage-based charges.
• Tuning a graph. Lineage policies depend on knowing which sources are sensitive. Somebody has to define and maintain those sources as the business changes.

None of this makes Cyberhaven a bad product. It makes it a product designed for a specific operating model.

Deployment and day-two operations

Buying a DLP platform is the easy part. Living with it is where mid-market teams win or lose. Three operational questions decide how much Cyberhaven will cost you in people time, and they apply to any lineage-first product.

First, rollout. Cyberhaven's coverage depends on its endpoint sensor, its browser extensions and its SaaS connectors all being in place. Each layer has its own deployment path, its own update cadence and its own failure mode. A browser extension that a user disables or a connector that loses its token creates a blind spot that the lineage graph cannot fill.

Second, policy ownership. Lineage policies are only as good as the list of sources marked sensitive. That list changes every time the company launches a product, opens a new data room or reorganizes a shared drive. Somebody has to own it, and in a lean team that somebody is usually also on call for the SWG, the IdP and the MDM.

Third, alert handling. Cyberhaven's Linea AI agents are designed to cut investigation time, which is a real benefit. Ask how many alerts a company your size sees in the first 30 days, and whether the agents are in your quote. The best detection model in the world still needs a human to decide what to do with a finding.

By contrast, an on-device approach that classifies by meaning at the moment of upload has fewer moving parts to keep in sync. The Fortune 100 customer that rolled dope.security out to more than 18,000 devices did it silently via Intune, with no per-device configuration.

Cyberhaven vs dope.security: two ways to stop the same leak

Take the most common 2026 incident: an employee pastes customer data into a personal ChatGPT account, or uploads a contract to a personal drive. Here is how each approach handles it.

Cyberhaven

The Cyberhaven sensor and browser extension see the paste or upload, consult lineage to decide whether the content came from a sensitive source, apply AI classification, and enforce the policy. The event joins a movement history that analysts can investigate later. Web filtering and tenant control for that same ChatGPT session come from a separate product.

dope.security

The dope.security agent is already inspecting the session on the device as the secure web gateway. Dopamine DLP extracts the text on the device and classifies it by meaning with an LLM under zero data retention, so it recognizes a contract or a list of patient records without regex rules or source tagging. Cloud Application Control can allow the corporate ChatGPT tenant and block the personal account on the same domain. One agent, one policy, one console.

• Detection model: Cyberhaven leans on where content came from plus classification; dope.security reads what the content means at the moment it leaves, with no rules to write.
• Web security: Cyberhaven needs a separate SWG; dope.security is the SWG, with on-device SSL inspection, URL filtering and anti-malware.
• Personal vs corporate AI: Cyberhaven governs the data in the session; dope.security governs the data and which tenant the user can sign into.
• Footprint: Cyberhaven adds its own sensor and extensions; dope.security runs in one agent under 100 MB of RAM on Mac and Windows.
• Time to value: lineage needs sensitive sources defined; Dopamine DLP is zero-config, so value starts on day one.
• Investigation depth: Cyberhaven's lineage history is deeper for long-running insider cases; dope.security gives a human-readable Dopamine summary of each detection, which is usually what a lean team needs.

Data at rest is a separate question. Cyberhaven sells DSPM. dope.security covers shared files in Google Workspace and Microsoft 365 with CASB Neural, which finds externally shared files and remediates them in one click.

Who should buy Cyberhaven, and who should not

Cyberhaven makes sense if you have a dedicated insider risk or data security team, a mandate to reconstruct incidents end to end, and an existing SWG you plan to keep. In that world, lineage is additive and the extra agent is a known cost.

It makes less sense if you are a mid-market company that needs web security, AI governance and DLP from a small team. Running a DLP platform next to a separate SWG means two agents, two policy models and two vendors to call when something breaks. An AI SaaS company that replaced Cisco Umbrella with dope.security for SWG and DLP together is a good example of the consolidated alternative.

Questions to ask Cyberhaven in your evaluation

Use these to turn a strong demo into a comparable quote. Most of them apply to any data security platform.

• Which capabilities in the demo are in the base platform, and which are add-ons such as Linea AI or DSPM?
• How is usage measured for pricing, and how do AI agents and automated tools count?
• What runs on the endpoint, how much memory does it use, and how does it behave on macOS?
• How long until lineage-based policies are tuned for our environment, and who maintains the sensitive-source list?
• Which secure web gateways have you validated running alongside your sensor?
• Can you block a personal AI account while allowing the corporate tenant, or does that require another product?

Compare the answers against peers we have reviewed, such as Code42 Incydr's approach to insider risk and Digital Guardian's kernel-level endpoint DLP.

The bottom line on Cyberhaven

Cyberhaven's lineage engine is one of the more original ideas in DLP, and it pays off for teams built around investigations. For most mid-market companies, though, the leak that matters happens in a browser or AI app, and the cheapest place to stop it is the agent already inspecting that traffic. That is why dope.security puts meaning-based Dopamine DLP inside the Fly-Direct SWG. Start dope.security free or book a demo to see a blocked upload and its Dopamine summary in under a minute.

Frequently Asked Questions

What does Cyberhaven do?

Cyberhaven is a data security platform that uses data lineage to track where content came from and how it moves across endpoints, browsers and cloud apps. It combines DLP, insider risk, DSPM and AI security, with Linea AI agents for detection and investigation. It does not position itself as a secure web gateway.

Is Cyberhaven a DLP tool?

Yes. DLP is a core part of Cyberhaven's platform, alongside insider risk management and DSPM. Its difference from traditional DLP is that policies can consider a file's history and origin, not only its content. dope.security takes a content-meaning approach with Dopamine DLP built into its on-device SWG.

What is Cyberhaven Flow?

Cyberhaven introduced Flow on July 28, 2026 as an AI-native data security platform for AI agents and people. It discovers AI tools and agents on endpoints and in browsers, scores them for risk, and records agent activity such as prompts, tool calls and file reads. Confirm which Flow capabilities are included in your license.

How is Cyberhaven priced?

Cyberhaven does not publish list prices. Third-party reviews report enterprise terms billed on endpoint users and/or endpoint usage, invoiced annually in advance, with some modules such as Linea AI sold as options. dope.security publishes its packaging and lets you start the SWG free.

Do I need a secure web gateway if I buy Cyberhaven?

Usually yes. Cyberhaven protects data movement but does not market URL filtering, SSL inspection for web threats, anti-malware or SaaS tenant controls. dope.security combines all of those with Dopamine DLP in one agent, which removes the need to run two endpoint products.

What is a good Cyberhaven alternative for mid-market companies?

For teams that need web security, AI governance and DLP without a dedicated insider risk staff, dope.security is a strong alternative. It runs SSL inspection, Cloud Application Control and meaning-based Dopamine DLP on the device under 100 MB of RAM, with zero-config DLP that works on day one.