Cyberhaven Pricing 2026

Key Takeaways

Cyberhaven does not publish list prices and uses custom quotes. Its public Enterprise Terms describe billing mechanics, while third-party marketplace data has reported a $37,872 median annual contract value and observed annual contracts ranging from $30,000 to $193,993. These figures are market observations rather than Cyberhaven list prices.
Cyberhaven currently markets AI security within its unified platform. Public materials position DSPM, DLP, Insider Risk Management, and AI security together, while feature-level pricing and package entitlements are not publicly itemized.
Total cost of ownership extends beyond license fees. Cyberhaven describes onboarding, rollout, training, policy tuning, analyst services, and technical account management options, making implementation effort and optional services part of the broader TCO picture.
Nightfall publishes public package information for evaluation. Nightfall publishes its pricing and package structure, feature matrix, and ROI calculator, while final pricing depends on user count and data volume.
Nightfall is built for AI-era data movement. Its AI security platform applies one detection engine across human and agentic workflows, with coverage spanning endpoints, browsers, email, SaaS, AI agents, and MCP security.
Microsoft Purview pricing and coverage depend on workload and licensing. Microsoft 365 and Office 365 E3 include DLP for Exchange, SharePoint, and OneDrive, while additional capabilities use qualifying licensing or pay-as-you-go models.

Understanding Cyberhaven's pricing model requires context about where the platform sits in the broader data loss prevention market and what organizations receive for their investment. As security teams evaluate data exfiltration prevention in 2026, the relevant comparison includes contract mechanics, deployment scope, administrative effort, and coverage for both human and AI-driven data movement.

The DLP market now spans legacy suites, lineage-focused platforms, native cloud controls, and AI data security platforms. Pricing models and public packaging vary considerably. A useful TCO comparison therefore considers software, implementation, operations, integrations, and the range of data movement surfaces covered by each product.

Understanding the Evolving Landscape of Data Loss Prevention

Cyberhaven uses multiple deployment modes, including cloud API connectors, an endpoint agent, and a browser extension. Its endpoint agent supports Windows, macOS, and Linux. Cyberhaven also documents professional services for planning, pilot activity, tuning, rollout, analyst support, and technical account management. These elements can contribute to implementation and operating costs beyond the software quote.

Modern DLP requirements increasingly extend beyond files, email, and sanctioned SaaS applications. AI assistants, coding environments, MCP servers, browsers, and autonomous agents create additional data movement paths. Nightfall's positioning centers on controlling both human and agentic data flows through one AI data security platform.

Cyberhaven's Position in the AI Data Security Market

Cyberhaven differentiates through data lineage capabilities that follow data movement and transformation across supported endpoints, browsers, and cloud applications. That lineage can provide useful investigation context by showing how information changes and moves through connected workflows.

Cyberhaven currently positions its platform as a unified architecture combining Data Security Posture Management, DLP, Insider Risk Management, and AI security. From a TCO perspective, this creates a platform-consolidation model in which several data security functions can be evaluated within one vendor relationship.

Cyberhaven capabilities relevant to package selection and deployment include:

Data lineage tracking: Origin-to-destination visibility for sensitive data movement and transformation across supported surfaces.
Multiple deployment modes: Cloud API connectors, an endpoint agent for Windows, macOS, and Linux, and browser-based coverage.
Unified platform scope: DSPM, DLP, IRM, and AI security in the company's current platform positioning.
Professional services options: Onboarding, analyst support, technical account management, and related implementation services.

Cyberhaven's public positioning presents AI security as part of its unified platform. Public materials do not itemize feature-level pricing or package entitlements, so the article keeps those commercial details at a high level.

For organizations comparing lineage-focused DLP with Nightfall, the architectural emphasis differs. Cyberhaven emphasizes lineage and investigation across supported surfaces. Nightfall starts with AI-native content and context detection, then applies relevant lineage, risk scoring, and inline controls to the events that matter. Nightfall also extends the same detection approach across SaaS, endpoints, browsers, email, local and remote MCP, and agentic workflows. The Nightfall vs Cyberhaven comparison provides additional product-level context.

Cyberhaven Pricing Structure and Considerations for 2026

Cyberhaven does not publish a public list price and uses custom quotes. Its public Enterprise Terms describe several billing mechanics, including fees based on endpoint users and/or endpoint usage, annual advance invoicing for direct purchases unless otherwise specified, Net 30 payment terms unless the applicable Order Form or statement of work specifies otherwise, and prorated charges for excess usage.

Available pricing intelligence includes:

Median annual contract value: Vendr currently reports a $37,872 median annual contract value. This is third-party marketplace data rather than a Cyberhaven list price.
Observed contract range: Vendr has shown annual contracts ranging from $30,000 to $193,993.
Pricing basis: Cyberhaven's Enterprise Terms state that fees can be based on endpoint users and/or endpoint usage.
Payment mechanics: Cyberhaven's Enterprise Terms state that direct purchases are normally invoiced annually in advance and payable within 30 days unless the applicable Order Form or statement of work specifies otherwise.
Overage charges: The Enterprise Terms provide for prorated excess-user or excess-usage charges through the end of the applicable order-form term.

Because list prices are not public, exact software budgeting depends on the quoted commercial package. Public terms still provide useful information for modeling billing structure, usage growth, and service-related cost categories.

Factors that can influence Cyberhaven pricing and TCO include:

Endpoint users and usage: Public terms allow fees to be based on endpoint users and/or endpoint usage.
Integration scope: Integration requirements can affect implementation and services scope.
AI and Linea entitlements: AI security is part of Cyberhaven's unified platform positioning, while feature-level package details remain quote-specific.
Professional services: Implementation, training, onboarding, analyst services, installation, and technical account management can be separately scoped.
Usage limits and overages: Contracted user or usage limits can result in prorated excess charges.

This quote-based structure makes TCO more useful than a single headline license figure. Software cost, service scope, implementation effort, policy management, and growth in protected users or data volumes all contribute to the overall financial model.

Evaluating Cyberhaven's Value Proposition for Data Security

Cyberhaven's value proposition centers on data lineage, investigation, and consolidation. Its materials position lineage as a way to understand how sensitive information moves and changes, while its unified platform brings DSPM, DLP, IRM, and AI security into one product strategy.

Potential TCO value drivers include:

Investigation context: Data lineage can connect related movements and transformations to support analyst investigations.
Tool consolidation: Cyberhaven positions its platform as a way to combine several data security functions within a unified architecture.
Email protection: Cyberhaven supports policies for external and personal email, recipient-based controls, and distinctions between corporate and personal accounts.
Insider risk management: IRM is part of Cyberhaven's current unified platform positioning.
Multiple control surfaces: Endpoint, browser, and cloud connector deployment modes provide coverage across supported environments.

Cyberhaven's lineage-centric approach can be useful when deep provenance and movement history are primary requirements. Nightfall takes a different approach by using AI-native detection to identify risky content and context first, then providing focused investigation context and enforcement. This detection-first model is designed to reduce low-value alert volume while supporting data detection and response across modern collaboration and AI workflows.

Cyberhaven's Deployment Architecture and TCO

Cyberhaven's architecture includes cloud API connectors, an endpoint agent, and a browser extension. The endpoint agent supports Windows, macOS, and Linux, while browser coverage can extend visibility to web-based data movement and certain unmanaged-device scenarios.

Deployment capabilities include:

Endpoint agent: Visibility and policy enforcement across supported Windows, macOS, and Linux systems.
Cloud API connectors: Coverage for supported sanctioned cloud applications.
Browser coverage: A browser extension for web-based data movement, including a standalone option for certain unmanaged or contractor devices.
Structured services: Planning, pilot, tuning, rollout, analyst services, and technical account management options.

These deployment modes give Cyberhaven several ways to cover enterprise data movement. TCO can include endpoint rollout, connector configuration, browser deployment, policy tuning, integrations, internal administration, and optional services.

Nightfall similarly spans endpoint, browser, SaaS, email, and AI environments, but its product narrative is organized around one detection brain across those surfaces. Its endpoint and browser DLP coverage combines human and AI-related data movement controls, while its MCP capabilities extend protection into local and remote agentic workflows.

Comparing Cyberhaven to Microsoft Purview DLP

Microsoft Purview is a practical pricing and capability benchmark for organizations already invested in Microsoft 365. Its 2026 licensing model includes a mixture of suite entitlements, workload-specific requirements, and pay-as-you-go capabilities.

Microsoft Purview DLP considerations include:

E3 coverage: Office 365 and Microsoft 365 E3 include DLP for Exchange, SharePoint, and OneDrive.
E5 and workload-specific licensing: Teams chat DLP requires qualifying E5-class licensing, while Microsoft 365 E5 with Teams is currently listed at $60 per user per month when paid yearly.
Billing models: Microsoft Purview supports both per-user and pay-as-you-go billing for different capabilities.
Non-Microsoft coverage: Purview supports DLP for connected apps including Google Workspace and Salesforce through a capability that Microsoft currently documents as preview.
Detection methods: Purview supports sensitive-information types, machine learning, Exact Data Match, trainable classifiers, document fingerprinting, and named-entity detection.
AI coverage: Purview Network Data Security supports interactions with services such as ChatGPT, Gemini, and Claude, while other AI governance scenarios use separate connectors and billing paths.

Organizations that already hold relevant Microsoft 365 entitlements may have no incremental license cost for included Purview capabilities. Other capabilities can introduce additional licensing or consumption-based charges.

Cyberhaven emphasizes lineage and investigation across its supported environment. Purview emphasizes integration with Microsoft 365 plus a growing set of endpoint, connected-app, network, and AI controls. Nightfall differentiates by bringing AI-native detection and real-time data movement control across SaaS, endpoints, browsers, email, and agentic workflows into one data security platform. The Nightfall vs Microsoft Purview comparison outlines that distinction in more detail.

Why Nightfall AI Stands Out for AI-Era Data Security

Nightfall is the AI security platform built to control AI agents and all data they touch. Its architecture is designed for both human and agentic data movement, with comprehensive coverage across endpoints, MCP servers, email, browsers, and SaaS.

AI agents create a different control problem from traditional human-driven workflows because they can autonomously access, transform, and move enterprise data. Nightfall addresses that problem with AI-native detection and inline data controls rather than treating AI security as a separate visibility layer.

Nightfall's differentiated approach includes:

One detection brain across surfaces: Nightfall applies detection and risk scoring across SaaS, endpoints, browsers, email, AI agents, and MCP workflows.
AI-native detection: Nightfall reports 95% detection precision out of the box and uses contextual, model-based detection rather than relying only on regex or keyword matching.
Agentic coverage: Nightfall supports local stdio and remote HTTP MCP, IDE hooks, shadow MCP discovery, tool-capability risk scoring, prompt-injection detection, and inline enforcement through its MCP security capabilities.
Real-time remediation: Nightfall supports actions such as redact, delete, revoke permissions, quarantine, block, and encrypt where supported by the underlying platform.
Public package information: Nightfall publishes its pricing page, package structure, feature matrix, and ROI calculator before final quote creation.
Rapid deployment: Nightfall is designed to deploy in minutes for supported SaaS and endpoint use cases, with agentic deployments scaling according to scope.
Unified operating model: DLP, insider risk, AI governance, and agentic data protection can operate through one platform rather than separate control planes.

Nightfall's current pricing page makes its product scope easier to evaluate before commercial discussions. It publicly separates organization-wide AI-native DLP coverage across SaaS, email, GenAI apps, endpoints, and browsers from expanded AI-agent, MCP-server, IDE, and MCP gateway coverage. The packages use the same policy engine, pre-trained ML detectors, and LLM classifiers, giving organizations a consistent control model across human and agentic data movement.

The architectural difference is particularly important for AI-era data movement. Data lineage remains useful for investigation, but Nightfall prioritizes identifying risky data and context first so analysts can focus on the lineage and events that matter. The same detection engine then extends into agentic surfaces such as MCP, IDE-based agents, and other AI workflows, with inline control built into the platform.

For total cost of ownership, Nightfall combines AI-native detection, public package information, streamlined deployment, and automated remediation. Its public ROI model includes assumptions around reduced manual investigation effort, while actual outcomes depend on each organization's environment and deployment scope.

Frequently Asked Questions

How do contract renewals typically work with enterprise DLP vendors like Cyberhaven?

Cyberhaven's current public Enterprise Terms state that each Order Form's initial term is specified in the Order Form. The terms do not establish a universal renewal cadence or notice period. Renewal pricing and mechanics remain deal-specific under a quote-based model and depend on the applicable agreement and Order Form.

What costs can exist beyond Cyberhaven's quoted license price?

Beyond the core software quote, Cyberhaven documents optional implementation, training, installation, onboarding, analyst, and technical account management services. Internal labor for deployment, policy tuning, integrations, and change management can also affect TCO. AI and Linea capabilities are part of Cyberhaven's current unified platform positioning, while exact package entitlements remain quote-specific.

Can organizations pilot Cyberhaven before a broader rollout?

Cyberhaven has published customer examples that used a proof of concept before wider deployment, including a 50-user PoC for Mission Australia. Its services materials also describe pilot and tuning as part of the implementation model. A pilot can cover endpoint and browser scope, integrations, policy behavior, detection quality, workflow fit, and production deployment requirements.

How does Cyberhaven pricing compare with building DLP capabilities internally?

A build-versus-buy comparison depends on the organization's required control surfaces and operating model. Internal scope can include endpoint controls, SaaS integrations, classifiers, enforcement workflows, investigation tooling, reporting, maintenance, and AI-agent security. Because Cyberhaven uses quote-based pricing, the commercial comparison varies by deployment size and package scope. Internal development costs likewise depend on engineering requirements, maintenance burden, and the breadth of coverage required. Nightfall provides an additional alternative for organizations that want one AI data security platform across human and agentic data movement. Its data exfiltration prevention, AI-native detection, and MCP controls are designed to cover SaaS, endpoint, browser, email, and AI-agent workflows through a unified architecture.

What contractual topics commonly affect enterprise DLP purchases?

Common enterprise DLP contract topics include service levels, support terms, data-processing obligations, data-retention and deletion provisions, renewal mechanics, price-protection language, ownership of custom policies, termination assistance, usage limits, overage treatment, and audit rights. Cyberhaven's public Enterprise Terms provide its standard baseline, while final commercial terms are defined by the applicable agreement and order form.