Lakera established itself as a provider of AI application runtime guardrails, focusing primarily on prompt injection defense for custom-built LLM applications. Following its acquisition by Check Point in October 2025, organizations are evaluating alternatives that address broader AI data security requirements beyond runtime screening.
For security teams managing sensitive data across AI agents, copilots, MCP servers, endpoints, and SaaS applications, choosing a unified AI data security platform can help organizations govern both human and AI-driven data movement in real time. This guide examines seven alternatives that serve different enterprise security needs in 2026, including Nightfall AI's approach to unified visibility and control across supported data movement surfaces.
Key Takeaways
- Unified policy enforcement: Platforms designed to cover SaaS, endpoints, email, browsers, and AI agents provide coordinated policy enforcement across supported integrations
- AI-native detection reduces alert fatigue: Nightfall's ML and LLM classifiers deliver 95% detection precision on customer data during a limited proof of value, helping reduce false positives and freeing security teams to focus on genuine risks
- MCP security is now essential: AI agents using Model Context Protocol move data autonomously through tool calls; security platforms can cover local stdio, remote HTTP, and MCP gateway workflows to reduce data exfiltration risks through agent chains
- Deployment speed impacts time to value: Platforms offering same-day deployment through existing infrastructure can establish security controls sooner rather than requiring extended implementation cycles
- Real-time control supports prevention: Detection alone provides visibility into potential risks, while effective platforms provide inline blocking, coaching, and automated remediation across supported data movement surfaces
1. Nightfall AI
Nightfall AI delivers a unified AI data security platform built to control data movement across humans and AI agents in real time. Unlike Lakera's original focus on runtime guardrails for custom applications, Nightfall provides unified coverage across SaaS, endpoints, email, browsers, and AI agent workflows, including MCP security for local and remote agent operations.
How Does Nightfall AI Work?
Nightfall's platform uses AI-native detection powered by supervised fine-tuned models to identify sensitive data across supported data movement surfaces. Key capabilities include:
- Unified Detection Engine: The same ML detectors and LLM classifiers operate across 12+ SaaS applications, supported endpoints, email, browsers, and AI agents, achieving 95% precision on customer data during limited proofs of value
- MCP Coverage: Security for local stdio, remote HTTP/SSE, and MCP gateway workflows, with risk scoring and tool classification for read, read/write, and destructive actions
- Real-Time Control: Block, coach, override, and automated approval workflows that help stop policy-violating data movement before sensitive information leaves supported channels
- AI Agent Security: Coverage for Cursor, Claude Code, VS Code, and other IDE-embedded agents, plus prompt injection detection on supported agent workflows
- Rapid Deployment: 10-minute setup for SaaS integrations and same-day endpoint deployment via MDM
Detection and Response Capabilities
Nightfall's detection engine uses ML detectors for PII, PHI, secrets, credentials, and financial data, plus LLM classifiers across 20+ categories. The platform includes:
- AI-assisted detection, investigation, and response that help reduce manual investigation time
- Continuous telemetry capturing data movement across supported integrations
- Rich investigation context including HRIS/IdP metadata, session replay, and endpoint lineage
- Multi-channel alerts through Slack, Teams, email, Jira, and on-device notifications
Privacy and Compliance
Nightfall maintains SOC 2 Type II and ISO 27001 certifications. The platform supports HIPAA, PCI, GDPR, and other regulatory frameworks through pre-built compliance templates and granular remediation actions including redact, delete, revoke, quarantine, and encrypt.
Best For: Enterprises seeking a unified AI data security platform that covers SaaS, endpoints, email, browsers, and AI agents through supported integrations, with real-time blocking capabilities and high-precision detection that helps reduce false positives versus legacy DLP.
2. HiddenLayer
Primary Focus
HiddenLayer focuses on enterprise AI lifecycle security, providing model-level protection and runtime guardrails for AI applications and agents. The company provides scanning and runtime security for ML model artifacts alongside sensitive-data exposure controls.
Key Features
- Model security scanning across multiple formats for backdoors, tampering, and serialization vulnerabilities
- AI supply chain protection for model artifacts and dependencies
- Runtime guardrails for AI applications and agents, including sensitive-data exposure controls
- MCP workflow support for agent security
- SOC 2 Type II and ISO 27001 compliance
- Patented detection technology for model-specific threats
Coverage Considerations
HiddenLayer supports model security, AI application runtime protection, and MCP-related agent security workflows. Its platform emphasizes model scanning, AI supply chain security, and runtime guardrails, while SaaS and endpoint DLP address related enterprise data movement use cases.
Nightfall Differentiation
Nightfall provides unified coverage across SaaS, endpoints, email, browsers, and AI agents through one platform, consolidating policy management and enforcement across supported workflows. Nightfall's 95% detection precision on customer data during limited proofs of value helps reduce false-positive alerts, while same-day deployment through existing infrastructure enables faster time to enforcement. Nightfall also delivers real-time blocking and automated remediation across supported integrations alongside runtime AI security controls.
3. Prompt Security (SentinelOne)
Primary Focus
SentinelOne announced its acquisition of Prompt Security in August 2025, integrating its capabilities into the Singularity Platform. The solution focuses on shadow AI discovery, AI application security, and runtime protection for employee and agentic AI workflows.
Key Features
- Shadow AI discovery across supported AI tools and services
- Risk assessment of 15,000+ MCP servers
- MCP Gateway for inspecting and enforcing policies on agent interactions with MCP servers
- Employee and code assistant protection
- Integration with SentinelOne's endpoint security platform
- Browser extension for AI usage monitoring
Coverage Considerations
Prompt Security provides AI usage discovery, runtime policy enforcement, browser and developer-tool monitoring, and MCP gateway controls within SentinelOne's broader security platform. Its capabilities address employee AI use, AI applications, and supported agentic workflows.
Nightfall Differentiation
Nightfall delivers a purpose-built unified AI data security platform that consolidates SaaS, endpoint, email, browser, and AI agent coverage through one control plane. Nightfall's rapid deployment through existing infrastructure enables protection within minutes for SaaS and same-day for endpoints, while AI-assisted investigation capabilities help security teams focus on genuine risks. Nightfall also provides inline blocking and automated remediation across supported integrations to control sensitive data movement in real time.
4. Cyberhaven
Primary Focus
Cyberhaven provides data lineage tracking and insider risk management, focusing on understanding how data moves from creation through user and agent interactions. The platform combines this lineage foundation with AI-agent discovery, MCP monitoring, and runtime security controls.
Key Features
- Data lineage tracking from file creation through transformations and movement
- AI-agent discovery, MCP monitoring, and runtime data controls across supported endpoint, SaaS, and developer workflows
- Behavioral context for insider risk analytics
- Endpoint agent for data tracking
- SaaS application coverage
- User behavior analysis for high-value IP protection
Coverage Considerations
Cyberhaven combines data lineage with AI-agent discovery, MCP monitoring, and runtime data controls across supported endpoint, SaaS, and developer workflows. Its approach connects sensitive-data context with agent activity, prompt and response controls, and policy-based enforcement.
Nightfall Differentiation
Nightfall's unified platform approach consolidates SaaS, endpoint, email, browser, and AI agent security with coordinated policy enforcement across supported integrations. Nightfall's AI-native detection achieves 95% precision on customer data during limited proofs of value, helping reduce the false-positive burden that can overwhelm security teams. Nightfall also enables same-day deployment through existing infrastructure, with AI-native detection and real-time blocking across supported data movement workflows.
5. Microsoft Purview
Primary Focus
Microsoft Purview provides native DLP capabilities within the Microsoft 365 ecosystem, offering baseline protection for organizations standardized on Microsoft applications, with extensions to supported non-Microsoft services and AI security capabilities.
Key Features
- Native integration with Microsoft 365 applications
- Sensitivity labels, pattern-based detection, and machine-learning-based trainable classifiers
- Email DLP for Exchange Online
- SharePoint and OneDrive protection
- Endpoint controls and supported non-Microsoft SaaS integrations
- Preview protections for AI governance use cases including agent tool interactions
- Compliance management features
Coverage Considerations
Purview extends beyond Microsoft 365 through endpoint controls, supported non-Microsoft SaaS integrations, and selected AI security capabilities, including preview protections for agent tool interactions. Classification capabilities vary by policy and supported workflow.
Nightfall Differentiation
Nightfall provides a unified AI data security platform purpose-built for SaaS, endpoint, email, browser, and AI agent coverage beyond any single ecosystem. Nightfall's AI-native detection delivers 95% precision on customer data during limited proofs of value, helping reduce false positives. Nightfall also enables 10-minute setup for SaaS integrations and same-day endpoint deployment, while real-time blocking and automated remediation help control sensitive data movement across supported integrations.
6. Varonis
Primary Focus
Varonis provides data governance and permissions management with particular strength in hybrid and on-premises environments. The platform combines data governance with Varonis Atlas, which provides AI-agent security and real-time enforcement capabilities.
Key Features
- Data governance and access control
- Permissions management across file systems
- Varonis Atlas for AI-agent security, MCP-related controls, and real-time policy enforcement across supported AI workflows
- Hybrid and on-premises environment support
- Cloud data security capabilities
- User behavior analytics
Coverage Considerations
Varonis combines data governance and permissions management with Varonis Atlas, which provides AI-agent discovery, runtime guardrails, MCP-related controls, and real-time policy enforcement across supported AI workflows.
Nightfall Differentiation
Nightfall delivers a unified platform that consolidates SaaS, endpoint, email, browser, and AI agent security with consistent policy management across supported integrations. Nightfall's 95% detection precision on customer data during limited proofs of value helps reduce false-positive alerts that burden security teams. Nightfall also enables same-day deployment through existing infrastructure and provides inline blocking, coaching, and automated remediation to help prevent sensitive data exposure across supported workflows.
7. Forcepoint
Primary Focus
Forcepoint offers traditional enterprise DLP capabilities with established market presence across large organizations. The platform has extended to supported AI applications and agent workflows through AI Security and MCP Gateway enforcement.
Key Features
- Network, endpoint, and email DLP
- AI Security capabilities covering sanctioned AI applications, Shadow AI, and an AI Agent Gateway
- MCP Gateway with DLP inspection and policy enforcement for tool requests and responses
- Policy management and enforcement
- Incident management workflows
- Regulatory compliance support
- Enterprise-scale deployment options
Coverage Considerations
Forcepoint has extended its traditional DLP capabilities to supported AI applications and agent workflows through AI Security and MCP Gateway enforcement. Its AI Security capabilities include agent registration, gateway connectors, access policies, and data security controls for supported MCP tool interactions.
Nightfall Differentiation
Nightfall provides a unified AI data security platform purpose-built for modern data movement patterns, with same-day deployment through existing infrastructure. Nightfall's AI-native detection achieves 95% precision on customer data during limited proofs of value, helping reduce the false-positive burden. Nightfall also delivers real-time blocking, coaching, and automated remediation across supported SaaS, endpoint, browser, and AI-agent workflows, enabling security teams to enforce policies on sensitive data movement in real time.
Why Nightfall AI Stands Out for AI Data Security
Unified Platform vs. Point Solutions
Lakera's capabilities now sit within Check Point's broader AI security portfolio, which includes workforce AI usage controls, agent discovery, risk assessment, and runtime guardrails for supported AI applications and MCP workflows. Nightfall AI provides a unified platform that controls data movement across SaaS applications, endpoints, email, browsers, and AI agents through supported integrations. This unified approach helps reduce policy fragmentation when organizations manage multiple data security tools.
AI Agent and MCP Security
Check Point provides workforce AI controls and runtime guardrails for supported AI applications and agents, alongside discovery and risk assessment. Nightfall provides MCP security covering local stdio, remote HTTP/SSE, and MCP gateway enforcement across supported workflows. The platform includes shadow-MCP detection, per-server risk scoring, and prompt injection protection across supported agent workflows. This coverage addresses the reality that AI agents now access data through IDE hooks, desktop applications, and enterprise SaaS.
Real-Time Control, Not Just Detection
Detection without enforcement creates visibility into problems without the ability to stop them. Nightfall provides inline blocking, coaching workflows, and automated remediation that help stop policy-violating data movement before sensitive information leaves supported channels. Security teams can enforce policies while end-user remediation options maintain productivity.
AI-Native Detection Precision
Nightfall's detection engine achieves 95% precision on customer data during limited proofs of value using ML detectors and LLM classifiers. This precision helps reduce false-positive alerts and the investigation burden associated with traditional DLP deployments. The platform includes customer-trainable detection with auto-retraining capabilities.
Deployment Speed and Operational Efficiency
Nightfall deploys within minutes for SaaS integrations and same-day for endpoints via MDM. Pre-trained detectors work immediately without extensive tuning. Nightfall's consolidated SaaS, endpoint, and AI security coverage helps reduce total cost of ownership compared to separate legacy DLP solutions, with AI-assisted detection, investigation, and response helping reduce manual investigation effort.
Claude Enterprise Integration
Nightfall integrates with Claude's Compliance API to inspect sensitive content in Claude Enterprise conversations and monitor activity logs across Claude Platform. Separate inference hooks provide real-time inspection and enforcement, extending Nightfall's unified data security controls across supported Claude workflows.
For security teams evaluating alternatives following Lakera's acquisition, Nightfall AI's combination of unified coverage, AI agent security, real-time control, and proven enterprise scale delivers AI data security across supported integrations. Request a demo to see how Nightfall governs sensitive data across supported data movement surfaces.
Frequently Asked Questions
What core problems do AI data security platforms solve for enterprise security teams?
Enterprise security teams require protection covering employee use of third-party AI tools like ChatGPT and Claude, data loss prevention across SaaS applications, endpoint security, and governance for AI agents using MCP. Purpose-built AI data security platforms address these requirements across supported SaaS, endpoints, email, browsers, and AI agent workflows. Check Point's AI security portfolio includes workforce AI controls, agent discovery, and runtime guardrails for AI applications and agents.
How does Nightfall AI differ from Lakera's approach to AI security?
Lakera provides runtime guardrails for AI applications and agents, while Check Point's broader AI security portfolio also includes workforce AI governance, agent discovery, and risk assessment. Nightfall AI controls data movement across SaaS, endpoints, email, browsers, and AI agents in a unified platform. Nightfall provides real-time visibility and control over sensitive data movement by humans and AI agents across supported SaaS, endpoint, browser, email, and agent workflows. The platforms address overlapping AI security requirements through different architectures and coverage models.
Can organizations use multiple AI security tools together?
Yes, organizations often combine specialized tools for different security domains. For example, HiddenLayer addresses model-level security for custom ML deployments, while Nightfall AI governs data movement across enterprise workflows. Nightfall's unified platform provides coordinated controls across supported SaaS, endpoint, browser, and AI agent and MCP workflows.
What should organizations consider when evaluating alternatives after the Check Point acquisition?
Following acquisitions, product roadmaps and packaging often change as capabilities integrate into the parent company's portfolio. Enterprise AI security requirements can extend beyond runtime application protection to include workforce AI governance, SaaS DLP, endpoint security, and MCP agent coverage. Nightfall addresses these requirements through a unified data security platform with real-time controls across supported integrations.
How do detection precision and deployment speed impact AI data security effectiveness?
Detection precision directly impacts operational effectiveness. Low-precision systems generate high volumes of false-positive alerts that overwhelm security teams and lead to alert fatigue. Nightfall's AI-native detection achieves 95% precision on customer data during limited proofs of value, helping reduce false positives. Deployment timelines vary across solutions. Nightfall AI offers 10-minute setup for SaaS integrations and same-day endpoint deployment via MDM, while implementation timelines depend on deployment scope, infrastructure, and policy requirements. Rapid deployment helps organizations establish data security controls sooner and reduce the time between implementation and enforcement.
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