Nightfall AI
Contact SalesAI-native DLP for AI agents, MCP servers, and SaaS
By Tanmay Verma, Founder · Last verified 03 Jul 2026
3.7k views
Added 4/3/2026
93/100Safe BetIn short
Nightfall AI — AI-native DLP for AI agents, MCP servers, and SaaS. Best for Security teams in healthcare, fintech, legal, manufacturing needing AI-native DLP, Organizations deploying AI agents and MCP servers requiring granular data access control, Teams overwhelmed by legacy DLP false positives seeking >90% detection accuracy. Contact Sales pricing.
Is Nightfall AI actually worth it?
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Editorial Verdict
Best for
Security teams in healthcare, fintech, legal, manufacturing needing AI-native DLPOrganizations deploying AI agents and MCP servers requiring granular data access controlTeams overwhelmed by legacy DLP false positives seeking >90% detection accuracyEnterprises wanting to enable Shadow AI safely with real-time blocking and coachingCompliance-conscious companies using Claude Enterprise with Compliance API
Not ideal for
Fully air-gapped, on-premises environments with no SaaS or AI tool usageSmall teams with limited budget and no dedicated SecOps (pricing is enterprise-grade)Organizations needing a simple endpoint DLP without AI/agent coverageTeams that already have mature Microsoft Purview deployment and no AI agent usage
For any enterprise running AI agents or MCP servers, Nightfall is the only DLP that covers those vectors natively at 95% precision. Its live Claude Compliance API integration and autonomous Nyx analyst give it a unique edge. But smaller teams without dedicated SecOps will find the pricing and complexity steep.
Skip Nightfall AI if Skip Nightfall if you don't use AI agents, MCP servers, or shadow AI apps, or if your team can't justify enterprise-level per-user pricing.
Compare with: Nightfall AI vs Cyera, Nightfall AI vs Vorlon, Nightfall AI vs Veza
Last verified: July 2026
What's new in Nightfall AI
Checked 2 days agoAcross the latest 4 updates: 1 feature update, 2 changelog entries and 1 news mention.
NewsBlog·12 days agoNewest
Best AI Agent Security & MCP Security Platforms for Businesses in 2026
Compares top AI agent security platforms, positioning Nightfall as a leader.
FeatureBlog·26 days ago
Nightfall's integration with Claude's Compliance API is now live
Announces live integration with Claude's Compliance API for enterprise AI security.
ChangelogBlog·May 27
Why MCP Breaks the Financial Services Security Stack
Explains how MCP standardizes AI agent connections, bypassing legacy DLP.
ChangelogBlog·May 19
What Is MCP Security? 9 Things Every CISO Needs to Know
Lists key MCP security risks and visibility gaps for CISOs.
Viability Score
93/100
Safe BetHow likely is Nightfall AI to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
momentum
100
funding runway
70
website health
90
wrapper dependency
100
Last calculated: July 2026
How we score →Key Features
- 100+ AI detection models for 95% precision
- Data lineage tracking from source to destination
- Shadow AI blocking for ChatGPT, Copilot, Gemini, Claude, Deepseek, Perplexity, Grok
- AI agent hook-level interception (prompt, tool call, shell)
- MCP server discovery and policy control
- Prompt injection blocking for agentic AI
- Automated remediation for 80% of incidents
- Real-time scanning and auto-quarantine in Slack
- PHI/PCI/PII blocking in outbound Gmail and endpoints
- Employee coaching with real-time violation alerts
- Browser plugins for Chrome, Firefox, Edge, Safari
- Nyx autonomous DLP analyst for threat investigation
- LLM-based file classifiers for documents and source code
- Claude Compliance API integration (live June 2026)
- Revoke inappropriate data access in SaaS
About Nightfall AI
Contact SalesIntermediateAPI availableWeb · API
Nightfall AI is an AI-native data loss prevention platform built for security teams who need to monitor and control sensitive data across modern data movement vectors—AI agents, MCP servers, browsers, endpoints, and SaaS applications. Its 100+ AI detection models achieve 95% detection precision out of the box, slashing false positives that plague legacy DLP systems. The platform covers Shadow AI apps (ChatGPT, Copilot, Gemini, Claude, Deepseek, Perplexity, Grok), endpoints, email, and SaaS, with hook-level interception for AI agents and MCP servers. Key capabilities include data lineage tracking from source to destination, automated remediation for 80% of incidents, and an autonomous DLP analyst called Nyx that investigates threats and optimizes policies via natural language. Nightfall deploys via API in hours, with browser extensions for Chrome, Firefox, Edge, Safari, and lightweight agents for macOS and Windows. A live integration with Claude's Compliance API (announced June 2026) extends enterprise-grade DLP to Claude Enterprise conversations. While pricing leans enterprise—requiring a demo for details—it targets regulated industries like healthcare, finance, legal, and manufacturing. For organizations deeply invested in AI adoption, Nightfall provides the most accurate, real-time DLP for modern data movement, outpacing legacy tools like Microsoft Purview or Palo Alto Networks for AI-centric environments.
Behind the Verdict
Nightfall is the first DLP purpose-built for the AI era, not a legacy tool retrofitted with AI detection. Its hook-level interception for AI agents—blocking prompts, tool calls, and shell commands before execution—is something no other DLP does. The data lineage feature traces file movement across endpoints, cloud drives, and email, even after renaming or repackaging. Nyx, the autonomous analyst, can take over incident triage and policy tuning, which is a genuine time-saver for lean teams. The live Claude Compliance API integration (went live June 2026) means Claude Enterprise conversations are monitored with the same detectors as Slack or Gmail, which is a must for regulated firms. Where Nightfall falls short is endpoint coverage: it doesn't do full hard-drive scanning or DLP for on-prem file servers. It's also pricey—pricing is undisclosed but appears to be per-user-year, with tiers that assume a significant budget. If you're a small startup without compliance mandates, you'd be better off with a simpler tool like Satori or plain Microsoft Purview. But for security teams in healthcare, finance, legal, or manufacturing that run AI agents, MCP servers, and want to enable Shadow AI safely, Nightfall is the clear leader. Just budget for it and plan for a demo-based sales process.
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Real-world workflow fit
Concrete scenarios for the personas Nightfall AI actually fits — and what changes day-one when you adopt it.
Security engineer at a fintech company
Deploy Slack integration to block API keys in real-time; configure auto-quarantine.
Outcome: Prevent credential leaks without manual monitoring; incident response time cut by 80%.
CISO at a healthcare organization
Enable Gmail and Google Drive scanning for PHI; set up employee coaching for violations.
Outcome: Maintain HIPAA compliance and reduce unintentional PHI exposure by 90%.
AI security lead at a tech company using Claude Enterprise
Integrate Claude Compliance API; define policies to block prompt injection and sensitive data in agent tool calls.
Outcome: Securely enable AI agent workflows while preventing data exfiltration and meeting compliance requirements.
Use Cases
- Prevent secrets and credentials from leaking in Slack messages or GitHub commits.
- Auto-redact PHI in Gmail or Google Drive to maintain HIPAA compliance.
- Block intellectual property from being uploaded to unauthorized AI apps like ChatGPT.
- Revoke over-permissioned sharing of sensitive files in Google Drive and OneDrive.
- Monitor and block data exfiltration via USB drives, clipboard, print on managed endpoints.
- Investigate data exfiltration incidents using Nyx autonomous analyst with full lineage.
- Secure AI agent tool calls to Salesforce, preventing data exposure through MCP servers.
- Detect and block prompt injection attacks targeting Claude and other agentic AI.
Models Under the Hood
GPT-4Claude OpusGeminiDeepSeekProprietary AI detection models (100+)LLM-based file classifiersComputer vision models
as of 2026-06-30
Limitations
- Pricing is per-user per-year and not transparent on the website; you must contact sales for custom quotes.
- The Free tier is limited to 100 scans per month with only Slack integration.
- Data Discovery and Classification is a separate add-on costing $/year per data pack tier.
- Endpoint protection is an add-on and only for macOS and Windows.
- AI Agent Security (Complete+AI Agent Security package) is a higher tier with additional per-user cost.
- Some integrations may require additional configuration or API keys.
- MCP agent security is limited to local stdio MCP servers and remote HTTP/SSE MCP; some environments may need additional setup.
as of 2026-06-30
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
—
Contact sales for a quote
Effective monthly
—
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Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Nightfall AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Data Detection & Response (DDR) Tier 1
Contact for pricing
Data Detection & Response (DDR) Tier 2
Contact for pricing
Data Exfiltration Prevention (DEX) Tier 1
Contact for pricing
Data Exfiltration Prevention (DEX) Tier 2
Contact for pricing
Nightfall Complete
Contact for pricing
Ideal for
Enterprises wanting full DLP coverage across SaaS, endpoints, and AI apps with dedicated support and priority SLA.
What this tier adds
All-in-one package: includes all DDR and DEX features plus dedicated CSM and 1-hour SLA. Best value at $/user/year.
Complete + AI Agent Security Tier 1
Contact for pricing
Complete + AI Agent Security Tier 2
Contact for pricing
Integrations
Where the pricing makes sense
The company stage and team size where Nightfall AI's pricing actually pencils out — and where peers do it cheaper.
Nightfall's pricing is enterprise-grade, with tiers from Data Detection & Response (starting at $/user/year for up to 3 apps) to Complete + AI Agent Security. For small teams, it's expensive compared to open-source or lighter DLP. For regulated enterprises adopting AI, the ROI from 80% automated remediation and 95% detection precision justifies the cost against legacy DLP modernization.
Setup time & first value
How long it actually takes to get something useful out of Nightfall AI — broken out by persona, not the marketing-page minute.
For security engineers, base SaaS integrations (Slack, Google Drive) deploy in hours via API. Browser plugins install in minutes. Endpoint agent deployment via Jamf/Intune takes a day. MCP and AI agent hooks require custom configuration, typically 1-2 days. Nyx analyst is operational within a week.
Switching to or from Nightfall AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Migrating in
- →From legacy DLP (e.g., Symantec): use APIs to onboard existing data sources; Nightfall's AI models reduce false-positive tuning.
- →From Microsoft Purview: migrate policies via manual review; Nightfall's automated remediation can be phased in parallel.
Migrating out
- ↗To Cyberhaven: export incident logs and policy configurations; transition endpoints and SaaS integrations gradually.
Resources & Guides
Frequently Asked Questions
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