Regex Rules, Endless Alerts
Pattern matches fire on every test card number and invoice. The flood of false positives causes alert fatigue, so teams tune rules down until real leaks slip through.
Replace Legacy DLP
Replace Legacy DLP with AI-Native Unified DLP
Netra covers endpoint, email, network, SaaS, and AI in one platform with one policy model, so data can’t slip between siloed tools. Its Turing AI agent analyzes event logs and triages alerts automatically, cutting false positives by 95%.
Get a DemoMAP › DATA FLOW
Data Flow
Outbound DataFile TypeReceived Data
Data Exfiltration EventsS4S3S2S1
AI Chatbot
412
AI Coding Assistant
268
Cloud Storage
231
Email
187
Instant Messaging
142
Computer Peripherals
64
Embedded AI
58
Product views on this page use illustrative data.
The Challenge
Why Legacy DLP Falls Behind
Keyword rules and network chokepoints don’t match how data moves now.
Siloed Tools, Partial Coverage
Endpoint DLP, email DLP, CASB, and network DLP each see one slice, with their own policies and consoles. Data that moves between them, or through a channel none of them watches, slips through the gaps.
Built Before AI Tools Existed
Legacy DLP was designed for files, email, and USB. It can’t read a prompt, follow an agent’s tool calls, or tell a personal AI account from the corporate one, so AI traffic passes as ordinary web traffic.
How It Works
Classify, Trace, Control, Detect and Response
One endpoint agent and one console, from first scan to final evidence.
01Classify
Classify Data by Meaning, Not Keywords
Hundreds of built-in classifiers, in categories such as Financial Data, Human Resource, and Research and Development, work with 580 built-in identifiers and your Microsoft Information Protection (MIP) labels to grade content S1 to S4. Test new classifiers in the Simulator against a file or text. Tests write nothing to audit logs.
POLICY › CONTENT
ClassifierIdentifierSensitive SourceMIP LabelsSimulator
ClassifierCategoryLevelUsage
Payment card dataFinancial DataS41,284
Employee payrollHuman ResourceS4312
Source codeResearch and DevelopmentS32,941
Product roadmapProduct ManagementS3187
Campaign plansMarketing and OperationS296
02Trace
Trace Data Lineage From Sources to Destinations
Content-fingerprint lineage follows each piece of sensitive data from its source, such as a Git repository, through downloads, compression, and renames, to where it finally goes. Data Flow shows what leaves by channel and what arrives from email, cloud storage, FTP/SMB, and code repositories, and Map › Search lists the sensitive files at rest on each endpoint.
MAP › DATA FLOW
Outbound DataFile TypeReceived Data
SourceFilesS4 Files
Email1,20684
Cloud storage94861
Code repositories61137
Office communication40212
FTP/SMB1339
Content LineageSame fingerprint
- Origin Source Git
- Download cloud_dsp_auction_logs_v2.csvfromGit
- Compression cloud_dsp_auction_logs_v2.csvtoOb3.zipwith7-Zip
- Rename Ob3.ziptoPartner-1.zip
- Upload Partner-1.ziptoGoogle Drive
03Control
Control 170+ Channels, AI Included
Netra ships 170+ built-in channels in 17 categories. AI Chatbot, AI Coding Assistant, and Embedded AI sit next to email, USB, cloud storage, instant messaging, and code repositories, and you can add custom channels. Write channel, content, email, and MIP label policies that block or allow, with a pop-up that tells the user why. Scoped watermarking and screen recording cover data people still need to see.
POLICY › CONTROL
ChannelContentEmailMIP Labels
PriorityPolicy NameChannelAction
1Block S4 data to AI chatbotsAI ChatbotBlock
2Pop-up on source code to coding assistantsAI Coding AssistantAllow + Pop-up
3Block S3+ files to USB drivesComputer PeripheralsBlock
4Pop-up on S3 files to cloud storageCloud StorageAllow + Pop-up
5Allow S1 content in embedded AIEmbedded AIAllow
04Detect and Response
Turing AI Triages Every Alert
Netra’s Turing AI agent analyzes event logs and triages alerts automatically. Turing reads the data semantically, pulls out the key findings, and reasons about the user’s intent. It rates each alert High, Medium, or Low risk, so true incidents stand out and noise drops by 95%, and it recommends the remediation for each one.
TURING AI · ALERT TRIAGE256 events analyzed
4High risk
8Medium risk
244Low risk
FileUser · ChannelRisk Level
Partner-1.zipJ. LinGoogle DriveHigh
brand-guide.pdfS. PatelCodex CLIMedium
q3-feedback.txtM. ChenChatGPT WebLow
Partner-1.zip · J. LinS4 · High risk
Key Findings - J. Lin uploaded Partner-1.zip to a personal Google Drive. It holds cloud_dsp_auction_logs_v2.csv, downloaded from Git.
- The archive was compressed and renamed minutes before upload, which suggests an attempt to hide its contents.
Customer IDs (412)Bid prices (2,180)Internal hostnames (3)
Recommendations - Remove the file from personal storage and revoke external storage access.
- Review J. Lin’s other transfers this week.
Side by Side
Legacy DLP vs Netra DLP
What changes when context replaces keyword rules.
| Area | Typical legacy DLP | Netra DLP |
|---|---|---|
| Detection | Regex and keywords | Context-aware and intent-driven |
| Coverage | Separate tools for endpoint, email, CASB, and network | One platform for endpoint, email, network, SaaS, and AI, across 170+ built-in channels |
| AI tools | Treated as generic web traffic | AI Chatbot, AI Coding Assistant, and Embedded AI as first-class channels |
| Alerting | Analysts work alerts manually, and most are false positives | Turing AI agent triages each alert by risk level, cutting false positives by 95% |
| Investigation | Time-consuming manual log analysis | Evidence with data lineage, plus Agent Trace for AI activity |
Next Steps
One Platform Beyond DLP
The same platform covers AI security and Token Governance.
Stop AI Data Leakage
Detect and block sensitive data in prompts, uploads, and responses.
Learn moreGovern AI Spend
Attribute AI token spend to users, departments, and models, then cap it.
Learn moreSecure AI Coding
Control coding agents like Claude Code, Cursor, and Codex on developer machines.
Learn moreDiscover Shadow AI
Find every AI app, agent, and account in use before you write policy.
Learn moreFAQ
Common Questions
How does Netra reduce false positives compared with legacy DLP?
Netra’s Turing AI agent analyzes event logs and triages alerts automatically, rating each alert High, Medium, or Low risk and cutting false positives by 95%. Each event is judged in context, not on a pattern match alone: UEBA templates compare activity with the user’s own baseline. Each event carries the user, data lineage, and, for AI activity, Agent Trace. The Policy Simulator shows which policies would fire before you roll them out.
How do we migrate from our existing DLP?
Phase it in. Start by using Netra to close the coverage gap for urgent AI adoption, then replace your existing DLP tools one at a time with Netra DLP. Within each phase, begin by monitoring channels and reviewing the Audit log, preview new policies in the Policy Simulator, then turn on blocking channel by channel.
Does Netra treat AI tools as DLP channels?
Yes. AI Chatbot, AI Coding Assistant, and Embedded AI are channel categories next to email, USB, cloud storage, and instant messaging, among 170+ built-in channels in 17 categories. The same channel, content, email, and MIP label policies apply to them.
Are watermarking and screen recording always on?
No. Both are scoped, policy-driven controls. Screen recording policies apply by scope, endpoint type, device labels, or file path. Watermarking (desktop visible, desktop invisible, print, and anti-photo in beta) applies only where your policy sets it.
See Your Data Flows With Context
Run a proof of value on your own endpoints and see your sensitive data, channels, and alerts the way Netra sees them.
Get a Demo