Solutions / DLP for GenAI
Prevent sensitive data leaks into AI tools
Small language models that understand context, so you catch more with far less noise
Regex only sees patterns. Harmonic assesses the whole prompt or file, so it detects unstructured sensitive data like deal terms, source code and customer details, with 96% greater accuracy than legacy DLP.
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Why Harmonic for DLP
DLP that understands context instead of matching patterns
Harmonic acts as an intelligent layer between your employees and the AI tools they rely on. Instead of matching patterns, our small language models assess the whole prompt or file in context. That means they detect unstructured sensitive data, such as deal terms, source code and customer details written in plain language, that regex cannot see, while cutting the false positives that bury security teams in alerts.
01Accuracy
Catch more sensitive data with far less noise
Stop wasting time chasing false positives. Purpose-built small language models read the whole prompt or file and interpret the nuance of natural language, separating routine queries from prompts carrying sales pipeline data, M&A documents or source code, even when nothing in them matches a pattern.
The result is 96% greater accuracy than regex, which struggles with unstructured text, and every analysis completes in under 200 milliseconds so the experience stays seamless.
02Training risk
Stop your data from becoming training data
Automatically categorize AI tools by their terms of service, and instantly detect when a tool trains on your data or hosts it in a region you would not choose.
Granular controls let you allow a tool for general work while blocking submission of PII or IP, so that material never reaches a public model’s training set.
03Personal accounts
Keep corporate data out of personal AI accounts
Employees using free, personal versions of ChatGPT or Claude are a flight risk: that context leaves with them.
Harmonic lets you enforce enterprise accounts where data is ring-fenced, or restrict uploading corporate context into personal ones.
Top resources
Resources for security teams doing AI DLP
How context-aware classification differs from pattern matching, and what it catches that regex cannot.
Frequently asked questions
Quick answers about AI DLP
Short, direct answers to what security and IT teams ask before bringing Harmonic in.
Can traditional DLP detect sensitive data in AI prompts?
Traditional regex-based DLP struggles with conversational AI, because prompts are unstructured, contextual, and often contain legitimate business information that patterns cannot distinguish from sensitive data. That leads to false positives and monitor-only deployments.
Do Netskope and Zscaler offer AI-specific controls?
Some SASE vendors offer limited AI controls for a small number of high-profile domains like ChatGPT or Copilot. Those controls require per-domain integrations and do not cover the full spectrum of AI tools, embedded AI features, or agentic workflows.
What is Harmonic Security's technical differentiator?
Harmonic uses purpose-built small language models that understand user intent and sensitive data in milliseconds. This low-latency analysis lets you understand AI usage and enforce inline controls without slowing work down.
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Build your AI guardrails for sensitive data
Gain the visibility and control you need to guide AI use with confidence. Most teams see first insight in about 30 minutes.
What you'll see with Harmonic Security
- Your full AI usage footprint: every surface, every team, every exposure.
- Inline guardrails that coach, warn, or block, firing in under 200ms.
- See and control what AI agents are actually doing.
- Coverage of browser, endpoint and MCP.
- Deployment in minutes via Intune, JAMF, or Kandji.
