Solution / AI DLP
Stop sensitive data before it reaches an AI model.
Classic DLP watches files and email, but today sensitive data leaves through prompts: customer records pasted into ChatGPT, credentials in a Copilot context window, internal documents fed to a RAG pipeline. Patronus inspects every prompt and response on the device, detects PII, secrets and policy-relevant content in milliseconds, and redacts or blocks it before it leaves your perimeter, across every AI tool, including streaming protocols like WebSockets and SSE.
Where classic DLP goes blind
Prompts aren't files
DLP built for attachments and uploads doesn't parse conversational AI traffic or streamed responses.
Encryption hides the payload
AI API calls are TLS-encrypted. Network DLP sees bytes, not the customer data inside the prompt.
Every tool is different
ChatGPT, Copilot, Gemini, local models, agents, per-tool DLP integrations can't keep up with how fast AI usage spreads.
How Patronus prevents AI data loss
On-device inspection
Prompts and responses are analyzed locally in the network path, before encryption, before the data leaves the machine.
PII & secrets detection
Purpose-built local models detect personal data, credentials and sensitive content in real time, no cloud scanning involved.
Redact, block or flag
Policies decide per data type and app: automatic redaction, hard block, or audit-logged pass-through with alerting.
Protection without the trade-off
0 bytes
of prompt data sent to any scanning cloud
ms-level
detection latency, no workflow impact
All protocols
REST, WebSockets, SSE, gRPC covered
FAQ