PromptGuard: AI-Native Data Loss Prevention for LLM Interactions

Large Language Models (LLMs) such as ChatGPT, Copilot, and Gemini are now widely used by professionals to draft documents, analyse data, write code, and support decision-making. While these tools significantly improve productivity, they also introduce new cybersecurity risks because users often share sensitive or regulated information within prompts or uploaded files without fully understanding the implications. Confidential contracts, financial data, proprietary code, internal reports, and personal information are increasingly exposed through AI interactions, and several organisations have already restricted AI usage after accidental data disclosures. These incidents highlight how even experienced professionals can unintentionally compromise sensitive information when using conversational AI systems.

Traditional Data Loss Prevention (DLP) solutions were designed to monitor email, file transfers, and network activity, but they are not equipped to protect data within real-time AI conversations. PromptGuard addresses this gap by providing an AI-native runtime protection layer that analyses prompts and uploaded content before submission to LLMs. It detects sensitive or regulated information and applies policy-based controls such as warnings, redaction, blocking, or secure routing, ensuring protection at the point of interaction without disrupting workflows. By enabling real-time preventative safeguards, PromptGuard supports secure and responsible AI adoption across regulated sectors including finance, healthcare, legal services, government, and technology.