AI-Aware Data Loss Prevention

Why traditional DLP cannot see AI prompts

Legacy DLP was designed around files and network egress: email attachments, uploads, USB devices, and unencrypted protocols. An AI prompt breaks every one of those assumptions.

• The data is pasted, not attached — there is no file object to inspect.
• The channel is TLS-encrypted to a sanctioned-looking domain, so network inspection sees only metadata.
• The sensitive content is often a fragment — a customer record inside a paragraph of context — rather than a whole document.
• The exposure is irreversible: once submitted to a public model that may train on input, it cannot be recalled.

What gets detected

Detection combines pattern matching, contextual validation, and classification, so a sixteen-digit number in an invoice is treated differently from one in a payment field:

• Personal data — names, national IDs, Emirates ID, passport and contact details.
• Health data (PHI) — diagnoses, patient identifiers, and clinical notes.
• Payment data (PCI) — card numbers, validated by checksum and context.
• Secrets — API keys, OAuth tokens, private keys, and connection strings.
• Source code and intellectual property — proprietary code and internal documents.

Redaction keeps people productive

A block teaches users to route around the control. Redaction does not: the employee still gets their answer, the sensitive span is simply never transmitted. In practice this is what makes an AI policy survive contact with the business — the control is invisible when it does not need to intervene, and minimal when it does.