AI
data loss prevention
PromptGlass AI DLP inspects every prompt, paste and file upload before it reaches an AI model. Built-in detectors find personal data, health data, payment cards, credentials and source code. Policies then allow, coach, redact or block, in milliseconds and without breaking the AI tool.
Outcomes
- ✓Sensitive data stopped before it reaches a model
- ✓Fewer blocks thanks to redaction
- ✓SIEM-ready events for your SOC
What you get
Inside PromptGlass ai data loss prevention
Purpose-built detectors
PII, PHI, PCI (with Luhn validation), national IDs, secrets and keys, source code, and financial or M&A terms.
Redact, don’t just block
Sensitive spans are replaced with tokens before the prompt leaves and can be restored in the response, so the work still gets done.
Exact data match
Fingerprint your customer list or employee table and detect real records, not just patterns.
In-the-moment coaching
A short, friendly message explains the risk and suggests the approved tool. Most users change behavior after one nudge.
Rollout
Four steps, no big bang
Start in observe-only mode and tighten controls as you learn what your organization needs.
- 1
Observe
Run detectors in log-only mode to baseline what is being shared.
- 2
Coach
Turn on coaching for the riskiest data classes.
- 3
Redact or block
Enforce redaction for PII and block secrets and regulated data.
- 4
Report
Send events to your SIEM and track the trend down.
AI data loss prevention: FAQ
What is AI DLP?
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AI data loss prevention (AI DLP) inspects prompts, pastes and uploads sent to AI tools and stops sensitive data from leaving, typically by warning, redacting or blocking. It differs from traditional DLP because it understands AI app sessions, conversational context and model APIs.
Will PromptGlass replace our existing DLP?
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Usually it complements it. PromptGlass focuses on AI interactions with AI-specific actions like redaction and model rerouting, and sends events to the same SIEM your DLP uses.
Find out how your company really uses AI.
Start a free 30-day AI usage assessment: a complete shadow AI inventory, the sensitive data leaving, and the AI seats you are paying for but not using.