Consumer Data Exposure in AI Prompts

Marketing, consumer insights, and R&D teams paste survey data, loyalty records, and product formulations into copilots and chatbots. Legacy DLP does not inspect these interactions, and generic detectors do not recognize formulas or ingredient specifications. PointGuard AI applies AI-native data protection with custom detectors for consumer data and proprietary formulas across every AI interaction.

Consumer and product data moves through AI tools without inspection.

• Insights teams share consumer PII with AI analysis tools.
• R&D teams paste formulations into public assistants.
• Agencies and partners use their own AI tools on shared data.
• Privacy rules vary across markets.

AI Data Protection and Shadow AI Control enforce data policies across sanctioned and unsanctioned AI tools.

1. Define protected data. Use built-in PII detectors and create custom types for formulas, ingredient specifications, and project code names.

2. Inspect every interaction. Scan prompts, responses, and tool calls at sub-100 ms latency.

3. Redact, block, or redirect. Mask sensitive data when work can continue, block it when it cannot, and steer users to approved tools.

4. Report by team and market. Track detections and feed events into privacy and IP protection programs.

• OWASP Top 10 for LLMs: LLM02 Sensitive Information Disclosure and LLM07 System Prompt Leakage, covering consumer and formula disclosure and exposure of sensitive prompt context.
• OWASP Top 10 for Agentic Applications: ASI02 Tool Misuse and Exploitation, addressing agents that move sensitive data through connected tools.
• NIST AI RMF: MAP identifies sensitive data; MEASURE evaluates exposure; MANAGE enforces policy; GOVERN sets acceptable use.