Protect sensitive enterprise data from exposure through AI prompts, responses, and workflows.
Generative AI creates new paths for sensitive information to move into prompts, model responses, and connected agent workflows. PointGuard AI applies inline data protection so enterprises can use AI without losing control of confidential or regulated data.
Employees, applications, and autonomous agents can send sensitive information to AI systems intentionally or accidentally, including PII, credentials, proprietary content, and regulated data. Because AI traffic moves through prompts, responses, attached content, APIs, and tool interactions, traditional DLP controls may not consistently inspect the full transaction. Enterprises need AI-native controls that understand these runtime exchanges, identify protected information in context, and enforce policy before sensitive data is exposed to a model, user, external service, or downstream tool.
Prevent AI data leaks by inspecting sensitive content inline and enforcing policy before information crosses an approved boundary.
1. Inspect AI traffic. Monitor prompts and responses inline so sensitive data can be detected before it reaches a model or is returned to a user.
2. Detect protected information. Identify PII, secrets, credentials, and other protected enterprise data using AI-native DLP inspection.
3. Enforce data policies. Block, mask, or redact sensitive information in real time according to organizational security and acceptable-use policies.
4. Extend protection to agent workflows. Apply the same DLP controls to agent prompts, responses, tool outputs, and MCP-connected data flows.
With consistent runtime inspection and enforcement, enterprises can expand AI adoption while keeping sensitive data inside approved trust boundaries.
PointGuard AI provides a complete solution for this use case using these capabilities:
• AI Intelligent Guardrails: inspects prompts and responses for sensitive data and can block, mask, or redact protected information in real time.
• MCP Security Gateway: extends AI-native DLP across agent inputs, outputs, tool interactions, and MCP-connected workflows.