Solution · Data Protection

Sensitive data is stopped before the model

The Semantic Security Engine™ reads every prompt, file, and response for meaning and intent, then allows, redacts, holds, or blocks it before data reaches the model.

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  • Judged by meaningDetection weighs data, actor, destination, and intent together, not string matches alone.
  • Enforced inlineAllow and record, redact in place, hold for human review, or block, applied before the prompt reaches the model's API.
  • Redaction in placeThe sensitive span comes out and the interaction keeps going.
  • Both directionsPrompts on the way in, model responses on the way out, one pipeline for both.
  • Every surface, one policyThe same policies secure and govern the Secure Enterprise AI Workspace, gateway, API, agents, and Endpoint Security for AI tools you do not own.
  • Detection that compoundsDrawing on the Security Context Graph™, threat and sensitive-data detection grows more accurate as your organization uses AI and connects its data.

Sensitive data is judged by meaning and intent

Data protection is AI Security Runtime™ running on the data path, beneath the workspace. Every prompt, file, and response crosses the same four functions on the way to the model.

READS MEANINGThe Semantic Security Engine judges each interaction in context, and sensitive-data detection improves as decisions accumulate in the Security Context Graph™
REDACTS IN PLACEThe sensitive span is removed inline while work continues
COVERS BOTH WAYSPrompts and responses pass the same judgment across the Secure Enterprise AI Workspace, gateway, API, agents, and Endpoint Security for AI tools you do not own
PROVES EACH DECISIONEvery enforcement decision creates a metadata record of what ran, what was enforced, and why, without duplicating prompt or response bodies

Common questions

What does it catch?

Credentials and access keys, payment data, customer and employee records, regulated content, and the sensitive data you define yourself. Detection is semantic: the engine weighs what the data is, who is sending it, where it is headed, and what the interaction intends, and it grows more accurate as your organization uses AI and connects its data, drawing on the Security Context Graph™.

What happens when a detection fires?

Policy decides the outcome per detection: allow and record, redact in place, hold for human review, or block. Redaction removes the sensitive span and lets the interaction continue, and hold routes ambiguous cases to a reviewer instead of stopping everyone. Deterministic rules stay deterministic: a class you designate always-block is blocked regardless of context; semantic judgment adds context on top, it never overrides a hard rule.

Do you store our prompts?

Analysis happens in the decision path. What is stored and exported is the decision and its context, sealed and metadata-only: surface, detection, policy, action. Raw prompts and data are not retained as evidence. The deliberate exception is hold for human review: a held item is visible to the reviewers you designate while it waits, and once decided, what remains in the trail is the decision, not the content.

The policy behind every decision

Decisions come from policy you control. Detection patterns carry severities, actions, and framework mappings, written once and enforced on every surface the runtime governs.

First Recon AI · Admin Console
Detection patterns in the admin console with severity, action, and framework mappings

Secure every
AI interaction.

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