Bridge the Gap Between Policy and Reality

Policies often drift from actual system behavior. Our AI Agent automates the mapping of high-level mandates to low-level controls, detecting weaknesses before audits occur.

The AI Agent Workflow

How the Agent Closes the Loop

Click on the stages below to explore how the agent parses, inspects, and detects.

1. Parse & Interpret
Reads human-readable policies and SOPs.
Input: PDF/Docx
2. Inspect Reality
Scans live system logs, configurations, and workflows.
Input: JSON/Logs
3. Detect Gaps
Identifies where controls fail to satisfy policy intent.
Output: Gap Report

Live Gap Detection Simulation

Select a policy scenario below to simulate the AI Agent's analysis of system drift.

Mocking diverse policy domains.

DOC Policy Document

LOG System Configuration / Logs

Analysis Results

Waiting for Analysis

Compliance Confidence Score

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Detected Gaps & Recommendations

Select a scenario and run the agent to see findings.

Why Use an AI Agent?

Transform reactive auditing into proactive control management.

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Early Identification

Find control weaknesses immediately after configuration changes, not months later during an annual audit.

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Contextual Mapping

The agent understands the *intent* of unstructured policy text and maps it to structured technical logs.

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Continuous Assurance

Prevents policy drift by constantly monitoring the gap between written rules and system reality.