Behavioral AI Risk Scoring

The evidence layer for AI governance.

PAICE Simulator

I can help you analyze that dataset. Based on the trends you mentioned, I'd recommend using a linear regression model with a confidence interval of 80%.

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How It Works

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Adapt

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For Organizations

AI Capability Baseline

See how your team actually collaborates with AI. Not what they report, what they do. A behavioral assessment that reveals capability gaps invisible to training records and usage dashboards.

Cohort Assessment: 2-week engagement measuring AI collaboration capability across your team
The Confidence Gap: See the difference between what your team believes and what they demonstrate
Governance-Ready: Privacy-first reporting aligned to GDPR, NIST AI RMF, and ISO/IEC 42001

Dimensions Measured

Minutes to Complete

Behavioral Subscores

0-1000

Standardized Scale

Aligned to GDPR, NIST AI RMF, ISO/IEC 42001, and SOC 2 principles.
Designed for responsible AI deployment from day one.

Starting at $3,500 for a 12-20 person Quick-Read

The Visibility Gap

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Why PAICE Matters

Behavior, Not Self-Report

Not a knowledge test or self-assessment. PAICE observes what people do when AI is uncertain, incomplete, or wrong — including catching injected errors.

Operational Risk Visibility

Where verification fails, confidence exceeds capability, and operational exposure concentrates. Surface organizational blind spots before they compound into liability.

Dimensional Evidence

Five behavioral dimensions: Performance, Accountability, Integrity, Collaboration, Evolution. Specific signals — not generic feedback — about where calibration breaks down.

Governance Without Surveillance

Comparable scores (0–1000) across individuals, teams, and organizations. No names, no emails, no integrations. Behavioral visibility without identity capture.

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