AIhood™
Robotic automation in a laboratory
Resources

Learn. Evaluate. Build.

Educational material, evaluation tools that demonstrate outputs, and technical resources for adoption.

Learn

Understand why Physical AI needs verifiable evidence and how AIhood works.

Test FAQ

Common questions about the AIhood Readiness Test, scoring and Verification Levels.

Why Software Logs Aren't Insurance Evidence

Descriptive logs describe; they rarely prove. What insurers actually need.

What Insurers Need From Physical AI

The verifiable facts behind an insurable machine.

Evaluate

Score methodology, sample reports and self-evaluation tools.

How the Score Works

Dimensions, weights, the 0–4 capability scale, evidence sources and Verification Levels.

Sample Readiness Report

A worked example of the full AIhood Readiness Report.

Capability & Risk Self-Evaluation

Map machine capabilities to evidence and risk considerations.

Standards Gap Checker

Check your evidence practices against relevant standards.

Build

Integration paths and implementation resources for builders.

AEM Integration Paths Overview

Choosing between existing secure hardware, AEM module, and EPU/SoC integration.

Identity-Binding Implementation Checklist

A builder-facing checklist for binding identity to the physical asset.

Component Evidence-Profile Explorer

Explore evidence profiles for common machine components.