prototype-classifier

Assess software tool readiness by classifying the artifact onto a four-rung production ladder using evidence-based thresholds. This classification evaluates risk and gauges deployment readiness from personal tools to customer-facing environments.

A production ladder for classifying AI artifacts is a four-rung framework that evaluates tools from personal use to customer-facing deployments. It uses evidence-based thresholds to determine governance gating and upgrade readiness.

Classify internal tools for governance gating by using a six-question intake process focused on specific criteria. This structured evaluation determines the tool's production readiness and identifies promotion gaps for upgrade planning.

Yes, you can use this classifier for upgrade planning of customer-facing tools. It evaluates software artifacts against evidence-based thresholds and generates a structured promotion-gap report to guide your upgrade decisions.

The four-rung ladder limits tool classification to four distinct phases, from personal tool to customer-facing deployment. It requires complete answers to six intake questions to accurately assess production readiness and avoid misclassification.

No, the classifier does not require specific dependencies to evaluate software artifacts. It operates independently using a six-question intake and evidence-based thresholds to determine production readiness and generate promotion-gap reports.