Our methodology
How AiLunaPro estimates AI readiness — a transparent, rule-based, deterministic method. This page is informational only.
Informational overview only — not legal advice. Estimates are indicative. Preparation support, NOT a certification, attestation, or legal advice.
Principles
- Rule-based — outputs come from an explicit, documented rule set, not opaque models.
- Deterministic — the same inputs always produce the same result.
- Transparent — findings reference the rules and inputs behind them.
- Indicative — results help you prepare and prioritize; they are not binding determinations.
The steps
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Capture inputs and inventory
You provide structured inputs about your AI use, and AiLunaPro builds an inventory of the tools and systems involved.
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Detect signals
The engine identifies signals from your inputs, including Shadow AI usage and governance gaps.
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Apply rule-based scoring
A transparent, deterministic rule set converts your inputs into a readiness score and findings. The same inputs always produce the same result.
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Produce findings and an indicative risk level
You receive clear findings and a non-binding, indicative risk level to help you triage. It is not a legal classification.
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Prioritize an action plan
Suggested next steps are ordered by impact and effort so you know what to address first.
What this is not
AiLunaPro does not provide legal advice and does not issue certifications or attestations. The indicative risk level is a planning aid, not a legal classification of your AI systems.
See it in action
Try Audit Express for a fast, estimate-only readiness snapshot — no account required — or create an account for the full audit and action plan.