A
AI Readiness
Framework as a product

Analyze a project against the framework

Point the framework at a real project. The analyzer reads the code, then scores both rubrics — Desirability and Feasibility & Viability — with evidence citations for every code-verifiable item, and honestly flags the items that need human/org artifacts (studies, signed memos, audits) that a code review can't produce.

Sample analysis
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Medicare Navigator AI — /v4 experience

The /v4 chat-first Medicare intake and enrollment experience: a hybrid voice + text intake that captures doctors, medications, ZIP, budget, and Medicaid status, verifies providers against NPPES and drugs against RxNorm, recommends a coverage strategy (Medicare Advantage, Medigap + Part D, or D-SNP) with a specific plan, and hands off to a licensed advisor for enrollment.

2 validated16 partial3 blocked78 items scored
Analyze your own project

Preview only. The intake pipeline (fetch → walk files → score via Lovable AI Gateway → persist report) isn't wired yet — the sample above shows the shape it will produce.

How the analyzer scores

Each rubric item is tagged as code-verifiable (confirmed or denied from repo contents, with a file quote) or needs-org-artifact (a question a code review honestly can't answer — a signed policy, a research study, an audit report). This keeps the score credible instead of over-claiming what static analysis can prove.

← Readiness approachRead the Desirability rubric →