Automated, repository-level scanning against 10 AI governance frameworks — NIST AI RMF, ISO 42001, EU AI Act, HIPAA, GDPR, FedRAMP, CMMC, ISO 23894, ISO 42005, and ISO 27001 — so governance keeps pace with how fast AI codebases actually change.
The scanner reads your repository's code for evidence of governance controls — audit logging, risk assessment, bias testing, encryption, human oversight — and scores each framework based on what it finds and what's missing.
Any public GitHub repository, branch, or folder — no local setup or CI integration required to get a first read.
Choose one or more of the 10 supported frameworks, matched to the regulatory and industry context that applies to the codebase.
An overall score, pillar-by-pillar breakdown, and specific findings with remediation guidance — in the time it takes to read this sentence, not the weeks a manual review takes.
This isn't a feature built for its own sake. It's a direct response to a well-documented gap: governance reviews conducted quarterly or annually can't keep pace with codebases that change daily, and that gap is exactly where AI initiatives stall or get penalized.
Built by Mary Hartwell as part of Hartwell & Co.'s work turning AI governance research into practical tooling. Get in touch to talk through what a governance scanning program looks like for your codebase and your regulatory context.
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