Skip to content

Crosswalk

Crosswalk reads your AI governance policy and validates it against EU AI Act, NIST AI RMF, FDA AI/ML SaMD, and ISO 42001 in one pass.

Core trick

Chains three LLM steps: extract policy commitments, map each to framework clauses with quoted evidence IDs, then draft matching replacement language.

Tags

Description

Crosswalk reads your AI governance policy and validates it against EU AI Act, NIST AI RMF, FDA AI/ML SaMD, and ISO 42001 in one pass. You get drop-in policy language for every gap, not a remediation roadmap. The pipeline is a 3-step prompt chain. Sonnet 4.6 extracts every concrete commitment from the policy as structured data. Opus 4.7 maps each commitment to framework requirements with verbatim evidence citations — every covered finding cites a specific commitment ID and a substring of that commitment's evidence quote, so you can audit Crosswalk's reasoning by hovering, not by trusting. Opus 4.7 then drafts remediation language matched to the policy's voice — preserving modal verbs, structure, and register. Microsoft RAI gets dense legalistic prose with numbered RS4.X structure. A flatter corporate policy gets institutional voice. I empirically verified by running the same Article 55 gap through both and comparing. Two features I'm proud of: Industry-aware applicability gate. Tell Crosswalk your industry and role, and it marks structurally out-of-scope requirements as not-applicable. Run a tech company through FDA SaMD and clinical-device requirements get skipped with a written rationale per item, not surfaced as false-positive gaps. The skipped section is the difference between a tool and a checklist. Tier C cross-framework merging. Equivalent requirements across regulators (e.g., EU Article 9 risk management ≡ ISO 42001 Clause 6.1) collapse into single proposals via union-find clustering, so accepting one fix counts toward both regulators' coverage. Soft-conflict detection (Jaccard similarity on token sets) flags when regulators want different things on the same topic. Word .docx export ships with a cover page, framework citations, severity badges, change-list table, and full audit trail. Per-step prompt caching keyed on policy_hash + framework_id makes re-runs near-instant and deterministic. Schema robustness via permissive parse + post-hoc hydration handles model drift without failing.

The linked repo returns 404, so it was deleted or made private.