Audit against every law that applies
Pick your regulations and run one audit. We scan your code and AI systems against the EU AI Act, SOC 2, NIST AI RMF and OWASP LLM, and map each finding to a control.
Run an audit against the laws that apply to you, then hand regulators a signed binder backed by tamper-evident evidence.
List every model, vendor and system you run.
We match each system to the controls that apply.
Every result is chained so it cannot be altered.
Hand regulators a signed, timestamped binder.
Backed by an append-only SHA-256 hash chain, Merkle proofs and write-once storage
Pick your regulations and run one audit. We scan your code and AI systems against the EU AI Act, SOC 2, NIST AI RMF and OWASP LLM, and map each finding to a control.
Every result is written to an append-only record, chained with SHA-256 hashes and timestamped. If a record changes, the chain breaks.
Get a regulator-ready binder, digitally signed and archived as PDF/A, that an auditor can check without trusting us.
Register every model, vendor and asset once. We map each one to its obligations and export an AI bill of materials on request.
See your coverage per framework, your open findings and a plan of actions and milestones, so you know what to fix next.
Migrating old COBOL estates? We mask personal data first, build a twin for review, and keep a rollback path for every step.
Covered, partial and gap controls for each framework, updated as evidence arrives — and flagged when it drifts.
EU AI Act · controls (example)
Regulatory audit · your repository (example)
src/model/train.py:42✕ EU AI Act Art. 10api/predict.py:118✓ passesconfig/logging.yaml:7✕ Art. 12 record-keepingdocs/model-card.md✓ passesPoint Axis at a repository and get a per-law report — complies or doesn't, down to the folder and line.
Signed PDF/A-3 binders and evidence packs your auditors can verify independently.
Audit binder (example)
Real penalties, real dates. The 2026 Digital Omnibus moved several deadlines. It did not remove the requirements.
Sources: Gibson Dunn · AI Act Explorer · Orrick
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