AI Startups
Model disclosures, training data provenance, output risk, and AI Act readiness.
Industries
We adjust scope, evidence, and severity weighting to the regulatory pressure your sector faces.
Model disclosures, training data provenance, output risk, and AI Act readiness.
DPAs, subprocessors, enterprise security questionnaires, and consent at scale.
PHI handling boundaries, vendor sharing, tracking pixels, and accessibility mandates.
Consent, disclosures, and marketing compliance under regulatory scrutiny.
Cookies, retargeting, SMS marketing consent, and checkout accessibility.
Lead-handoff consent, client pixel governance, and TCPA-safe capture.
Confidentiality, records management, and accessible client portals.
Multi-business-unit assessments, procurement reviews, and board reporting.
Sector notes
Same rigor, different weighting. Here is how the emphasis shifts.
Healthtech and fintech reviews lead with data-sharing boundaries, vendor exposure, and tracking on authenticated surfaces.
Commerce and DTC reviews weight consent capture, SMS flows, and retargeting disclosures the heaviest.
AI platforms get deeper coverage of training data provenance, output disclosure, and human review paths.