AI governance
Responsible AI decisions with a record behind them.
Data>Nuance helps SaaS and AI companies build practical governance around systems deployed across Europe and the United States.
Governance pathway
Controls that can be used before and after launch.
Inventory and intake
Identify AI use cases, models, vendors, personal-data touchpoints, affected decisions and internal owners.
Use-case intake recordRisk classification
Assess privacy impact, human oversight, transparency, security, fairness and jurisdiction-specific expectations.
Risk classification memoVendor and model review
Review terms, data use, training controls, subprocessors, assurance evidence and escalation obligations.
Vendor evidence fileDecision documentation
Create approval records, monitoring triggers, customer-facing evidence and repeatable governance routines.
Launch decision logRegulatory context
EU discipline. US operational readiness.
European operations may require a joined-up review of GDPR accountability, DPIAs and EU AI Act obligations. US buyers and customers increasingly expect clear vendor, privacy, security and governance evidence even where regulation differs by state or sector.
The objective is a workable record: who owns the use case, what risks were assessed, what safeguards are operating and when the decision is reviewed again.