Straight answers,
before you engage.

AI governance is the framework of policies, controls, and accountability structures that determine how AI systems are owned, monitored, and audited within an organization. It matters now because regulators, enterprise clients, and procurement teams are actively asking for evidence of it. Without a documented governance program, organizations face contract losses, regulatory exposure, and liability that cannot be quantified.

Yes. The Act applies to any organization deploying AI to users in the EU, regardless of where the organization is incorporated. U.S. companies whose software or services reach European users — or whose enterprise clients are themselves subject to the Act — need to understand their obligations. Geography is not the qualifier most U.S. companies assume it is.

The NIST AI Risk Management Framework is a voluntary federal framework for identifying, assessing, and managing AI risk. It is not currently mandatory for most organizations, but it is the de facto reference standard that auditors, enterprise procurement teams, and federal contractors use to evaluate whether an AI program is defensible. Alignment is increasingly a commercial requirement rather than a compliance one.

Engagements range from 2–20 weeks. A standalone AI Risk Assessment (S1) takes 2–4 weeks. A Governance Framework Setup (S2) takes 4–8 weeks. A complete program from first inventory to audit-ready certification readiness takes 10–20 weeks. Every timeline is set transparently in the engagement letter before work begins.

ISO/IEC 42001 is the international standard for AI management systems. Certification is increasingly written into enterprise RFPs and vendor qualification requirements. Whether it is worth pursuing depends on your client base, regulatory exposure, and organizational maturity. We give you an honest assessment of that in the discovery call.

It varies. Often Risk, Legal, or the CIO/CTO function sponsors it; operational ownership commonly sits with a cross-functional AI council. Part of S2 is recommending an ownership model that fits your size, sector, and risk profile — and writing it down so it survives staff turnover.

Governance as a Service (GaaS) is a model in which an external advisory like Kneuralabs builds, installs, and operationalizes your AI governance program — delivering it as a structured service rather than a one-time report. Kneuralabs GaaS covers AI risk assessment (S1), governance framework setup (S2), standards readiness (S3), and IT modernization (S4), all scoped transparently with fixed timelines and artefacts your team owns after engagement.

IT Modernization (Kneuralabs S4) re-platforms legacy systems for an AI-ready operating model. It covers architecture review, cloud and data foundation work, integration patterns, and a phased migration roadmap — so your infrastructure can support governed AI at scale. It runs 6–16 weeks standalone or sequenced into the full governance program.