Trust Requires More

“We don’t just check if your AI works. We ask whether it deserves to be trusted.”

How Do We Measure Responsible AI?

TRUST-AI Open™ Standard: Lead Responsible AI

Unlock trust with the TRUST-AI Open™ Standard, the only framework offering system-level assessments, SPRI™ validation, and A+/AA+/AAA+ badges with QR-coded profiles. Unlike NIST’s generic RMF or ISO 42001’s governance focus, TRUST-AI delivers operational outcomes and cultural maturity for AI ethics.

Human Centred

Organizational: Responsible AI begins with organisational intent—your systems should reflect your values, not just your ambitions.

System: AI must support human agency, align with social context, and remain meaningfully contestable by people.

Transparent

Organizational: Your teams must be clear on who owns decisions, how AI is used, and its impact on stakeholders.

System: Responsible AI systems are explainable, auditable, and traceable—designed to be understood, not just observed.

Trustworthy

Organizational: Trust is built when organisations take proactive steps to secure data, manage risk, and respond to failure.

System: AI must be safe, secure, and respectful of privacy—robust in design, accountable in failure, and resilient under scrutiny.

TRUST-AI is the World’s First Responsible AI-as-a-Service™

Responsible AI-as-a-Service (RAIaaS) is a new model for AI maturity. We give organisations the tools, frameworks, and public trust signals to scale AI responsibly. It's not a whitepaper. It's not a principle. It's a productised trust system for the AI age.

TRUST-AI Open™

The only the only framework with organisation and system-specific criteria. Unlike NIST’s generic RMF or ISO 42001’s governance focus, TRUST-AI Open™ delivers operational outcomes and cultural maturity for Responsible AI.

TRUST-AI Check™

A free online tool for your organization to check it can meet the basic requirements for TRUST-AI Verified™ rating.

TRUST-AI Ready™

A readiness assessment allowing your enterprise to internally benchmark AI capability and identify gaps before undertaking a TRUST-AI Verified™ assessment.

TRUST-AI Verified™

Complete multi-tier, quantitative and qualitative maturity-based scoring of your organization and AI system(s) for a TRUST-AI Verified™ Responsible AI rating (A+, AA+, or AAA+).

TRUST-AI Verified™: Certify What Matters

Culture. Systems. Trust. Our unique multi-tier certification framework assesses how well your organisation governs AI—and how your individual systems bring those values to life.

How Does TRUST-AI Verified™ Compare to Global AI Standards?

TRUST-AI Open™ and TRUST-AI Verified™ build on the principles of ISO/IEC 42001, NIST AI RMF, OECD, and UNESCO—but go further. They transform ethical intent into operational assurance across both organizations and systems.

Key Area ISO/IEC 42001 NIST AI RMF OECD UNESCO TRUST-AI Verified™
Type Management System Standard Risk & governance framework Policy principles Global ethics recommendations Assessment + certification model (Org + System)
Focus Top-down governance Risk-based controls & mapping Transparency, fairness, values Human rights, ethics, inclusion Operational outcomes, cultural maturity, AI trust signals
System-Level Specificity Limited Partial use-case focus Abstract principles Macro-level policy framing Explicit assessment of individual systems, not just governance
Ethical Depth Referenced Referenced Foundational Foundational Embedded throughout in scoring, review, and readiness
Certification Output ISO-certified accreditation Non-certification framework Policy influence only Policy influence only A+, AA+, AAA+ scoring and badge with system traceability

Fast Comparison Snapshot

A quick look at how TRUST-AI Verified™ stacks up against global frameworks:

Capability ISO 42001 NIST AI RMF OECD UNESCO TRUST-AI Verified™
Dual-Level (Org + System) ❌ ⚠️ Partial ❌ ❌ ✅
Behavioural Maturity Scoring ❌ ❌ ❌ ❌ ✅
Certification with Public Badge ✅ ❌ ❌ ❌ ✅
Human-Centred Evaluation ⚠️ Referenced ⚠️ Referenced ✅ ✅ ✅
Designed for Practical Adoption ⚠️ Policy-led ⚠️ Risk-led ❌ ❌ ✅

Legend: ✅ Yes | ❌ No | ⚠️ Referenced but not operationalised