AI systems are being deployed into child-facing environments without independent verification.
Safety is being claimed. Not proven.
SAFE is the standard that proves it.
Independent definition. Independent verification. Structural separation.
View the StandardWhat's Happening
AI safety today is defined by guidance, policies, and internal testing.
Governments issue guardrails.
Companies define their own standards.
Systems are tested by the people who build them.
This is not verification.
What SAFE Is
SAFE is a verification standard.
It defines what safety is.
It verifies whether systems meet it.
It enforces separation between definition, implementation, and verification.
SAFE
Defines the standard
SAFE Labs
Verifies systems independently
SAIL
Implements the standard within systems
The Gap
Every high-risk system has independent verification.
Aviation.
Pharmaceuticals.
Infrastructure.
AI does not.
Consequence
Without independent verification:
Safety claims cannot be trusted.
Harm is addressed after it occurs.
Accountability does not exist.
Governance Whitepaper
The complete SAFE standard.
Why current AI safety systems fail — and the structural gap they leave
The separation principle — governance, certification, and implementation
SAFE-001 risk taxonomy — ten behavioural harm classifications (P1–P10)
Council structure, validation gates, and capture prevention architecture
Regulatory alignment — EU, UK, US, Australia, and UN frameworks
Five-phase adoption pathway from formation to recognised standard
Open Letter
A Call for Independent AI Safety Standards and Verification
Join governments, researchers, educators, technologists, and institutions worldwide in supporting the development of independent AI safety standards.
Read & Sign the Open Letter