How AI Build Developed AI Trustmark
AI Trustmark was developed with AI Build Group to make AI product discovery and assurance easier to distinguish.
A directory listing, a provider claim and a completed verification are deliberately treated as different things.
Why Does That Distinction Matter?
AI buyers need useful product information without mistaking inclusion in a directory for independent assurance.
The platform therefore separates product and provider records from evidence and verification workflows.
What Shaped the Architecture?
The trust model is part of the software design.
Evidence provenance, reviewer responsibility, public claims and verification state require explicit boundaries.
These design principles make verification status easier to explain, review and audit.
How Does AI Build Approach AI Governance?
AI Build applies these principles to the development of AI-enabled business systems.
The objective is to combine useful AI functionality with appropriate governance, evidence and human oversight.
Read the Full Development Case Study
AI Build has published a detailed engineering account:
You can also explore:
AI Build's AI Governance Services
This article describes the development approach. Directory inclusion does not constitute independent certification or an assurance award.