TRUST LAYER™ builds, deploys, and maintains the trust signals, governance declarations, and transparency layer that AI systems use to determine whether a business is credible, reliable, and authoritative enough to recommend to buyers.
Verification proves claims are accurate. Trust proves something different — that the business is a reliable, consistent, and transparent source of information that AI systems can reference with confidence. These are different problems. A business can be verified and still score low on trust.
AI systems weight trust signals separately from verification signals. A business that is verified but untrusted will appear in AI answers. It will rarely be recommended. TRUST LAYER™ builds the signals that move a business from verified to trusted — from appearing in answers to being chosen as the answer.
Each pillar addresses a distinct dimension of how AI systems evaluate business credibility.
Does AI treat your business as a credible, consistent source in its category? Built from external citations, sector directory presence, client testimonials with schema markup, peer reviews, and professional body memberships — all structured in the Trust Registry.
Are your AI usage, data handling, and editorial policies declared and machine-readable? HITL protocol documentation, EU AI Act readiness declarations, GDPR compliance posture, and algorithmic transparency statements — all published in structured format.
Can AI systems verify how your content is produced, who is responsible for it, and what standards it meets? Editorial standards declaration, content authorship attribution, data processing declaration, and AI usage declaration — all machine-readable.
The Trust Registry is published as authority.json — a machine-readable file AI systems access directly to evaluate the business's trust profile.
Every governance declaration is published in both machine-readable JSON and human-readable PDF. AI systems read the JSON. Auditors and regulators read the PDF.
Documents the Human-in-the-Loop governance process used in all AI deployments. Every stage of the ADI™ pipeline where human review is mandatory. The declaration AI systems and EU AI Act auditors look for when assessing responsible AI use.
Structured declaration of EU AI Act readiness activities completed and in progress. Not a certification — a machine-readable statement of readiness posture. Updated quarterly. We support readiness. We never certify.
Machine-readable statement of data processing activities, legal bases, data subject rights provisions, and data retention policies. Aligned with Romanian ANSPDCP requirements and EU GDPR.
Declaration of what AI tools are used in business operations, for what purposes, with what human oversight, and with what safeguards. Required for high-trust AI visibility positioning.
All trust signals, citations, external references, and authority indicators in structured JSON. Updated automatically as new signals are added. Publicly accessible at domain root.
Composite trust score with dimensional breakdown, verification status, last audit date, open gaps, and trend data. Input for AI SONAR™ continuous monitoring.
Machine-readable policy declarations covering data handling, AI usage, content authorship, and editorial standards. Both machine-readable JSON and human-readable PDF.
HITL protocol, EU AI Act readiness declarations, GDPR compliance posture, and algorithmic transparency statements. Updated quarterly. Both formats.
Composite score reflecting the density, quality, and consistency of trust signals across all trust signal categories — citations, reviews, case studies, and professional body presence.
Score reflecting the completeness and currency of governance documentation against EU AI Act, GDPR, and sector-specific standards. Updated every time a governance document changes.
Score reflecting the completeness and currency of editorial standards, authorship declarations, data processing declarations, and AI usage declarations.