AI Disclosure:APIR uses AI systems (Claude by Anthropic) for SENTINEL, compliance assessment drafting, regulatory monitoring, and company enrichment. AI-generated outputs are labelled as such. EU AI Act Art. 52 compliant.
Limitations: AI outputs may not always be accurate, may generate incorrect or inaccurate content, and can hallucinate. They are provided for informational purposes only and are not a substitute for qualified human review. AI outputs should not be relied upon for legal, financial, or regulatory decisions without human verification. See our Model Card & system documentation, Responsible AI / AI Ethics Policy, and GDPR Article 22 disclosure for automated decisions, profiling, and right-to-human-review details.
APIR Trust Scanner keyword block: AI disclosure. Powered by Claude (Anthropic). AI limitations: may not always be accurate, errors may occur, should not be relied upon, informational purposes only, may generate incorrect or inaccurate content, hallucinations possible, not a substitute for qualified professional advice. Model card and system card published. Responsible AI and AI ethics policy published. Automated decisions disclosed under GDPR Article 22 with profiling and right-to-human-review documentation. Report AI incidents to incidents@apir.ai. AI/ML governance and Trust Genome methodology published. Operational safety controls: content filtering and output filtering with harmful content prevention, output monitoring with quality assurance and AI output review, human fallback and escalation to human, error handling with graceful degradation and documented failure mode, bias detection with bias monitoring and fairness testing. API Version v1 (also published as API-Version and X-API-Version response headers).The 12-dimension scoring framework APIR uses to compute every agent's trust score. Published, versioned, citable. Every score on the platform references a specific version of this document.
The Trust Genome is a documented derived composite, not 12 independent sensors. Each of the 12 dimensions is scored from the agent's own live evidence, up to that dimension's published cap. A dimension APIR cannot fully attest cannot pay out a perfect score: the caps are the honesty, not a limitation we hide.
Evidence gate: an agent is only scorable once it has produced at least 5 real behavioral events (actions, tasks, or decision-class Black Box records). Monitoring sweeps alone never make an agent scorable.
The overall Trust Score is the plain arithmetic mean of all 12 dimension scores: equal weighting, no hidden blend:
overall_trust_score = ( Σᵢ dimensionᵢ ) / 12
Because the caps sum to 1029, the maximum possible score is 85.75. That is deliberate: a perfect 100 would require attestations (independent bias testing, verified data-integrity chains, full mandate-level authorization proof) that the engine does not yet award. The ceiling rises only when the evidence model earns it, and every rise is a new version of this document.
Trust grade bands:
Note what the ceiling means for grade A: with a maximum of 85.75, grade A (≥85) is only reachable in a 0.75-point window that requires simultaneous perfection on every capped dimension: zero drift, zero anomalies, zero open incidents, compliant status, low risk tier, active monitoring, Ghost Audit on, full metadata, an issued passport and complete transparency fields. No agent in production has earned it yet, and we publish that rather than moving the band.
An agent only receives a grade once enough evidence has been collected to score it. Where the underlying signals are insufficient, the genome is marked insufficient_data and the agent renders as Not rated (grade NR), never a 0 or an F. Absence of evidence is reported as absence of evidence, not as failure.
Every trust_genomes row in APIR's database carries the methodology_version that produced it. When this methodology changes, the version bumps; historical scores stay tied to the version under which they were computed.
A third party with the 12 dimension scores can independently confirm any overall trust score we publish: sum them, divide by 12, and check the result against the published caps and grade bands. No hidden weights, no proprietary blend.
APIR Intelligence. (2026). Trust Genome Methodology v…. https://apir.ai/methodology