OMNIERAX RESPONSIBLE AI POLICY

This policy applies to all AI and machine learning systems developed or deployed by Omnierax:

For customer-deployed models on Cortex AI, this policy establishes the governance architecture customers must configure — operational governance is the deploying customer's responsibility under applicable law.

Statement: Omnierax AI amplifies human judgment — it does not replace human authority over decisions that require human values, accountability, or contextual judgment.

Implementation: Every operational AI deployment includes a configurable Human Authority Framework — defining what the system may execute autonomously, what requires human review, and what is outside its authority. Enforced architecturally, logged immutably, and modifiable by authorized administrators.

Limitation: Omnierax will refuse configurations that remove meaningful human authority where our assessment is that human authority is required. Where reasonable disagreement exists, the more conservative position applies.

Statement: Every AI system that influences operational decisions must explain its outputs in terms human reviewers can understand, evaluate, and challenge.

Implementation: Explainability is a first-class product — ranked evidence inputs, reasoning chains, alternative conclusions evaluated, and confidence decomposition.

Scope: Depth scales with consequence. Routine outputs include standard explainability; high-consequence decisions include full evidence inventory and counterfactual analysis.

Limitation: For architectures with limited mechanistic explainability, we supplement with system-level transparency documented in AI System Cards and behavioral monitoring.

Statement: Omnierax AI must not systematically produce harmful, unjustified, or unlawful discrimination on protected characteristics.

Implementation: Bias assessments during development and continuous monitoring in production for systems affecting individuals.

Scope and Limits: Not all disparities are harmful bias. We distinguish genuine predictive relationships from model bias; genuine model bias requires mandatory remediation.

Statement: AI deployed in mission-critical environments must meet reliability standards appropriate to failure consequences and must fail safely outside their reliable envelope.

Implementation: Pre-deployment reliability specs cover minimum thresholds, known degradation conditions, behavior outside the envelope, and escalation/fallback procedures. Systems reduce confidence honestly, escalate to humans, and generate operational flags.

Continuous Monitoring: Production performance is tracked continuously; degradation triggers automated adjustment, human review, or suspension.

Statement: Systems are designed to use the minimum personal data necessary; training data is protected with the same rigor as production data.

Implementation: Data minimization assessments at design time. Pseudonymized, aggregated, or synthetic data preferred. Customer production data is not used to train models deployed for other customers without explicit authorization.

Omnierax AI is designed to resist adversarial manipulation — data poisoning, adversarial inputs, model inversion. Adversarial robustness testing during development; production monitoring for distribution shift; input validation and output confidence gating to limit operational impact.

Statement: Every significant AI decision must be attributed, recorded, and auditable.

Implementation: Every inference and automated action is recorded in the immutable AI Audit Ledger — input reference, model version, output, confidence, and any human review/override. Cryptographically chained. Access is role-based.

Retention: Typically 7 years for significant operational decisions, longer where law requires.

EU AI Act: For high-risk AI we implement risk management, data governance, technical documentation, transparency, human oversight, accuracy/robustness, and cybersecurity measures.

NIST AI RMF: Mapped to GOVERN, MAP, MEASURE, MANAGE — alignment documentation available through the Trust Portal.

National Regulations: Monitored and reflected in governance practice in the jurisdictions where products deploy.

Reviewed annually by the AI Governance Committee and updated when capabilities change, regulations change, gaps are identified, or external review suggests improvement. Contact: ai-governance@omnierax.com.