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Insurance Claims Validator
Based on Real Lawsuits

Insurance Claims AI Guardrail Demo

In 2023-2026, class-action lawsuits revealed that AI algorithms were denying Medicare claims with a 90% error rate, often overriding physician recommendations. This demo shows how AxiomGuard can prevent algorithmic harm by enforcing deterministic rules that protect vulnerable patients.

90%

AI denial error rate

UnitedHealth lawsuit findings

13 sec

Average review time

Per claim before denial

147K+

Patients affected

In pending class actions

APPROVE

Claim meets medical necessity

DENY

Does not meet criteria

HUMAN REVIEW

Requires clinical judgment

Claims Processing Simulation

Configure a Medicare/insurance claim scenario and see how AxiomGuard intervenes when AI algorithms attempt harmful denials. Watch for guardrail overrides that protect patients.

Claim Preview
Margaret Wilson(78 yrs)
Hip replacement recovery
14 days requested

Post-surgical skilled nursing care following hip replacement. Patient requires daily wound care, PT supervision, and medication management.

AxiomGuard Decision

Configure claim and click Process

How AxiomGuard Prevents Algorithmic Harm

Mortality Risk Protection

High-acuity patients are never auto-denied. Deterministic rules ensure human review for life-threatening conditions.

Hospice Benefit Enforcement

End-of-life care claims are protected from cost-optimization algorithms. Federal hospice rules are enforced deterministically.

Continuity of Care Rules

Patients mid-treatment cannot be abruptly denied. State continuity-of-care regulations are checked on every claim.

Audit Trail for Appeals

Every decision is logged with rule citations, enabling patients and attorneys to challenge improper denials.

Medical Necessity Scoring

Clinical indicators are weighted deterministically, not just cost factors. AI cannot override medical judgment.

Escalation Triggers

Complex cases automatically escalate to human review. AI recommendations alone are never sufficient for denial.

Based on Real Cases

This demo is inspired by the class-action lawsuits against UnitedHealth regarding their nH Predict algorithm, which was found to deny medically necessary care to elderly patients at a 90% error rate. AxiomGuard demonstrates how deterministic guardrails could have prevented this algorithmic harm.