Defensible by Design: How Neuro-Symbolic AI Solves What Traditional AI Cannot
How Neuro-Symbolic AI Architecture Determines Audit Outcomes
Your AI reports high accuracy. CMS still rejects your codes. The architecture is the problem.
This e-book reveals why traditional AI fails audits and how neuro-symbolic AI delivers explainable, audit-defensible risk adjustment through architecture, not tuning.
Key Outcomes
- Understand why high (94%) accuracy scores still fail CMS audits
- Identify structural limitations that cause traditional AI audit failures
- End hallucination and output variability permanently
- Enable persistent evidence trails that auditors can trace
What You’ll Gain
- Why traditional AI hallucination undermines audit defense
- How neuro-symbolic AI solves the accuracy trilemma
- What glass-box explainability means for RADV readiness
- Five questions to ask AI vendors before signing