Reasoning Platform Proof Stack
Complete transparency, explainability, and governance for every AI decision. From input to reasoning to output—every step is documented, auditable, and explainable.
Last reviewed: 2026-01-06
What is the Reasoning Platform Proof Stack?
The Reasoning Platform Proof Stack is IntelliHuman's comprehensive framework for AI decision transparency. Every decision generates: input provenance, reasoning trace, explainability artifacts, immutable audit logs, and human oversight workflows—ensuring AI decisions are explainable, auditable, and compliant with regulatory requirements.
The Six Layers of Proof
1. Input Provenance
Every data point used in a decision is tracked to its source: EHR system, policy document, user input, external API. Data lineage ensures traceability.
Example: 'Patient BMI (32.4) sourced from EHR record dated 2026-01-03, recorded by Dr. Smith (NPI: 1234567890).'
2. Reasoning Trace
The AI reasoning process is captured step-by-step: rules evaluated, criteria checked, evidence considered, alternatives explored, confidence calculated.
Example: 'Evaluated medical necessity criteria: 1) Failed conservative treatment ✓, 2) BMI >30 ✓, 3) Comorbidity present ✓ → Medical necessity MET (confidence: 92%)'
3. Explainability Artifacts
Human-readable explanations generated for every decision: why this decision was made, what evidence supported it, what factors were most influential.
Example: 'Authorization APPROVED because patient meets all 3 medical necessity criteria per Aetna Policy #MED-2024-001. Patient has documented 6-month history of failed conservative treatments.'
4. Immutable Audit Trail
Every decision, input, and reasoning step logged to tamper-proof audit trail with timestamps, user context, system version, and environmental factors.
Example: '[2026-01-06 14:23:45 UTC] User: jane.doe@health.org | Decision ID: PA-2026-00123 | AVI Version: 2.4.1 | Policy: Aetna MED-2024-001 | Outcome: APPROVED'
5. Governance & Compliance
Role-based access controls, approval workflows, compliance checks, and policy enforcement ensure AI operates within organizational and regulatory boundaries.
Example: 'High-value authorization ($50K) triggered automatic medical director review. Approved by Dr. Johnson (MD-5678) on 2026-01-06 at 15:45 UTC.'
6. Human Oversight & Feedback
Subject matter experts review AI decisions, provide feedback, override when necessary, and contribute to continuous model improvement—all actions logged.
Example: 'Adjuster override: AI recommended DENY but adjuster approved based on special circumstances (documented in note #456). Override logged, case escalated for model refinement.'
Why the Proof Stack Matters
Regulatory Compliance
Meet HIPAA audit requirements, SOC 2 change controls, insurance regulatory compliance, FDA 21 CFR Part 11, and EU AI Act transparency mandates.
Legal Defense
Defend against claims or audits with complete documentation: 'Here's exactly what data was used, how the decision was made, and who approved it.'
Quality Assurance
Internal QA teams can review AI decisions, identify improvement opportunities, and ensure AI operates consistently with organizational policies.
Continuous Improvement
Human feedback and overrides create a learning loop: AI learns from expert corrections, improving accuracy and reducing future overrides.
Trust & Transparency
Stakeholders (patients, customers, regulators) can understand how decisions are made, building trust in AI-assisted operations.
Frequently Asked Questions
What is the Reasoning Platform Proof Stack?
The Proof Stack is IntelliHuman's comprehensive framework for AI decision transparency. It includes: input provenance, reasoning trace, explainability artifacts, audit trails, governance workflows, and human oversight—ensuring every AI decision is explainable, auditable, and accountable.
How does IntelliHuman ensure AI decisions are auditable?
Every decision generates an immutable audit log capturing: input data with source provenance, rules and policies applied, reasoning steps taken, evidence evaluated, confidence scores, output decision, and user context. These logs support compliance audits, regulatory reviews, and internal quality assurance.
Can humans override AI decisions?
Yes. IntelliHuman provides human-in-the-loop workflows where subject matter experts can review AI recommendations, override decisions with rationale, and provide feedback that improves the AI model. All overrides are logged with justification for auditability.
What compliance standards does the Proof Stack support?
The Proof Stack supports HIPAA audit requirements, SOC 2 change management and access controls, insurance regulatory compliance, FDA 21 CFR Part 11 (electronic records), and EU AI Act transparency requirements.
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