🧠 AI Knowledge Layer Architecture: Where AI Advises, Humans Decide

#tauguard #taudil #ai #aigovernance

Here's a breakdown of this powerful governance-first AI architecture built around a Company Knowledge Graph (CKG):

🔷 Three-Layer Design

1️⃣ AI KNOWLEDGE LAYER (Advisory Only | No Execution Authority)

Documents & Data → EU AI Act, Policies, Contracts feed into the system
CKG (Company Knowledge Graph) → Entity Extraction, Relation Typing, confidence-gated via SandboxCKG + AGL
SYGON → φ-Lattice Semantic Engine with Wave Coherence, Drift Tracking, ManifoldWalker & Domain Registry
AI Assistant → Provides Context, Explanation & Reasoning Support — Advisory Only

🚫 NO EXECUTION AUTHORITY — The AI never acts on its own.

2️⃣ SEMANTIC GATES (SYGON Read-Only Checks)

Three critical gates ensure integrity at every stage:

Gate	When	Threshold
`ckg_integrity_gate()`	Before CKG commit	Coherence + Drift check
`pre_llm_gate()`	After rules loaded, before AI call	Coherence > 0.55
`post_llm_gate()`	After AI output, before verdict	Coherence > 0.50

🔒 SYGON is read-only here — gates observe, never write.

3️⃣ EXECUTION LAYER (Deterministic Rules Only | No AI | No Inference)

RulesEngine → Whitelist DSL only (CONTAINS/MATCHES/>/</=/!=). No eval(), no exec(), no imports
SafeConditionEvaluator → Pure String/Regex/Numeric — zero AI involvement
CanonicalQueryEngine → Applies rules before AI call, full audit trail via Aelthered
HUMAN DECISION → Final Authority, informed by AI context, enforced by Rules

🔑 Key Principles

✅ Authority Boundary — AI stops at the gate. Humans make final decisions.
✅ Semantic Gate Boundary — Separates knowledge from execution.
✅ Human-in-the-Loop — Emerging concepts are reviewed by humans before CKG expansion.
✅ Audit Trail — Every query logged as OK/BLOCKED/REFUSED/FLAGGED.
✅ EU AI Act Compliant — Built for regulatory alignment from day one.