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37	37	* Detected manipulation attempt
38	38	* Unusual pattern
39	39	* Moderator reviews and may take action
	40	+
	41	+== 2.5 LLM-Based Processing Architecture ==
	42	+
	43	+FactHarbor delegates complex reasoning and analysis tasks to Large Language Models (LLMs). The architecture evolves from POC to production:
	44	+
	45	+=== POC: Two-Phase Approach ===
	46	+
	47	+**Phase 1: Claim Extraction**
	48	+* Single LLM call to extract all claims from submitted content
	49	+* Light structure, focused on identifying distinct verifiable claims
	50	+* Output: List of claims with context
	51	+
	52	+**Phase 2: Claim Analysis (Parallel)**
	53	+* Single LLM call per claim (parallelizable)
	54	+* Full structured output: Evidence, Scenarios, Sources, Verdict, Risk
	55	+* Each claim analyzed independently
	56	+
	57	+**Advantages:**
	58	+* Fast to implement (2-4 weeks to working POC)
	59	+* Only 2-3 API calls total (1 + N claims)
	60	+* Simple to debug (claim-level isolation)
	61	+* Proves concept viability
	62	+
	63	+=== Production: Three-Phase Approach ===
	64	+
	65	+**Phase 1: Claim Extraction + Validation**
	66	+* Extract distinct verifiable claims
	67	+* Validate claim clarity and uniqueness
	68	+* Remove duplicates and vague claims
	69	+
	70	+**Phase 2: Evidence Gathering (Parallel)**
	71	+* For each claim independently:
	72	+ * Find supporting and contradicting evidence
	73	+ * Identify authoritative sources
	74	+ * Generate test scenarios
	75	+* Validation: Check evidence quality and source validity
	76	+* Error containment: Issues in one claim don't affect others
	77	+
	78	+**Phase 3: Verdict Generation (Parallel)**
	79	+* For each claim:
	80	+ * Generate verdict based on validated evidence
	81	+ * Assess confidence and risk level
	82	+ * Flag low-confidence results for human review
	83	+* Validation: Check verdict consistency with evidence
	84	+
	85	+**Advantages:**
	86	+* Error containment between phases
	87	+* Clear quality gates and validation
	88	+* Observable metrics per phase
	89	+* Scalable (parallel processing across claims)
	90	+* Adaptable (can optimize each phase independently)
	91	+
	92	+=== LLM Task Delegation ===
	93	+
	94	+All complex cognitive tasks are delegated to LLMs:
	95	+* **Claim Extraction**: Understanding context, identifying distinct claims
	96	+* **Evidence Finding**: Analyzing sources, assessing relevance
	97	+* **Scenario Generation**: Creating testable hypotheses
	98	+* **Source Evaluation**: Assessing reliability and authority
	99	+* **Verdict Generation**: Synthesizing evidence into conclusions
	100	+* **Risk Assessment**: Evaluating potential impact
	101	+
	102	+=== Error Mitigation ===
	103	+
	104	+Research shows sequential LLM calls face compound error risks. FactHarbor mitigates this through:
	105	+* **Validation gates** between phases
	106	+* **Confidence thresholds** for quality control
	107	+* **Parallel processing** to avoid error propagation across claims
	108	+* **Human review queue** for low-confidence verdicts
	109	+* **Independent claim processing** - errors in one claim don't cascade to others
	110	+
	111	+
40	40	== 3. Risk Tiers ==
41	41	Risk tiers classify claims by potential impact and guide audit sampling rates.
42	42	=== 3.1 Tier A (High Risk) ===