# Compliance Audit — Enterprise Knowledge Governance

<details>
  <summary><strong>🧭 Quick Return to Map</strong></summary>

<br>

  > You are in a sub-page of **Enterprise_Knowledge_Gov**.  
  > To reorient, go back here:  
  >
  > - [**Enterprise_Knowledge_Gov** — corporate knowledge management and governance](./README.md)  
  > - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)  
  > - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)  
  >
  > Think of this page as a desk within a ward.  
  > If you need the full triage and all prescriptions, return to the Emergency Room lobby.
</details>


Guardrails and patterns to enforce **compliance-ready audits** in AI pipelines.  
Use this page when enterprise policies or regulators require **auditability, traceability, and repeatable evidence** for AI knowledge usage.

---

## When to use this page
- Internal or external auditors require proof of AI outputs.  
- You need to show exactly which documents were cited and how they were retrieved.  
- Enterprise standards mandate **compliance trails** (ISO, SOC2, GDPR, HIPAA, etc).  
- Users ask "why did the model say this?" and you must replay the answer deterministically.  

---

## Core acceptance targets
- Every AI output must be linked to **retrieval evidence** (doc_id, section_id, offsets).  
- **ΔS(question,retrieved)** logged per query, with thresholds verified.  
- **λ_observe** states stored for all runs (paraphrase, rerun, seeds).  
- Full **audit trail exportable** (JSON, CSV, signed logs).  

---

## Typical audit failures → exact fix

| Symptom | Likely cause | Open this |
|---------|--------------|-----------|
| Missing or inconsistent citations | No schema enforcement on retrieval | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
| Evidence cannot be reproduced | No deterministic ΔS/λ logs | [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) |
| Multiple outputs differ for same input | λ flips or entropy collapse | [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) |
| No visibility into expired docs | Missing expiry field in audit logs | [knowledge_expiry.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Enterprise_Knowledge_Gov/knowledge_expiry.md) |
| Incomplete audit trails | Storage not aligned to contracts | [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) |

---

## Fix in 60 seconds
1. **Enforce snippet schema**:  
   Each retrieval must return `doc_id`, `section_id`, `offsets`, `tokens`, `expiry_date`.  

2. **Log ΔS and λ** per step:  
   Store values for retrieval, assembly, reasoning.  

3. **Export audit logs**:  
   JSON or CSV export at end of run.  
   Example:  
   ```json
   {
     "question": "What is policy X?",
     "ΔS": 0.38,
     "λ": "→",
     "citations": ["doc123#section5"],
     "timestamp": "2025-08-28T12:34:00Z"
   }
````

4. **Replay capability**:
   Store retriever seed + config for deterministic reruns.

---

## Copy-paste compliance probe

```txt
You have TXTOS and WFGY Problem Map loaded.

My compliance audit requirement:
- Audit log must contain {ΔS, λ_state, citations, expiry_flag}
- Logs must be exportable to JSON/CSV

Task:
1. Verify schema presence in retrieval.
2. Re-run with same seed and compare logs.
3. If mismatch, cite the exact WFGY page that explains the fix.
```

---

## Escalate when

* Audit log missing ΔS or λ.
* Same seed replay yields different citations.
* Expired documents appear in logs as valid.

Escalation fix: apply [ops/debug\_playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/ops/debug_playbook.md) and [bootstrap-ordering.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) to enforce deterministic ordering.

---

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### Explore More

| Layer | Page | What it’s for |
| --- | --- | --- |
| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |

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