WFGY/ProblemMap/GlobalFixMap/Enterprise_Knowledge_Gov/compliance_audit.md

Compliance Audit — Enterprise Knowledge Governance

🧭 Quick Return to Map

You are in a sub-page of Enterprise_Knowledge_Gov.
To reorient, go back here:

• Enterprise_Knowledge_Gov — corporate knowledge management and governance
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

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.

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
Evidence cannot be reproduced	No deterministic ΔS/λ logs	retrieval-playbook.md
Multiple outputs differ for same input	λ flips or entropy collapse	context-drift.md, entropy-collapse.md
No visibility into expired docs	Missing expiry field in audit logs	knowledge_expiry.md
Incomplete audit trails	Storage not aligned to contracts	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:

   {
     "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.

---

<!-- WFGY_FOOTER_START -->

### 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 |

If this repository helped, starring it improves discovery so more builders can find the docs and tools.  
[![GitHub Repo stars](https://img.shields.io/github/stars/onestardao/WFGY?style=social)](https://github.com/onestardao/WFGY)

<!-- WFGY_FOOTER_END -->

要繼續幫你生嗎？