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| title: Murray Love Code | |
| emoji: 🛡️ | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: static | |
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| short_description: Open enterprise data agent governance resources | |
| # Enterprise Data Agent Governance | |
| **Open resources for deciding when an AI agent may answer from enterprise data, when it must request clarification or defer, and what evidence an organization should retain.** | |
| This organization hosts the Hugging Face distribution of the Enterprise Data Agent Governance project. The current dataset contains 18 synthetic evaluation cases across three decision bands—`answer`, `needs_definition`, and `refuse`—alongside machine-readable controls, schemas, citation metadata, licensing, and a version-pinned Mnemiq evidence record. | |
| ## Project resources | |
| - [Hugging Face dataset](https://huggingface.co/datasets/murraylovecode/enterprise-data-agent-governance) — evaluation cases and machine-readable governance resources | |
| - [Canonical GitHub repository](https://github.com/murraylovecode/enterprise-data-agent-governance) — code, schemas, project files, releases, and version history | |
| - [Public reference site](https://murraylovecode.github.io/enterprise-data-agent-governance/) — framework overview and practitioner guidance | |
| - [GitBook knowledge base](https://murray-love-code.gitbook.io/murray-love-code-docs/) — navigable implementation guidance | |
| ## Scope | |
| The resources support governed enterprise-data-agent evaluation, refusal testing, control workshops, and reproducible implementation planning. The cases are synthetic and are not a substitute for deployment-specific testing, access controls, semantic ownership, data-quality checks, or human oversight. | |
| ## Important disclosures | |
| This project is independently maintained by Murray Newlands as a personal practitioner resource. It is not official product documentation for Mnemiq or Agentic Fabriq and does not constitute independent certification or validation of any vendor. Mnemiq is included as a publicly inspectable worked case study. Agentic Fabriq develops and maintains Mnemiq, and Murray Newlands advises Agentic Fabriq. | |
| The framework is not legal, compliance, or security advice. Organizations must adapt its controls to their own risk, data, jurisdiction, and operating environment. | |