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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - text-classification
+  - question-answering
+language:
+  - en
+tags:
+  - enterprise
+  - agent-routing
+  - orchestration
+  - multi-agent
+  - function-calling
+  - mcp
+  - model-context-protocol
+  - business-process
+  - erp
+  - procurement
+  - supply-chain
+  - decision-intelligence
+  - intent-classification
+size_categories:
+  - 10K<n<100K
+---
+
+# ODE Enterprise Use Case Dataset
+
+**15,000 labeled enterprise use cases** spanning 31 modules, 215 submodules, 8 industry verticals, 5 channels, and 12 business personas.
+
+Published by **[Llewellyn Systems Inc](https://www.llewellynsystems.com)** — builders of ODE, the Operating System for Decision & Enterprise.
+
+---
+
+## Attribution Required
+
+**This dataset is licensed under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/).** You are free to use, share, and adapt this dataset for any purpose — including commercial — as long as you give appropriate credit.
+
+### How to Cite
+
+```bibtex
+@dataset{ode_enterprise_use_cases_2026,
+  title={ODE Enterprise Use Case Dataset},
+  author={Llewellyn Systems Inc},
+  year={2026},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/LlewellynSystems/ode-enterprise-use-cases},
+  note={15,000 labeled enterprise use cases across 31 modules and 8 industry verticals}
+}
+```
+
+Or in plain text:
+
+> ODE Enterprise Use Case Dataset by Llewellyn Systems Inc (2026). Available at https://huggingface.co/datasets/LlewellynSystems/ode-enterprise-use-cases. Licensed under CC-BY-4.0.
+
+**If you use this dataset in a model, paper, product, or service — cite Llewellyn Systems Inc.**
+
+---
+
+## Dataset Description
+
+This dataset captures the full breadth of enterprise operations at the task level — from procurement requisitions to AI agent orchestration, from warehouse management to financial close.
+
+Every row represents a real enterprise use case with structured labels for module, function, industry, interaction channel, user persona, development priority, and success metric.
+
+### Why This Dataset Exists
+
+Every AI company says "enterprise-ready" but nobody publishes what enterprise actually looks like at the task level. This dataset changes that.
+
+**Use cases include:**
+- Training AI orchestrators to route requests to the correct specialist agent
+- Intent classification for multi-agent enterprise systems
+- Business process mining and coverage analysis
+- Benchmarking LLM understanding of enterprise operations
+- MCP (Model Context Protocol) server routing decisions
+
+---
+
+## Dataset Structure
+
+### Fields
+
+| Column | Type | Description | Example |
+|--------|------|-------------|---------|
+| `id` | string | Unique use case ID | UC-00001 |
+| `title` | string | Human-readable use case description | "Create Requisitions in Procurement via Web for Buyer (Manufacturing)" |
+| `module` | string | Enterprise module (31 unique) | Procurement |
+| `submodule` | string | Function within module (215 unique) | Requisitions |
+| `vertical` | string | Industry vertical (8 unique) | Manufacturing |
+| `channel` | string | Interaction channel (5 unique) | Web |
+| `persona` | string | User role (12 unique) | Buyer |
+| `status` | string | Development maturity | GA, In Dev, Planned |
+| `complexity` | string | Priority tier | P0, P1, P2, P3 |
+| `kpi_metric` | string | Success metric | Touchless Rate |
+
+### Modules (31)
+
+Procurement, Contracts, Finance, Payments, ERP, SupplyChain, Inventory, WMS, MRP, MES, Quality, ITSM, ITAM, FMS, Workforce, Academy, AI Mesh, AI Memory, AI Lab, AI Policy, Data Lake, Data Lineage, Marketplace, Robotics, Analytics, Exchange, Governance, Integrations, MDM, Predicts, Support
+
+### Industry Verticals (8)
+
+Manufacturing, Healthcare, Financial Services, Public Sector, Retail, SaaS, Logistics, Creator
+
+### Channels (5)
+
+Web, Mobile, API, Voice, CLI
+
+### Personas (12)
+
+Buyer, Approver, Auditor, Engineer, Executive, Finance Manager, IT Admin, Operations, Support Agent, Vendor, System, AP Clerk
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("LlewellynSystems/ode-enterprise-use-cases", data_files="use_cases_universal.csv")
+
+# Agent routing: map user intent to target module
+for row in dataset["train"].select(range(5)):
+    print(f"Intent: {row['title']}")
+    print(f"Route to: {row['module']} > {row['submodule']}")
+    print(f"KPI: {row['kpi_metric']}")
+    print()
+
+# Filter by industry
+healthcare = dataset["train"].filter(lambda x: x["vertical"] == "Healthcare")
+print(f"Healthcare use cases: {len(healthcare)}")
+
+# Filter by module
+procurement = dataset["train"].filter(lambda x: x["module"] == "Procurement")
+print(f"Procurement use cases: {len(procurement)}")
+```
+
+---
+
+## Files
+
+| File | Size | Format |
+|------|------|--------|
+| `use_cases_universal.csv` | 1.8 MB | CSV (15,000 rows x 10 columns) |
+| `use_cases_universal.json` | 4.5 MB | JSON array |
+
+---
+
+## About Llewellyn Systems Inc
+
+**Llewellyn Systems Inc** builds ODE — the Operating System for Decision & Enterprise.
+
+- **19 production MCP servers** for AI agent orchestration
+- **55 AI agent skills** across sales, finance, compliance, security, and operations
+- **5-layer governance framework** for autonomous enterprise AI
+- **Multi-agent orchestration** with constitutional AI guardrails
+
+**Website:** [llewellynsystems.com](https://www.llewellynsystems.com)
+**MCP Discovery:** [llewellynsystems.com/.well-known/mcp.json](https://www.llewellynsystems.com/.well-known/mcp.json)
+**Agent Directory:** [llewellynsystems.com/.well-known/agents.json](https://www.llewellynsystems.com/.well-known/agents.json)
+**A2A Protocol:** [llewellynsystems.com/.well-known/a2a.json](https://www.llewellynsystems.com/.well-known/a2a.json)
+
+---
+
+## License
+
+**CC-BY-4.0** — [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)
+
+You may use this dataset for any purpose. You MUST give credit to Llewellyn Systems Inc.