The Blueprint for a Global AI Finance Hub: My "North Star" Structure
Even before the meetings happen, preparation is everything. I’ve been brainstorming how to take the principles we learn here and scale them for a global corporation (14,000 employees, 72 countries). This is the "North Star" for my journey toward becoming an AI Finance Manager. It’s a technical skeleton that ensures security, scalability, and—most importantly—the K.I.S.S. (Keep It Simple Stupid) model for the end-user. The Infrastructure (The Engine Room) Using the folder structure we’ve mastered, I’ve mapped out how a global hub would actually look "under the hood":Plaintext/ ├── CLAUDE.md # The Master Router (Direct OData Logic) ├── /identity # ACCESS CONTROL GATE │ ├── global_admins.md # Full access (Admin level) │ ├── DK.md # Validated users for Denmark │ └── [70+ countries].md # Global validation files ├── /library # THE COMMAND CATALOG │ ├── /global # Standard tools (e.g., /extract_ledger) │ └── /local # Country-specific tools (e.g., /dk_vat_report) ├── /core-logic # THE ENGINE ROOM │ ├── date_parser.md # Translates "MMYY" into OData parameters │ └── odata_templates.md # Master OData entity mapping ├── /countries # LOCAL CONTEXT & AUDIT │ └── /DK │ ├── audit-log.md # Record: Date | User | Command | Status │ └── local_settings.md # Local Legal Entity IDs / Currencies ├── /technical # SYSTEM RELIABILITY │ ├── mcp_config.md # OData read-only parameters │ └── health_check.md # System status triggers └── /schemas # EXCEL TEMPLATES └── ledger_standard.xlsx # Raw data structure The User Journey: From Teams to "Done" I want a user (let’s call him Lars) to get what he needs in under 60 seconds without ever touching a complex ERP menu. 1. The Request: Lars types /dk_vat_report 0126 in Microsoft Teams. 2. The Gatekeeper: The system checks /identity/DK.md. Lars is validated. 3. The Health Check: The system pings the MCP (Model Context Protocol). Connection is green. 4. The Data Pull: The AI uses the date_parser to see that 0126 means January 2026. It reaches directly into D365 via OData. 5. Delivery: The AI maps the data into a clean Excel template and uploads it to the chat. 6. Audit: The system silently logs the action for compliance.