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1 contribution to Clief Notes
The Blueprint for a Global AI Finance Hub: My "North Star" Structure
Even before the meetings happen, preparation is everything. Iโ€™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. Itโ€™s a technical skeleton that ensures security, scalability, andโ€”most importantlyโ€”the K.I.S.S. (Keep It Simple Stupid) model for the end-user. The Infrastructure (The Engine Room) Using the folder structure weโ€™ve mastered, Iโ€™ve mapped out how a global hub would actually look "under the hood":Plaintext/ โ”œโ”€โ”€ CLAUDE.md # The Master Router (Direct OData Logic) โ”œโ”€โ”€ /identity # ACCESS CONTROL GATE โ”‚ โ”œโ”€โ”€ global_admins.md # Full access (Admin level) โ”‚ โ”œโ”€โ”€ DK.md # Validated users for Denmark โ”‚ โ””โ”€โ”€ [70+ countries].md # Global validation files โ”œโ”€โ”€ /library # THE COMMAND CATALOG โ”‚ โ”œโ”€โ”€ /global # Standard tools (e.g., /extract_ledger) โ”‚ โ””โ”€โ”€ /local # Country-specific tools (e.g., /dk_vat_report) โ”œโ”€โ”€ /core-logic # THE ENGINE ROOM โ”‚ โ”œโ”€โ”€ date_parser.md # Translates "MMYY" into OData parameters โ”‚ โ””โ”€โ”€ odata_templates.md # Master OData entity mapping โ”œโ”€โ”€ /countries # LOCAL CONTEXT & AUDIT โ”‚ โ””โ”€โ”€ /DK โ”‚ โ”œโ”€โ”€ audit-log.md # Record: Date | User | Command | Status โ”‚ โ””โ”€โ”€ local_settings.md # Local Legal Entity IDs / Currencies โ”œโ”€โ”€ /technical # SYSTEM RELIABILITY โ”‚ โ”œโ”€โ”€ mcp_config.md # OData read-only parameters โ”‚ โ””โ”€โ”€ health_check.md # System status triggers โ””โ”€โ”€ /schemas # EXCEL TEMPLATES โ””โ”€โ”€ ledger_standard.xlsx # Raw data structure The User Journey: From Teams to "Done" I want a user (letโ€™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.
0 likes โ€ข 15h
What you have done is well though out However, and I don't want to be negative, but your goal may be a bit too ambitious. There's lots of solutions that pull data from systems, like my favourite, Qlik that are far more cost effective at data manipulation. I would take your idea and scale back to just one painful task like looking up an invoice. Get that working perfectly then move ahead based on user requirements. Good luck ๐Ÿคž
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John-Paul Della-Putta
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@john-paul-della-putta-5830
I run an IT consulting business in Adelaide, called Advance.

Active 4h ago
Joined Apr 27, 2026
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