Microsoft Foundry Platform Setup
Your production-ready AI platform on Azure. EU data residency, RBAC, cost management, and first model deployment — structured, configured, documented.
Leadership Expects AI Results. Your IT Has No Platform to Deliver Them.
Azure is in place. Copilot licenses may be too. What is missing: a structured, GDPR-compliant environment where AI models can be operated securely. Without this foundation, every AI initiative remains an experiment — no governance, no cost control, no path to scale.
This is not a failure of your IT team. It is reality: Microsoft Foundry is new, the documentation extensive, the configuration options complex. Starting without experience means weeks of trial and error — and an environment without clear structure at the end.
Traditional consulting for an AI platform setup? Quickly five figures. And the knowledge leaves with the consultant.
ACTIVITIES IN DETAIL
DELIVERABLES
Validate Azure subscription and create a dedicated resource group for AI workloads
Create Microsoft Foundry resource (SKU S0, EU region Germany West Central) with custom subdomain
Set up Foundry project and configure RBAC roles — least privilege based on team structure
Ensure EU data residency: deployment type Data Zone Standard, region Germany West Central
Set up cost management: Azure Budgets, cost alerts, token consumption monitoring
Deploy first model (GPT-4.1-mini) and enable Playground access for business users
Document governance baseline: naming conventions, access policies, data residency rules
Validate Azure subscription and create a dedicated resource group for AI workloads
Create Microsoft Foundry resource (SKU S0, EU region Germany West Central) with custom subdomain
Set up Foundry project and configure RBAC roles — least privilege based on team structure
Ensure EU data residency: deployment type Data Zone Standard, region Germany West Central
Set up cost management: Azure Budgets, cost alerts, token consumption monitoring
Deploy first model (GPT-4.1-mini) and enable Playground access for business users
Document governance baseline: naming conventions, access policies, data residency rules
Production-Ready Foundry Environment: Foundry resource and project in Germany West Central — EU data residency configured and validated
RBAC Concept: Documented role model (Account Owner, Project Manager, User) — implemented and tested
Cost Management Setup: Azure Budgets, cost alerts, and reporting dashboard — active from day one
First Model Deployment: GPT-4.1-mini ready in Playground, access enabled for defined user group
Governance Baseline Document: Naming conventions, access policies, data residency rules, recommendations for next steps
Complete Project Documentation: All configuration decisions captured without gaps, audit-ready
3 steps. From start to finished project
How a typical Microsoft project runs with DAMALO
STEP 1
Choose a blueprint and analyze your environment
Select a proven blueprint. AI agents pull your licenses, current config, and compliance needs into the plan. No generic advice.
STEP 2
Receive your plan and start implementation
Review the plan. AI agents draft architecture, sequence tasks, and map dependencies to Microsoft best practices. Tailored to your tenant.
STEP 3
Guided implementation through to completion
Execute step by step. AI agents provide PowerShell scripts, admin center deep-links, and walkthroughs. Every change auto-documented.
The result: A completed Microsoft project in 1-2 weeks. Documented. Audit-ready. Understood by your team. Adjustable at any time. No change requests. No follow-up engagements.
Next steps after Microsoft Foundry Platform Setup
A cleanly configured tenant is the foundation. These blueprints build directly on it
