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Cloud foundation
Landing zones, governance, hub and spoke networking. Everything else runs inside this boundary.
landing_zone · policy · hub_spoke
We are senior Azure architects. We design the landing zone, build the network, then put AI on top of it. The people who scope your project are the people who build it.
landing_zone
migration_wave
avd / avs
ai_workload
Each segment below is work we have delivered ourselves. The silver core is the architecture that holds it together. AI sits inside the same structure, not bolted on the side.
Landing zones, governance, hub and spoke networking. Everything else runs inside this boundary.
landing_zone · policy · hub_spokeData center moves planned and cut over with control. Wave plans that respect the business calendar.
wave_plan · cutoverAzure Virtual Desktop and Azure VMware Solution. Two ways to run a managed desktop estate. We know which one fits.
avd · avsWe define the use case, design the architecture, then build it on the networking, identity and governance already in place.
llm_orchestration · private_aiYou brief the engineers directly, not an account manager. Nothing is lost between the people who plan the work and the people who do it.
Networking, identity and governance are designed in from day one. The AI workload passes security review instead of stalling there.
Discovery, design and implementation under one owner. No gaps between the plan and the build, because the same team carries both.
A practical course for engineers who run production Azure estates. The same senior architects who build them teach it. Every module ends in a lab on a real landing zone, not a slide deck.
for: sysadmins · platform engineers · ops teams moving to AzureEvery engagement runs through the same three phases. Each one ends with something concrete you can act on.
Requirements, current state, constraints. We map subscriptions, policy, and the AI pilots already running inside the business.
Target architecture: landing zone, hub and spoke network, governance, and the AI workload drawn as one system.
We build it, test it, deploy it and watch it in production. Then we hand it over with the documentation to run it.
Before we write a line of Terraform, you see the system as a diagram. What moves. What connects. Where the AI workload sits. Gold marks the AI component. Everything else is the foundation underneath.
We build the AI business case before any deployment. Each use case has its benefit defined up front, and an ROI agreed before work starts. You know it is worth doing. You know when it paid off.
Facilitated sessions to find, score and rank use cases by value, feasibility and risk. We will tell you which one is worth funding, and which to drop.
For the use case you pick, we define the benefit and set the baseline it must improve on. We agree the ROI target that measures success before anything is deployed.
Only once the numbers work. A target design covering model deployment, data access, private networking, governance and cost, scoped to hit the agreed ROI.
Tell us what is driving your timeline: a data center exit, a contract ending, an AI initiative. We will look at the architecture and tell you honestly whether it is ready.