Azure that fits the Microsoft estate you already run.
Most Azure work is not greenfield. It sits beside Entra ID, Microsoft 365, an on-premises estate and licensing decisions made years ago. We design for that reality rather than for the reference architecture in the slide deck.
Identity is where Azure projects quietly go wrong.
On Azure, identity is not a component — it is the substrate. Entra ID already governs who your staff are, what they can open and which device they are on. A workload designed without that in view produces a second identity model that has to be reconciled forever afterwards, usually by hand.
A parallel identity model
Application roles that do not map to groups anyone administers, so joiners and leavers are handled twice and one of the two is forgotten.
Subscriptions as a filing cabinet
Subscriptions created per project with no management group structure, so policy, budget and compliance have nowhere to attach.
Licensing driving architecture
A design chosen because of what was already paid for, without anyone modelling what it will cost to run at the volume actually expected.
The Azure work that pays for itself.
Landing zone & governance
Management groups, subscription design, Azure Policy, budgets and a baseline that new subscriptions inherit instead of being configured by memory.
Entra ID & access
Conditional access, managed identities, privileged access review and application roles that map to groups your IT team already maintains.
AKS, App Service & Functions
The right compute for the workload, with ingress, scaling, secrets and deployment pipelines built once and reused rather than rediscovered per team.
Data & integration
Data Factory, Synapse or Fabric where they earn their place, Service Bus and Event Grid for messaging, and integration with the line-of-business systems that will outlive the project.
Integration workAzure OpenAI
Model access inside your own tenant and region, with private networking, content filtering, cost attribution and evaluation, rather than keys handed to individual teams.
AI engineeringCost & commitment modelling
Reservations, savings plans, hybrid benefit and right-sizing modelled against actual usage, with showback so each team can see what it spends.
The same sequence as any cloud engagement, with identity first.
Assess
Tenant and subscription structure, identity and access, network topology, cost, and the delivery pipeline as it exists rather than as documented.
Foundation
Management groups, policy, networking and identity patterns, deployed as infrastructure code so the next subscription is a template rather than a project.
Workloads
Move or build the applications themselves, in reviewable increments, with your engineers in the pull requests.
Operate
Monitoring, cost review, patching and a documented handover to a named owner on your side.
Multi-cloud is a consequence, not a strategy.
Many of the organisations we work with are on Azure for the corporate estate and on AWS for a product, usually for reasons that made sense at the time. That is workable if identity, networking and deployment are designed deliberately across both. It is expensive when each cloud is treated as a separate country.
Questions we get asked
Do you work with our existing Microsoft partner?▼
Yes. Licensing and commercial arrangements usually stay exactly where they are. We work on architecture and delivery, and we are happy to be the party that asks the awkward technical questions in a joint review.
Can Azure OpenAI keep our data inside the EU?▼
Deployments can be pinned to European regions and run over private networking inside your own tenant, and we design that way by default for Irish and European clients. The exact regional availability of a given model changes over time, so we confirm it against current Microsoft documentation for your specific case rather than assuming.
We are half on-premises. Is that a problem?▼
No, and it is the common case. Hybrid identity, network connectivity and a clear rule about which systems stay put are part of the design. Not everything should move, and a plan that pretends otherwise fails in year two.
AKS or App Service?▼
App Service or Container Apps for most workloads, because the operational cost is far lower. AKS when you genuinely need the control, and with an honest conversation first about who will run it at three in the morning.
Do you help with Microsoft Fabric?▼
Where it fits. Fabric is a strong answer for some analytical estates and an expensive answer for others. We would rather assess the workload than lead with the product.
One free hour. No pitch, no obligation.
Bring the problem you are stuck on — an integration that keeps breaking, a cloud bill nobody can explain, an AI project that is all demo and no product, or a platform you are about to invest in. You will leave with a straight answer and a written summary, whether or not you ever work with us.
- Architecture and integration review
- AI feasibility — what will actually work, and what will not
- AWS, Azure and Google Cloud cost and design
- Business process audit and ISO readiness
- Technical due diligence before you invest or acquire