Azure landing zones
Subscriptions, networking and identity designed properly from day one with Entra ID, Key Vault, Private Link and policy as code.
Enterprise Platform Engineering & Azure Cloud Architecture
A cloud platform where the secure way is also the fast way. We design and build Azure foundations (networking, identity, infrastructure as code, deployment pipelines and monitoring) so your teams ship AI features in days, not quarters, and every pound of cloud spend is accounted for.
The problem
Why this goes wrong without the right expertise.
What we see in the field
AI exposes every weakness in a cloud platform. Hand-built environments, shared passwords and missing monitoring turn one AI feature into weeks of firefighting and an invoice nobody can explain.
What we deliver
Concrete, merged, documented.
Everything lands in your repositories and your cloud subscriptions, with the runbooks to own it.
Infrastructure as code
Bicep, Terraform or OpenTofu modules with environment promotion, drift detection and on-demand preview environments.
Deployment pipelines
Azure DevOps or GitHub Actions templates with security scanning, approvals and AI quality checks built in.
Runtime architecture
Container Apps or AKS behind Front Door and WAF, including GPU capacity for private models, sized for speed and cost.
Monitoring and FinOps
OpenTelemetry, Application Insights, service targets and cost dashboards that show spend by team, product and customer.
Cloud migration
Moving existing systems to Azure in stages, improving them on the way rather than copying old problems across.
Typical stack
- Azure Container Apps
- AKS
- Azure Front Door
- Entra ID
- Bicep / Terraform / OpenTofu
- Azure DevOps
- GitHub Actions
Proof, not slides
Where we have already done this.
FAQ Hub runs on this pattern in production: ASP.NET Core on Azure Container Apps behind Front Door and WAF, Azure SQL and Blob Storage, Azure AI services, and Azure Pipelines from commit to release.
Related insights
Go deeper.
A Paved Road for AI Workloads on Azure
The Azure platform defaults we set before a team ships its first AI feature: managed identity, private model endpoints, an AI gateway, tracing, cost attribution and eval gates.
Read the article →Other services
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AI that works inside your rules, not around them.
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Software that survives an audit as well as a traffic spike.
Explore →SaaS Platform Modernisation
From a separate copy per customer to one platform that serves them all.
Explore →Talk to an expert, not a sales team.
Tell us about your stack, your constraints and where AI needs to fit. A founder replies within one working day.