Cloud and infrastructure
Microsoft Azure
Chosen for the workload.
Connect enterprise applications, data and AI on Azure, with architecture shaped around your Microsoft environment, workload needs and operating constraints.
The starting point
What needs to change.
Cloud selection must reflect workload fit, data location, integration needs and whole-life operating cost.
A platform is only useful when access, delivery and operational ownership are designed together.
What we deliver
From opportunity to working systems.
Enterprise application integration
Connect existing applications and business systems through documented interfaces and a staged migration approach.
Data and AI services
Build data and AI workflows around approved sources, access controls and measurable task outcomes.
Identity and operations
Align identity, environment management and monitoring with the teams responsible for running the workload.
Usage metering and allocation
Meter Azure service consumption in workload-relevant units. Allocate usage to customers, projects or teams and connect budgets with clear cost reporting.
One Emerge commercial model
Consume selected Azure services through Emerge, with usage-based customer billing, chargeback and service operations connected to the same consumption records.
Our approach
A clear path into delivery.
Start with the business problem. Make each stage useful, reviewable and owned.
- 01
Assess workload requirements, existing investments and the available regional service options.
- 02
Compare the architecture with alternatives across AWS, Azure, Google Cloud and Cloudflare.
- 03
Build, validate and hand over a documented increment with monitoring and release controls.
Explore the detail
Related work and resources.
See the approach in context. Client engagement stories are anonymised; related examples may come from other sectors or platforms.
Your next move
Bring us the business problem.
We will help you define a useful starting point, the expertise you need and a practical path to delivery.