Cloud architecture sized for today, built to grow
Most cloud work needs someone who understands what you are building and can set it up without unnecessary complexity. We architect and manage infrastructure on Azure, GCP or AWS to support your data and AI workloads, sized for today, built to grow, with cost discipline built in.
Right-size your cloudWho it's for
Teams standing up or cleaning up cloud infrastructure for data and AI workloads who want it right-sized and cost-controlled, not over-engineered, and not a surprise bill.
What we deliver
Infrastructure designed around your workload, with FinOps discipline from the first day.
Workload-fit architecture
Infrastructure designed around what you are actually building (data pipelines, analytics and AI inference), without unnecessary complexity.
Multi-cloud capability
Azure, GCP or AWS, chosen on your constraints and existing footprint rather than our preference.
Cost optimisation built in
FinOps discipline from day one (right-sizing, spend visibility and waste removal), with no separate engagement needed.
Infrastructure for AI
The compute, storage and networking that data and AI workloads actually need, including for self-hosted and sovereign models.
Managed operation
We can run it for you, with monitoring and observability, or set it up and hand it over.
Growth-ready foundations
Built to scale with your data, so today's setup doesn't become next year's rebuild.
How it works
-
Understand the workload
We start from what you are building and its real constraints, not a reference architecture.
-
Design right-sized
Architecture sized for today's load with clear paths to scale, and cost modelled up front.
-
Build with cost discipline
We stand it up with FinOps controls (spend visibility and right-sizing) from the first day.
-
Operate or hand over
We manage it with monitoring, or document and hand it over to your team.
-
Optimise continuously
Ongoing right-sizing and waste removal keep cost in check as you grow.
Proof
Azure environments optimised. Less waste, fewer incidents, same delivery capacity.
Cost discipline is built into the engagement, not sold separately: on one Azure environment it cut spend by 25% with no loss of delivery capacity.
Questions we get asked
Which cloud should we use?
The one that fits your constraints, existing footprint and workload, not our favourite. We work across Azure, GCP and AWS and will tell you honestly which suits you.
How do you keep cloud costs down?
FinOps discipline is built into the engagement, not sold separately: right-sizing, spend visibility and waste removal from day one. On one Azure environment this cut costs by 25% with no loss of delivery capacity.
Can you support self-hosted AI?
Yes. We architect the compute, storage and networking that self-hosted and sovereign models need, so you can run AI in your own environment.
Do you manage it or just set it up?
Either. We can run it for you with monitoring and observability, or stand it up and hand over a documented setup to your team.
Will this scale?
We size for today's load but design for growth, so the foundation scales with your data instead of forcing a rebuild later.
Related
Paying more for your cloud than you should?
Let's review your setup