- Environments behave differently and setup is done by hand
- The cloud bill keeps growing with no clarity on what each service returns
- Single-region infrastructure is a business continuity risk
04
Cloud & Platform
Cloud & Platform Engineering
On AWS and Azure, we build the platform your application runs on so that it is repeatable, secure and predictable in cost.
Scope
What we take on
We weigh infrastructure across cost, speed and resilience together. We make it visible which decision lands on the bill and which lands on performance, and we break migration and modernisation into steps that never stop daily operations. We work on both AWS and Azure; your workload and existing enterprise agreements decide which.
Workstreams
- Infrastructure on AWS and Azure that scales with load and costs nothing when idle
- A platform layer where every service is managed from one place
- Staging that behaves the same way as production
- Business continuing when a single region goes down
- Clear visibility into which workload drives the cloud bill
When you need this
If these signs
look familiar.
Where we applied it
Serverless AWS architecture for the NEXT AI platform; multi-node and multi-region infrastructure at MultiVM; at Obilet the same workload is now served at roughly 20% lower cloud cost.
Results in production
Which platforms
have we applied this on?
OCPPcharge point control from one place
EV Charging Management (CSMS)
Charging infrastructure spread across the field is managed from a single centre.
As Ford’s charging estate spread across the field, monitoring station status and sending commands turned into a load the operation could not scale. We brought charge point control and command management over OCPP, telemetry-based fault monitoring and charging session tracking together on a single platform, and built the service infrastructure for high availability. Field operations now monitor and manage the entire station fleet from one place.
Platform →
ServerlessLLM + vector search on AWS
Customer Intelligence (AI)
Scattered customer data became actionable insight on a serverless AWS architecture.
NEXT AI’s customer data was spread across several sources, and because every analysis required manual interpretation, capacity was tied directly to headcount. We built the collection and normalisation flows, the LLM-based classification and the vector-search segmentation on a serverless AWS architecture, taking on the solution architect and DevOps roles. The platform now turns raw data straight into insight teams can act on, while infrastructure cost scales in proportion to usage.
Platform →Related platforms
Which platforms
does this discipline come into?
Let’s work together
Let’s look at a need you have around cloud & platform engineering.
Tell us where you are today and which constraints matter most; we will define a clear starting point together.