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A cloud platform sized for what you actually run

We design cloud architecture, move workloads onto it in reversible steps, and keep the result patched, backed up and financially sane. This is the platform layer — the accounts, networks, data stores and capacity your applications sit on.

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A senior engineer replies within 24 hours — not a sales rep.

Where cloud platforms tend to go wrong

The move happened and the bill went up

Servers were re-hosted one-for-one, sized against what the physical boxes had rather than what the workloads use. Nothing was re-architected, so you now pay hourly for idle capacity you previously owned outright, plus storage tiers and egress charges that had no equivalent in the data centre.

No two environments are quite the same

Staging was built first, production was built later with fixes applied along the way, and a third account exists because a project needed isolation once. A change that works in one place fails in another, and nobody can say with confidence what differs — which makes testing anything infrastructure-related close to meaningless.

The recovery plan has never been run

Backups are configured and nobody has restored one. There is a documented recovery objective in a policy somewhere, written by someone who did not measure it. The first genuine test will be during an outage, with the business waiting, which is the worst possible time to discover the snapshots do not include the volume that mattered.

Access grew by accident

Permissions were granted broadly to unblock someone at speed and never narrowed. Contractors from a finished project still have keys. There is a root account whose credentials live in a password manager two people can open, and the network was flat from the start because segmenting it later looked like effort.

How we build and run cloud platforms

The architecture decisions that matter get made early and are expensive to revisit — account structure, network topology, data residency, how state is stored. We settle those deliberately, then move workloads in slices small enough to reverse.

Landing zone first, workloads second

Account and subscription structure, network segmentation, identity federation, logging and guardrails go in before anything of consequence lands on the platform. Retrofitting an account boundary around a running production system is one of the more miserable pieces of work in this field, and it is entirely avoidable.

Migration assessed workload by workload

Each application gets a decision: re-host as-is, adjust it to use managed services, rebuild it, or leave it where it is. Some workloads have no business case for moving and we will say so. The plan sequences the ones that do, starting with something whose failure would be recoverable.

Resilience proven by testing, not by configuration

We set recovery objectives with the business, design backup and failover to meet them, and then actually restore into a clean environment and time it. If the measured result misses the target, the design changes. A recovery capability you have not exercised is an assumption.

Spend attributed before it is optimised

Tagging and account structure that let you see cost by team, environment and product — because you cannot make a sensible rightsizing decision about a resource whose owner is unknown. Then the ordinary work: idle cleanup, storage lifecycle rules, instance families matched to actual utilisation, and commitment purchasing once the baseline is stable.

What this covers

Pick the piece you need, or bring us the problem and we'll tell you which applies.

Cloud & DevOps

Where platform work and delivery automation are bought together — infrastructure as code, pipelines and monitoring alongside the cloud footprint itself. Most engagements that start as a migration end up touching this, because moving to cloud without automating what runs on it just relocates the manual work. There is a dedicated page covering this combined scope in detail.

Combined platform build and delivery automation under one engagement and one plan
Infrastructure as code covering the cloud footprint and the workloads deployed onto it
Pipelines, monitoring and cost visibility introduced alongside the migration rather than after it
Covered in full on the Cloud & DevOps page, including our approach to deployment frequency and lead time

Cloud Architecture & Migration

Designing the target platform and getting your workloads onto it without a weekend of held breath. The architecture work covers account structure, networking, identity, data placement and the resilience posture; the migration work covers sequencing, cutover and rollback for each application. For teams leaving a data centre, consolidating after an acquisition, or moving between providers.

Multi-account landing zone with network segmentation, identity federation and centralised logging
Per-application assessment recommending re-host, re-platform, rebuild or retain, with the reasoning written down
Database and large dataset migration using replication and a short cutover window rather than an offline copy
Documented rollback position at every slice, so a bad move costs hours instead of a weekend

Managed Cloud Infrastructure

Running the platform day to day once it exists: patching, backups, capacity, access reviews and the cost conversation nobody gets round to. Most useful for teams whose developers are currently absorbing this work between features, or who need continuity when the one person who understood the infrastructure moves on.

Patching and version upgrades on a scheduled cycle, including managed database engine versions
Backup verification with periodic restore tests, timed and reported rather than assumed
Quarterly access review and key rotation, with dormant credentials removed rather than left in place
Monthly cost review naming what changed, what it cost and what we recommend doing about it

The stack we build on

Chosen to fit the problem — not because it's what we used last time.

Cloud providers

Amazon Web Services
Microsoft Azure
Google Cloud Platform
DigitalOcean
Cloudflare

Platform & networking

Amazon VPC
Azure Virtual Network
AWS Transit Gateway
Load balancers & CDN
AWS IAM
Microsoft Entra ID
HashiCorp Vault

Compute, data & storage

Amazon EC2
Azure Virtual Machines
Amazon RDS
Azure SQL
Amazon S3
Kubernetes
Serverless functions

Operations & cost

Terraform
Ansible
AWS CloudWatch
Azure Monitor
Prometheus
Grafana
AWS Cost Explorer

How we'll work together

Every stage ends with something in your hands — not a status update.

01
Estate assessment
We inventory what you run, how the pieces depend on each other, and what each one needs in terms of availability, data residency and compliance. Dependency mapping is where the surprises live — the reporting job that quietly reads a production database is always found here rather than in the documentation.
You get: A workload inventory with dependency map, a disposition recommendation per application, and an indicative running cost for the target platform.
02
Platform design and landing zone build
Account structure, network layout, identity and guardrails designed and then stood up as code. Your team reviews the design before it is built and the pull requests as it is, so the platform is not a black box handed over at the end.
You get: An architecture decision record, a network and account diagram, and a working landing zone defined in Terraform in your repositories.
03
Migrate in slices
Workloads move in the agreed sequence, each with its own cutover plan and rollback position. Data-heavy systems run replicated in parallel so the cutover itself is short, and we verify against the old system before the old one is switched off.
You get: Each workload live on the new platform with a cutover record, verification results and the rollback path documented.
04
Prove resilience, then run or hand over
We test restores and failover against the agreed objectives, tune what misses, and set up the operational cadence — patch windows, access reviews, cost reporting. From there your team takes it on, or we run it under a managed arrangement.
You get: Timed restore and failover test results, an operations runbook, cost dashboards, and either a handover session or a managed service schedule.

Where we've applied this

Healthcare

Data residency and encryption requirements designed into the account and network layout, with audit logging retained on the terms a compliance review will ask about.

Logistics

Platforms sized for demand that follows a shipping calendar, using autoscaling and queue-backed processing so peak weeks do not require peak-sized infrastructure all year.

Retail

Capacity planning around trading peaks, edge caching for storefront performance, and payment workloads isolated in their own account boundary.

Finance

Segregated environments, least-privilege access with periodic review, and immutable log retention that satisfies both internal audit and the regulator.

Manufacturing

Hybrid platforms where plant systems stay local and analytics, integration and backup run in cloud, connected over private links rather than the public internet.

Education

Term-cycle demand where enrolment and assessment periods dominate, so capacity and licensing follow the academic calendar instead of a flat annual commitment.

Clients we've built for

Real products, in production, with real users on them.

OrbiSim

View project

National Industries Company

View project

evera

View project

Science and Mind

View project

Questions buyers ask us

Which provider should we be on?

Usually the one your team already knows, unless a specific requirement overrides that. Azure is the pragmatic default where identity, licensing and BI already sit in the Microsoft estate. AWS has the broadest managed service catalogue. GCP is strong where data and analytics workloads dominate. The difference between providers matters far less to your outcome than the quality of the architecture you build on whichever one you pick.

How is this different from your DevOps work?

This page is about the platform: accounts, networks, data stores, capacity and how it is operated. DevOps is about the path a change takes from a developer's branch to production — pipelines, automated testing, release safety. They meet, and plenty of clients buy both, but they solve different problems. If your servers are fine and releases are the pain, start on the DevOps side.

Can you migrate without downtime?

For most workloads, close to none — we replicate data ahead of time and keep the cutover to a short switch of traffic, with the old system standing by. Some legacy applications with stateful in-process sessions or a single-writer database genuinely need a window, and where that is the case we say so during assessment and plan it for a quiet period rather than promising otherwise.

What drives the cost of a migration?

The number of workloads, how much each one needs changing rather than simply moving, and how tangled the dependencies are. Data volume affects the migration mechanics more than the price. Compliance obligations add design and evidence work. We scope this properly in a paid assessment rather than quoting an estate we have not looked inside.

Do you take over an environment somebody else built?

Regularly. We start by reading what exists — infrastructure, access, backups, invoices — and give you a written account of the risks and what they would cost to fix, ranked. Nothing gets rebuilt for the sake of it. Where the previous setup is sound but undocumented, the first piece of work is usually bringing it under code and version control so it can be changed safely.

If you manage our infrastructure, what do we still control?

All of it. The accounts, the code and the data are yours throughout, and your team keeps administrative access — we work inside your tenancy rather than a reseller arrangement. Changes come through pull requests you can review, and there is no proprietary agent or dashboard in the path. Ending a managed arrangement means the handover of a runbook, not an extraction project.

Tell us what your platform looks like today

Send us a short description of what you run, where it runs and what worries you about it. A senior cloud engineer replies within one business day with an honest read on what is worth changing and what is fine as it stands.

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