Cloud strategy and business case
Align cloud decisions with business objectives, costs and risk.
We help you decide what to move, what to change and what to leave, then design an AWS architecture that is secure, resilient and ready for AI.
Workloads move one by one with no agreed target, standards or ownership.
Environments built under time pressure carry risks that only appear in production.
Without a clear structure, permissions, networks and spending become hard to control.
AI workloads need data, security and platform capabilities that many environments lack.
Align cloud decisions with business objectives, costs and risk.
A secure multi-account foundation with identity, networking, logging and guardrails.
Proven patterns for your workloads, adapted to your requirements.
Structured reviews of existing workloads against AWS best practice, with a prioritised improvement plan.
Define roles, responsibilities and ways of working between your teams and ours.
Prepare data, security and platform capabilities for AI workloads.

Understand your applications, data, constraints and goals.
Agree principles, standards and the architecture to aim for.
Specify the foundation and reference architectures in detail.
Validate designs and existing workloads against the Well-Architected Framework.
Sequence the work into stages that deliver value early.
The AWS Well-Architected Framework reviews workloads across six pillars: operational excellence, security, reliability, performance efficiency, cost optimisation and sustainability.
Identity, encryption, logging and network boundaries are part of the foundation, not an add-on.
Policies prevent risky configurations while letting teams move quickly.
Every account, workload and cost has a named owner.
Architecture choices and their reasons are documented for future teams.
Let's identify the opportunity and determine the right path to a working solution.
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