Cloud Strategy & Migration
Migration roadmaps aligned to a specific business outcome – not a generic lift-and-shift. AI-assisted dependency mapping cuts discovery time before migration even starts.
AI and Cloud consulting as one senior-led practice – strategy, migration, modernisation, and Platform Engineering across AWS, Azure, and GCP. Production-grade cloud architecture that holds up under real-world demand – and doesn't quietly drain your budget while doing it.
Most consultancies sell AI and Cloud as separate engagements, and the seam between them is where programmes leak value. We run them as one practice: secure, production-grade cloud architecture for modern applications and AI workloads – covering cloud strategy, migration, modernisation, and Platform Engineering across AWS, Azure, and GCP. AI agents sit inside the pipeline: generating and reviewing IaC, forecasting spend, and catching drift before it becomes an outage. Cloud transformation without FinOps discipline turns into the most expensive infrastructure you've ever run – so we build in the governance from day one.
Five capability areas, each governed by senior Cloud practitioners and tied to a clear business outcome. No capability exists for its own sake – each one serves your programme's specific objective.
Migration roadmaps aligned to a specific business outcome – not a generic lift-and-shift. AI-assisted dependency mapping cuts discovery time before migration even starts.
Interoperable architectures across Kubernetes and OpenShift – portability without vendor lock-in and without the operational tax that usually follows.
AI agents generate and review infrastructure-as-code, enforce policy-as-code, and catch configuration drift before it ships – compressing deployment timelines without compromising integrity.
Zero-trust architecture and encryption enforced from the start – not retrofitted after an audit flags a gap. AI-assisted control validation runs continuously, not annually.
Spend governance through FinOps practices and AI-driven cost forecasting – giving your CFO visibility on the bill before it arrives, not after.
The most common failure we're asked to fix is AI projects stalling after cloud migration succeeded. The programme closes, the steering group disbands, and ownership of access, cost, and data contracts scatters across teams that were never asked to hold it. Every AI initiative then queues behind a question with no named answer, and six months later the board pack blames data readiness. The fix is structural: a standing platform team, named before cutover, with the authority to answer those questions inside a week. We've written up the argument – and the two that sit either side of it – below.
The ownership argument in full: why a permanent platform team keeps an AI programme moving after cutover, and why ownership devolved to product teams fails more often than it works.
Read the articleDay rate or fixed price – what each commercial model does to risk, why procurement keeps picking the wrong one, and which one we'll argue for on your programme.
Read the articleSteering committees that record decisions versus forums that change them – and the single test that tells you which one is running your transformation.
Read the articleA selection of cloud programmes our clients have entrusted to us – from global infrastructure migrations to next-generation DevOps transformations.
A selection of the senior Cloud practitioners who lead and deliver our client engagements. The people you meet in the discovery are the people who deliver.
Meet just some of the Vertex Agility Cloud team.
Common questions we get from senior technology leaders evaluating this work. Direct answers, no hedging. Open one to read in full.
One practice covering cloud strategy, migration, modernisation, and Platform Engineering across AWS, Azure, and GCP – with AI delivery built into each of them rather than sold as a separate engagement. AI agents work inside the pipeline generating and reviewing IaC, forecasting spend, and validating controls, and the same senior team designs both the landing zone and the AI workloads that will run on it. Platform decisions and AI decisions get made together, so they never drift apart.
AI agents run inside the engineering pipeline. They draft Terraform and Bicep from architectural intent, review it against your security and FinOps policies, and catch configuration drift before it ships to production. The architect still makes the calls. The agents handle the repetitive translation work that used to consume the most senior time on the team. Faster, more consistent infrastructure delivery on the same architectural standard.
Because the migration programme was quietly the operating model, and it ended. While it ran, access requests, cost allocation, and data contracts all had a named owner with the authority to decide. When it closed, they passed to nobody. Every AI initiative then queues behind an ownership question – who grants access, who pays for the training run, who fixes the broken data contract – and six months later the board pack blames data readiness. The failure is structural, so the fix has to be structural too.
A standing platform team, named before cutover rather than worked out afterwards. It owns access, spend, and the data contracts every AI workload depends on, and it answers requests in days rather than quarters. One client’s platform team saves 6,000 engineering days a year from manual cloud operations – a figure that’s only achievable when ownership is permanent. Rotate it through product teams and the automation rots.
Cost is a design constraint, treated with the same rigour as availability or security. AI-assisted cost forecasting on every architectural decision, tagging discipline enforced through policy-as-code, and FinOps dashboards comparing actual against forecast on a daily cadence. Cost discipline written into the architecture survives the migration. Anything retrofitted afterwards usually drifts within a quarter.
Fixed price wherever scope can be defined – a migration wave, a landing zone, a modernisation tranche – because a fixed price forces our estimate to absorb the risk instead of transferring it to you. Day rate has a legitimate place in early discovery and in co-delivery inside your own team, where the scope genuinely can’t be fixed yet. What we won’t do is lead with a day rate because it’s the easiest number to put in a comparison table. How you buy shapes what you get.
Yes. Senior practitioners certified across all three hyperscalers, with strategic partnerships at Microsoft, AWS, and Google. Cloud choice is workload-driven, never vendor-driven. Multi-cloud is the right answer for some workloads. For others it’s expensive complexity dressed up as a strategy – we’ll tell you which one yours is.
Zero-trust by default. Identity-based access on every service, encryption in transit and at rest, no implicit network trust anywhere in the estate. AI-assisted security validation runs continuously, catching misconfigurations and drift before they become incidents. Security sits in the architecture from the start. Adding it later costs more and rarely produces the same posture.
Yes. We’ve delivered against EU data sovereignty rules, UK Public Sector residency requirements, and regulated financial-services constraints. Architectures get designed around the specific regulatory shape of the workload – provider region, encryption controls, audit posture – aligned to the rules that actually apply to the data. Defaulting to whatever the host department already uses is how those programmes get expensive to unwind later.
Four areas, one standard. Each specialism is led by senior practitioners with deep domain expertise – explore the others.
Most AI deployments are performance theatre. Our generative AI consulting practice integrates AI – from workflow automation and intelligent decision-making to custom LLMs and agentic systems – where it demonstrably pays back, and we'll tell you directly when it won't.
Explore AI ConsultancyMost organisations have more data than they can act on. We build AI-ready data platforms, AI-augmented pipelines, and production ML foundations that close the gap between data collected and decisions made – with governance and lineage architected in from the start.
Explore Data ConsultancyEngineering without architectural governance is expensive rework. We deliver full-stack software engineering, microservices, and software modernisation through AI-augmented pipelines – compressing roadmap-to-production timelines without trading away quality.
Explore Software ConsultancySend us a brief and we'll come back within one working day with a senior Cloud consultant – and a clear sense of how to start.