Four consulting practices, backed by hands-on professional services — all grounded in the same discipline.
Design, assessment, and modernization across private and public cloud — with deep specialization in IT technologies, and defensible decisions about licensing, hardware refresh, and platform direction.
Evaluate your current estate and plan upgrade and modernization paths, including VMware Cloud Foundation adoption. Estate data is gathered with vHyperTrace, our own discovery platform, so the assessment rests on what is actually running rather than on last year's documentation.
Which workloads belong in public cloud, which do not, and what each will cost once it gets there. We model placement decisions with our own analysis tooling instead of generic calculators.
Migration is where plans meet reality. Dependency mapping and wave planning come straight out of vHyperTrace, so tightly-coupled systems move together and cutovers are scheduled against evidence.
Everything above can be delivered as well as advised. Our professional services engineers build what the consulting practice designs — from reference architecture through to production handover, using the same methodology that produced the assessment.
Private cloud and virtualization platform builds, cloud infrastructure deployment, and networking and storage integration.
Implementation done right the first time — with automated build validation and as-built documentation generated from our own tooling.
Health assessment, performance and capacity tuning, and operational process improvement — automated and repeatable, so improvement can be measured.
Adopting AI well depends less on the technology than on the clarity behind it. We help organizations answer three questions before committing investment: why this, how it will work, and what it will genuinely require.
Where AI genuinely creates value in your business — and where it does not. Our own readiness tooling profiles your data estate and infrastructure so the roadmap is grounded in fact, not in vendor marketing.
From selecting the right approach — build, buy, or integrate — to standing up the supporting infrastructure for AI in production, responsibly.
AI initiatives succeed when your people understand them. We build the literacy and operating practices your teams need to own these capabilities after we leave.
You cannot improve what you have not measured. We build a structured picture of your IT landscape — systems, workloads, costs, dependencies, and risks — and map it against what your business actually needs from it. The result is a working profile your leadership can use, not a shelf document.
A complete inventory of systems, applications, and workloads, collected through our own automated discovery tooling rather than questionnaires — so nothing depends on who remembered to fill in the spreadsheet.
What each system costs to run, what it depends on, and what breaks if it fails. Dependency data is captured automatically, which is how relationships nobody documented tend to surface.
The profile turned into decisions: what to invest in, what to consolidate, and what no longer earns its keep — each recommendation traceable back to the evidence behind it.
Digital transformation becomes challenging when it is treated as a technology project. We treat it as a business change program with a technology backbone — sequenced, measurable, and grounded in your organization's real starting point.
Where you are going and why, defined against the evidence from profiling and discovery. Our tooling carries that evidence straight into the target-state model instead of it being re-keyed into slides.
Choosing the platforms and partners that fit your estate, your team, and your constraints — with selection criteria written down and scored, not decided in a room.
Change delivered in stages that each stand on their own. We use our own planning tooling to sequence work, expose the critical path, and identify the manual processes worth automating first.