IT Consulting Services

Cloud decisions are hard to reverse and easy to get wrong in ways that only surface on the invoice eighteen months later. We start from your actual workloads rather than a vendor comparison chart: what runs where today, what it costs, what the compliance constraints are, and which systems genuinely need to move versus which are fine where they are. The output is a migration plan sequenced by risk and business value, with a cost model that accounts for egress, reserved capacity, and the engineering time the migration itself consumes. Where staying put is the right answer, we say so — a lift-and-shift that saves nothing is worse than doing nothing.

• Workload inventory and dependency mapping
• Provider comparison against your specific requirements
• Landing zone and network architecture design
• Migration waves sequenced by risk
• Three-year total cost of ownership model

Systems accumulate decisions. Most were reasonable when made, some have quietly become load-bearing problems, and the team closest to the code is often the least able to see which is which. We read the codebase, trace the critical paths, review the data model and deployment topology, and interview the engineers who maintain it. What you get back is a prioritised list: what will fail first under growth, what is merely ugly but harmless, and what carries genuine risk. We are explicit about the difference, because a review that flags everything is as useless as one that flags nothing.

• Codebase and data model review
• Scalability and failure-mode analysis
• Technical debt inventory, ranked by risk
• Security and dependency audit
• Prioritised remediation sequence

Most organisations asking about AI have a data problem first. Before a model is worth discussing, the underlying data has to be accessible, reasonably clean, and legally usable for the purpose intended — and often one of those three is missing. We assess what you actually hold, what state it is in, and which of your candidate use cases survive contact with it. For the ones that do, we specify the platform architecture and a realistic path to production. For the ones that do not, we say why, which usually saves more money than the ones we greenlight.

• Data inventory, quality, and lineage assessment
• Platform and pipeline architecture
• Use-case scoring against feasibility and value
• Build-versus-API evaluation for model choices
• Governance and data-handling requirements

Compliance work goes wrong when it becomes a paperwork exercise disconnected from how the system actually behaves. We start with a threat model specific to your business — what an attacker would want, where it lives, and what currently stands in the way — then map that against whichever framework your customers or regulators require. The remediation plan is sequenced so the highest-risk gaps close first, not so the easiest checkboxes tick first. Where a control is genuinely not applicable to your architecture, we document why rather than implementing it theatrically.

• Threat model and risk register
• Framework gap analysis against your target standard
• Remediation roadmap ordered by risk reduction
• Policy and evidence requirements for audit
• Guidance on scoping to reduce audit surface

The build-versus-buy question is usually decided on gut feel and defended afterwards with numbers. We do it the other way round. We establish what the capability must actually do, evaluate the credible vendors against that specification, and model the real cost of each path — including integration effort, licence escalation, switching cost, and the ongoing engineering time a self-built system consumes forever. Hybrid answers are common and often correct: buy the commodity layer, build the part that is genuinely your differentiator.

• Capability specification and must-have criteria
• Vendor evaluation against that specification
• Five-year cost model for each option
• Integration and switching-cost analysis
• A recommendation with the reasoning written down

When a deal depends on a technology asset, someone independent needs to look at it. We review the codebase, infrastructure, security posture, and delivery process, and assess the team's ability to execute the plan the deal assumes. The report separates findings that should change the price from findings that are simply post-close work, because conflating the two helps nobody. We work to deal timelines and write for an audience that is not technical, with the detailed evidence in an appendix for the people who will act on it.

• Code quality and architecture assessment
• Infrastructure, security, and licence compliance review
• Team capability and key-person risk
• Technical debt quantified as remediation cost
• Findings split into deal-relevant and post-close