Frequently Asked
Questions.

Every migration is different, but the pattern is consistent: assess what you've got, define the target architecture, migrate in phases, and optimise once you're there. We favour AWS and Azure, we automate everything we can, and we don't lift-and-shift unless there's a genuine reason. The goal is a platform that's cheaper to run, faster to deploy to, and doesn't page anyone at 3am.

Both. There's a lot of hype, and there's a lot of genuine value. The trick is knowing which is which. We help clients identify AI use cases that will actually deliver ROI, build proofs of concept to validate them, and then productionise the ones that work. We use AI ourselves every day (Claude, Copilot, custom agents) so we're not theorising. We're practitioners.

We're headquartered in Leeds, West Yorkshire with offices at 66 Paul Street, London. We work with clients across the UK and beyond. Our consultants are embedded in client teams, sometimes on-site, sometimes remote, always delivering. We're proudly onshore and don't offshore engineering work.

We start with the problem, not the technology. What decision are you trying to improve? What process are you trying to automate? Once we understand the business case, we scope a focused PoC, typically 4-8 weeks, that answers a specific question. We use real data, build something tangible, and present results your board can actually evaluate.

Three things. First, we only send senior people, no graduate bench-filling. Second, we're practitioners who use AI in our own work, not just sell it. Third, we're direct about what will and won't work. We'd rather lose a deal by being honest than win one by overselling. Our 93% customer CSAT score suggests this approach works.

Carefully. We assess the existing system's architecture, dependencies and data flows. Then we design a target architecture on AWS that actually takes advantage of cloud-native services, not just running the same monolith on EC2. We migrate in phases, with rollback plans at every stage, and we automate the infrastructure so it's repeatable and auditable.

We build. Our engineers write production code, architect systems and ship features alongside your team. We also advise on architecture, delivery approach and technology choices, but we believe the best advice comes from people who are also doing the work. We're not a slide deck consultancy.

We've delivered across financial services, gaming and betting, travel, media and professional services. Our sweet spot is complex, regulated environments where engineering quality matters. Places where a bad deployment isn't just embarrassing, it's expensive.

Every engagement is scoped to your needs, so there's no standard price list. We're transparent about rates and we scope work honestly. We'd rather give you a realistic estimate than a low-ball that creeps. The best way to get a sense of cost is to tell us what you need and we'll give you a straight answer.

Data engineering is the plumbing that makes analytics and AI possible. It's the pipelines that move data from source systems into warehouses, the transformations that make it usable, and the infrastructure that keeps it reliable. Without solid data engineering, your dashboards show stale data and your AI models train on garbage. We build the foundations that make everything else work.

Yes, but we don't use that phrase without rolling our eyes a bit. What we actually do is help you figure out which technology investments will move the needle, build a roadmap that's achievable with your team and budget, and then help you execute it. Strategy without delivery is just a PDF. We do both.