Software Giant

Project summary: A previous engagement had delivered something that worked in staging and struggled in production. We approached this project with greater rigour in vendor selection as a result.

We had worked with three agencies before this engagement. The comparison is not flattering to the others. What distinguished this team was a systematic approach to understanding the problem before proposing a solution — something that sounds obvious and is practiced far less often than it should be. The delivery phase ran to schedule, the codebase is clean enough that our internal engineers made positive comments during handover review, and we have not logged a critical incident in five months of live operation. We intend to use them for our next phase of work.

Project summary: Grid modernisation funding required us to demonstrate demand-response capability. The machine learning models existed on paper; we needed an engineering partner to build and productionise them.

The technical quality of the final deliverable is the easiest thing to point to. The automated test coverage is thorough, the deployment pipeline is reliable, the documentation is genuinely useful rather than ceremonially produced. But the metric I keep returning to is the number of post-launch conversations we have not had to have. No incident calls at two in the morning. No emergency patches. No retrospective discussions about what went wrong. The absence of those events is the evidence I would show to someone considering this vendor.

Project summary: Several years of incremental development had left us with a platform that was technically functional but strategically limiting. A structured rebuild was the agreed path forward.

The technical quality of the final deliverable is the easiest thing to point to. The automated test coverage is thorough, the deployment pipeline is reliable, the documentation is genuinely useful rather than ceremonially produced. But the metric I keep returning to is the number of post-launch conversations we have not had to have. No incident calls at two in the morning. No emergency patches. No retrospective discussions about what went wrong. The absence of those events is the evidence I would show to someone considering this vendor.

Project summary: Customer expectations had reset and our conversion funnel data showed precisely where we were losing them. We needed a commerce platform capable of delivering the experience our competitors already had.

The project brief was ambitious and we had received proposals ranging from two to five times our eventual budget from other vendors. This team came back with a proposal that was commercially realistic and technically credible — and then delivered against it. That alignment between proposal and outcome is not something I take for granted. I have been on the other side of it enough times to know it requires both honesty in the sales process and discipline in delivery. We experienced both.

Project summary: Cross-agency data sharing had been blocked by incompatible systems for four years. A secure integration platform was the prerequisite for every transformation initiative in our roadmap.

The technical quality of the final deliverable is the easiest thing to point to. The automated test coverage is thorough, the deployment pipeline is reliable, the documentation is genuinely useful rather than ceremonially produced. But the metric I keep returning to is the number of post-launch conversations we have not had to have. No incident calls at two in the morning. No emergency patches. No retrospective discussions about what went wrong. The absence of those events is the evidence I would show to someone considering this vendor.

Project summary: Serialisation requirements under new traceability legislation had a compliance deadline. Our supply chain system required targeted development to meet it — generalist knowledge was not sufficient.

Six months after go-live our platform is processing three times the transaction volume we specified in the original brief. The architecture choices made during discovery accommodated that growth without remediation work. That is the difference between a team that designs for what you tell them and a team that designs for what you are likely to need. We are in conversation about a Phase 2 engagement and I expect to be using this partnership for several years.

Project summary: Integration between our clinic management system and our patient-facing app had been a recurring failure point. We needed an engineering partner who could own the integration layer end to end.

We had worked with three agencies before this engagement. The comparison is not flattering to the others. What distinguished this team was a systematic approach to understanding the problem before proposing a solution — something that sounds obvious and is practiced far less often than it should be. The delivery phase ran to schedule, the codebase is clean enough that our internal engineers made positive comments during handover review, and we have not logged a critical incident in five months of live operation. We intend to use them for our next phase of work.

Project summary: First notice of loss processing was taking three days on average. Market benchmarks were under four hours. Automation of the intake and triage workflow was the agreed priority.

I came into this engagement as a sceptic. We had been through a failed implementation with a previous vendor and I had high standards for what evidence of competence looked like before I would trust a partner with our core systems. This team earned that trust progressively — through the quality of the discovery documentation, the rigour of the technical proposals, the consistency of the sprint deliveries, and ultimately the stability of the production system. I no longer lead with scepticism when recommending them.