Jiratech

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.

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.

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.

The thing that retrospectively seems most significant is how little drama there was. Complex technology projects tend to accumulate incidents, escalations, and tense conversations. This one did not. Problems were surfaced before they became incidents. Scope changes were handled with process rather than conflict. Risks were managed rather than avoided. That level of maturity is rare in my experience and it made the delivery feel almost effortless from our side, which I know it was not from theirs.

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.

We gave this team an aggressive timeline, a technically complex scope, and a client-side project team that was stretched thin and not always available at the speed the engagement required. They absorbed all of that gracefully. Where they needed input they were precise about what they needed and when. Where they could proceed independently they did. The result was a delivery that landed on time despite the constraints on our side, which I regard as evidence of genuine professional maturity.

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 integration layer was the part of the project I was most concerned about going in. Our system landscape is complex, several of the upstream APIs we relied on were poorly documented, and two third-party vendors had a history of unpredictable response times on integration questions. This team managed all of that. They documented what the upstream vendors could not, built resilience into the integration architecture where the upstream behaviour was unreliable, and delivered a solution that works as specified in production. I could not have asked for more.

Project summary: A merger had left us with two incompatible student information systems. We needed a consolidation path that preserved historical data, maintained service continuity, and met accreditation requirements.

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: Our campaign management workflow had grown to involve twelve different tools and significant manual reconciliation. The inefficiency was affecting both speed and accuracy.

What made the most difference in practice was the quality of the engineering judgment on this team. Not the ability to execute a specification — that is a baseline expectation. The ability to recognise when a specification was suboptimal, explain why, propose an alternative, and support the client in making a decision about it. That consultative dimension elevated the output beyond what the brief described and resulted in a product that is more fit for purpose than the one we had originally specified.

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.

What made the most difference in practice was the quality of the engineering judgment on this team. Not the ability to execute a specification — that is a baseline expectation. The ability to recognise when a specification was suboptimal, explain why, propose an alternative, and support the client in making a decision about it. That consultative dimension elevated the output beyond what the brief described and resulted in a product that is more fit for purpose than the one we had originally specified.