SoftDoes

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 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: Remote care had gone from an experiment to a core service line and our technology had not kept pace. We needed a robust, compliant telehealth platform in a timeline that the market would not wait for.

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: Multi-touch attribution across our media mix had become the most-requested capability from every client in our portfolio. We could not deliver it without rebuilding our data layer.

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: Warehouse management inefficiencies were adding cost and introducing errors at a rate that was becoming visible to clients. A modernised WMS was the agreed solution internally — we needed a partner to build it.

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: Remote care had gone from an experiment to a core service line and our technology had not kept pace. We needed a robust, compliant telehealth platform in a timeline that the market would not wait for.

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: Remote care had gone from an experiment to a core service line and our technology had not kept pace. We needed a robust, compliant telehealth platform in a timeline that the market would not wait for.

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: 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.

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: As a technology business ourselves we apply the same scrutiny to our vendor selection that our clients apply to us. We needed a delivery partner who could meet a standard we would be comfortable being measured against.

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.