Blink+

Project summary: Our audience data was fragmented across eight tools with no single identity layer. Personalisation had become impossible without first solving the data foundation.

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: 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: 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.

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: An international expansion required multi-currency, multi-language, and multi-warehouse capabilities that our existing platform could not support without a fundamental re-architecture.

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: Our engineering capacity was committed to maintaining existing systems and could not absorb a net-new build of this complexity. An external partner with the right skills was the only viable option.

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: 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.

Project summary: Our actuarial models had outgrown the reporting infrastructure feeding them. Data latency was introducing risk into pricing decisions that the business had decided it could no longer accept.

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: Our agents were spending more time managing data across disconnected systems than managing relationships. We needed a unified platform to give them that time back.

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.