Please describe your company, your role, and the industry you operate in.
I run technology for Silverbrook Digital Ltd, a growth-stage Government & Public Sector company based in Belfast, UK. My role as VP of Product Engineering covers product engineering, platform operations, and our vendor relationships. We'd hit a point where our internal capacity just couldn't keep pace with what the roadmap demanded.
What specific problem or business challenge led you to hire this company?
Our AI & Machine Learning capability had become the thing slowing everything else down. New feature requests, client asks, internal initiatives — all of it kept queuing up behind a platform that had been stretched way past what it was originally built for. We needed a proper rebuild, not another patch.
What services did the company provide for your project?
The scope ran the full AI & Machine Learning lifecycle — discovery, requirements, architecture, development across roughly a dozen sprints, integration testing, performance validation, deployment, and a four-week hypercare window afterward. They also handed over full documentation and ran a knowledge transfer session for our internal team.
Why did you choose this company over other providers you considered?
The questions they asked during the briefing stage told us most of what we needed to know. Vendors who ask sharp questions during sales tend to bring that same rigor into delivery, and that held up. The technical proposal had real substance, the team was senior from the start, and the pricing was straightforward.
How clearly did the company understand your requirements and business goals?
Thoroughly. The requirements document was detailed enough that our own QA team used it directly to build acceptance criteria. Every user story had a clear business reason attached, and nothing was left open to interpretation. That discipline early on paid off through the rest of development and testing.
How was your overall experience with their communication and project management?
Proactive and well-calibrated. Technical detail for the engineering side, plain summaries for the steering group, and risk flags that came with a proposed fix attached rather than just a problem statement. The biweekly sprint reviews kept our stakeholders in the loop without requiring them to sit in on every working session.
Did the company deliver the project on time and within your expected budget?
On time and inside the approved budget. Their estimating was notably accurate — they'd broken the work down in enough detail during discovery that the forecast held up the whole way through, instead of drifting with every small change. We had exactly one change request, and it was for scope we added ourselves.
What tangible results or business impact have you seen since the project was completed?
The clearest measure is how the system's actually performing in production. In the four months since go-live we've had zero major incidents, our page performance scores improved across every Core Web Vitals metric, and two enterprise clients who'd previously flagged our old platform's limits during renewal talks signed again without raising it.
What did you like most about working with this company?
Their willingness to just be direct. If our requirements were unclear, they said so. If our priorities contradicted each other, they explained why. If an approach we'd assumed was right actually had real downsides, they told us before we'd committed to it. That kind of honesty is exactly what I look for in a long-term partner.
Would you recommend this company to others, and would you work with them again?
Yes, no hesitation. I've already referred them twice within my own Government & Public Sector network, both times to people facing AI & Machine Learning problems similar to ours. I made those referrals confidently because I know the experience I had was repeatable, not a one-off stroke of luck on our project.