Please describe your company, your role, and the industry you operate in.
As Head of Product Engineering at Vinter Digital AB I oversee technology spend and delivery across our Pharmaceuticals & Biotechnology operations out of Uppsala, Sweden. We're a commercially minded business, so every technology decision gets judged on what it actually contributes to the bottom line, not on how elegant it looks on paper.
What specific problem or business challenge led you to hire this company?
Regulation in our Pharmaceuticals & Biotechnology segment shifted and the compliance deadline came from the regulator, not from us. The scale of the AI & Machine Learning changes required justified bringing in a specialist rather than pulling our internal team off the product roadmap to handle it.
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?
We shortlisted five vendors through a structured process. The technical review knocked two out right away. Of the remaining three, this team stood out because their AI & Machine Learning approach was specific rather than generic, backed by actual reference projects in Pharmaceuticals & Biotechnology — not just case studies pulled off a website. The reference calls confirmed everything the proposal claimed.
How clearly did the company understand your requirements and business goals?
Very well. The discovery phase was more thorough than anything we'd been through with prior vendors. They pushed back on requirements that were vague or contradictory, suggested better alternatives where our own thinking was limited, and produced a spec our internal stakeholders agreed was the clearest version of the product they'd ever seen written down.
How was your overall experience with their communication and project management?
The most structured project management I've dealt with from any outside vendor. Sprint planning was tight, acceptance criteria were specific, and retrospectives actually led to changes rather than just being a box to tick. The backlog and risk register were both treated as live tools, not paperwork. I never once had to chase a status update.
Did the company deliver the project on time and within your expected budget?
Both, yes. One sprint hit a one-week delay from a third-party API dependency outside anyone's control. The team flagged it three weeks ahead of time, laid out two options, and we picked an approach that clawed the schedule back within the same sprint. That's the kind of foresight that separates real project management from just reacting to problems.
What tangible results or business impact have you seen since the project was completed?
Hard to isolate perfectly given everything else going on in the business, but the numbers we can attribute directly to the AI & Machine Learning work are solid: session duration up, conversion up, error rate down, and our NPS for that touchpoint has moved noticeably. Our account managers say it's coming up positively in client conversations now too.
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?
Absolutely, with one caveat worth mentioning: the value really starts in discovery, so clients who take that phase seriously will get the most out of it. We put real effort in upfront and it clearly paid off in what got delivered.