Please describe your company, your role, and the industry you operate in.
As Head of Digital Health at Cedarview Health Systems I oversee technology spend and delivery across our Telecommunications operations out of Phoenix, USA. 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?
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?
Full AI & Machine Learning delivery, with particular depth on the integration and data migration pieces — the riskiest parts of the whole program. On top of that, they kept a dedicated QA person on the project throughout and left our operations team with a proper runbook at handover.
Why did you choose this company over other providers you considered?
We were coming off a failed engagement and went into vendor selection this time with a lot more scrutiny. We asked pointed questions about how they handle scope changes, how they estimate, how they communicate bad news. The answers were specific and consistent across everyone we spoke to on their team, which gave us confidence it wasn't a rehearsed pitch.
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?
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?
What they did after launch. A lot of vendors treat go-live as the finish line. This team treated it as the start of a different phase — the hypercare period was substantial, the documentation held up in practice, and they checked back in at the thirty and ninety day marks to go over production metrics with us unprompted.
Would you recommend this company to others, and would you work with them again?
Without reservation. We're already in early conversations about a second engagement, and I expect this to turn into a multi-year relationship. Anyone in Telecommunications looking for real AI & Machine Learning depth paired with actual delivery discipline should have this team near the top of their list.