Please describe your company, your role, and the industry you operate in.
I run technology for Bug Tech Studio, a growth-stage Energy & Utilities company based in Poznań, Poland. My role as CTO 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?
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?
Better than we understood them ourselves, honestly. The workshops they ran surfaced assumptions we'd never questioned and exposed a few requirements that flatly contradicted each other. Sorting that out before development started saved us from what would have been serious rework later.
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 ROI model we took to the board was deliberately conservative. Current performance against that model puts us on track to hit payback well ahead of the eighteen-month target we set. The operational efficiency gains in particular have outpaced the model, partly because the new platform's data quality supports decisions the old system simply couldn't.
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?
Yes, no hesitation. I've already referred them twice within my own Energy & Utilities 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.