Work
Projects we ran from the problem to production
Each case study covers the business challenge, the scope of delivery and the technical approach — including the decisions that turned out to be hard.
01Loyalty app and admin platform
IZAPzoo
IZAP, a brick-and-mortar retail chain, wanted its own loyalty programme on customers' phones instead of plastic cards. We designed and built the whole thing — Android and iOS apps, a cloud backend and an admin platform — and store staff now run points, rewards and promotions themselves.
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02Private opportunity-discovery tool with AI-assisted analysis
ThomasSeekerAI
A private trader was combing OLX, Otomoto, Allegro and a handful of smaller sites by hand, every day, for things worth reselling. We built an internal tool that takes that work over: searches described in a plain sentence run on a schedule in the background, the noise is filtered out, and what is left is ranked by how good the opportunity looks — hours of manual browsing turned into an automated job.
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03Client site
Kamil Rosikiewicz
Kamil Rosikiewicz needed a website that proves quality through imagery yet still opens fast on a phone. We built a site where the portfolio plays like a showreel and every page leads the visitor down a clear path — to an enquiry, or to a place on a training course.
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04Selected CI/CD, automation and infrastructure engagements
DevOps Engineering
Most of these projects start the same way: releases done by hand after hours, environments nobody can rebuild, deployment knowledge locked in one head. They end with a repeatable process — CI/CD pipelines, infrastructure described in code and monitoring that reports problems before users do — and with releases nobody holds their breath for.
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05Automated data validation and testing in an enterprise environment
Data Reliability Platform
The most dangerous data failures are silent: jobs finish 'successfully' while the reports show something false. This enterprise platform on AWS catches such inconsistencies daily — automated validation, integration tests and monitoring, with results you can check rather than take on trust. The firm's founder worked on it as an engineer within a larger team, responsible for data-validation automation and testing.
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Some projects are covered by confidentiality — we describe them without revealing client data or details protected by agreements.
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