Not every app needs to reinvent the wheel. But sometimes the existing wheels don't fit — and that's exactly the situation with Control Canine. Standard appointment scheduling tools are built for broad use cases. Pet services, particularly for dogs, have their own specific flow: breed considerations, service types, scheduling windows, owner preferences. A generic solution would have felt like a square peg in a round hole.
I joined the team after Fingo, and for three months we focused entirely on building something purpose-built for this niche.
What I Worked On
The core of my contribution was designing the appointment scheduling experience — building a flow that felt intuitive for pet owners rather than just functional. That meant thinking carefully about how users would actually move through the app. What information do they need upfront? Where do they get confused? How do you make booking a grooming appointment feel effortless rather than administrative?
I also handled API integration, connecting the app to external systems to keep scheduling data, availability, and service information in sync. Clean data flow is invisible when it works and immediately frustrating when it doesn't — making it reliable was a quiet but important part of the project.
The Design Challenge
Pet service apps live in an emotional space. People care deeply about their dogs. The interface had to reflect that — warm enough to feel approachable, structured enough to be efficient. Getting that balance right across the UI was something the whole team cared about, and something I put real thought into.
What Three Months Here Taught Me
After Fingo's scale and complexity, Control Canine was a focused exercise in doing one thing really well. Appointment scheduling sounds simple. Doing it in a way that's genuinely tailored to a specific audience — that's the harder problem. This project sharpened my thinking about user-specific design and reminded me that niche products deserve the same care as broad ones.
This was a private company project — screenshots and code remain confidential, but the problem-solving behind it was very real.