-
Logo
Inspiration
The idea for Fishbox was born from frustration shared by millions of anglers: wasted trips, poor catch rates, and inconsistent results. We saw an opportunity to combine data science and user-friendly design to take the guesswork out of fishing. With so much environmental data available, why not use it to give everyday anglers a smart edge?
What it does
Fishbox analyzes real-time and historical data to predict where and when the fish are most likely to bite.
Challenges I ran into
Modeling accurate bite-time predictions across multiple regions with diverse conditions
Balancing app performance with data complexity on lower-end mobile devices
Harmonizing UX for both novice weekend anglers and hardcore pros
Sourcing and normalizing weather and water condition data in real-time
Managing battery and GPS usage without sacrificing accuracy
Accomplishments that I'm proud of
Developed a real-time predictive model that consistently outperforms generic fishing forecasts
Grew an active beta user base across four countries with strong retention
Built a scalable backend capable of handling thousands of location queries per minute
Received consistent 5-star feedback from testers on app usability and usefulness
What I learned
The value of user-centered design, especially for non-tech-savvy audiences
How to integrate and normalize disparate data sources for AI consumption
That fishing, though a traditional activity, can benefit greatly from modern tech when done right
Building trust with outdoor communities requires transparency and long-term commitment
What's next for Fishbox app
Expanding our spot database with user-submitted data and local fishing reports
Launching premium features: pro-level forecasts, offline mode, and tackle recommendations
Integrating smartwatch support for on-the-water convenience
Partnering with bait shops and local guides for verified insights
Scaling infrastructure for international growth with multilingual support
Built With
- flutter
- kotlin-(android)
- postgresql
- swift-(ios)
