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Eric Reyna
Case Studies
Other Works
- Enabled partners to use OnWater as a field-ready data tool
- Created a new revenue stream via branded integrations
- Improved partner satisfaction through tailored flows and lower onboarding friction
- Strengthened trust with conservation groups through ethical data UX
- Extended OnWater’s reach with an AI-powered Journal feature
- LandTrust and Abel Reels actively promoted their OnWater-integrated features
I designed data collection flows for partners like Science on the Fly to log repeatable river observations and submit tagged media.
These tools supported AI-driven fish recognition by allowing photo uploads with geolocation metadata, enabling pattern-matching to identify individual fish across time and space.
All flows reused our shared design system for consistency and development efficiency.
I created a native-feeling booking experience in-app for private land trips and reservations through LandTrust.
Shared components helped maintain OnWater’s visual consistency while supporting third-party integration.
I helped design a B2C flow that let users engrave Abel reels with OnWater map locations.
The UI bridged both brands using existing patterns to simplify dev and stay visually aligned.
I shaped the Journal UX around OnWaters Patented AI tools that auto-identified species, estimated fish size, and recognized individual fish based on skin patterns (Patent : US-12094119).
These same tools supported conservation efforts, like the Trout Spotter Program by Trout Unlimited, by logging sightings with geolocation data. I designed form states to accept metadata fields that made the experience trustworthy, editable, and intuitive.
This project taught me how to balance the goals of internal teams, brand partners, and everyday users without compromising usability.
Collaborating closely with GIS, product, and engineering helped me build flexible tools that respected both ecological data constraints and brand standards.
Designing around AI pushed me to think about trust, transparency, and control, especially when the same feature served both personal use and conservation tracking.
My next steps would include deeper customization for partners, user feedback loops on AI accuracy, and role-based data presentation for both casual anglers and scientific contributors.
