AI Advisor
Client
Phytech
Focus Areas
Agriculture / Data management / AI
(01)
Client overview
Phytech’s platform provides growers with real-time, data-driven insights that improve crop quality, optimize irrigation, and reduce resource usage. Through predictive algorithms, continuous plant sensing, and advanced hydraulic monitoring, Phytech supports farms worldwide in making more precise, efficient operational decisions.
(02)
Project Challenge
As AI technologies became more accessible, Phytech saw an opportunity to enhance the grower experience by introducing AI-powered recommendations. At first glance, this sounds simple, but integrating AI into a data-heavy, multi-layer agricultural platform introduced several strategic and UX challenges.
(03)
Project Goal
Help growers make more accurate decisions around plant growth, irrigation timing, fertilization amounts, and overall crop management.
(03)
Main Design Challenges
Where should AI recommendations live within a multi-layer, data-dense product?
Phytech’s platform includes multiple layers of agronomic data. Adding another information stream, especially one as influential as AI, risked overwhelming growers, many of whom already struggle with digital complexity.
How should AI recommendations relate to existing recommendation types?
Before AI, Phytech already provided multiple recommendation models:
agronomy-based recommendations (location, date, evapotranspiration), replacing or hiding them would create friction and erode confidence.
But displaying all recommendations simultaneously, old and new, risked sending conflicting signals and increasing confusion.
(04 Projects)
