AgriSmart.
Smart farming ecosystem — sensors, AI & advisory
Problem, solution, and result.
A tighter story that reads like a real client case study.
Smallholder farms lack affordable precision agriculture tools.
Low-cost LoRaWAN sensors paired with an AI advisory app in regional languages.
28% water savings · 17% yield uplift · 5k+ farms onboarded
A system designed to last.
Edge-native, observable and built for compounding velocity.
What was actually built.
A useful snapshot of the product and system behind the case study.
Smallholder farms lack affordable precision agriculture tools.
Low-cost LoRaWAN sensors paired with an AI advisory app in regional languages.
A project-specific visual that anchors the story without relying on a generic category mockup.
- Soil moisture & NPK
- Weather-aware irrigation
- Yield forecast
- Regional language UX
Crafted surface. Considered system.
Grouped so the product read feels intentional instead of crowded.
Core experience
- Soil moisture & NPK
- Weather-aware irrigation
Platform & systems
- Yield forecast
- Regional language UX
Five movements. One outcome.
The work is easier to follow when each phase gets its own room.
Stakeholder interviews, market analysis, success metrics and a sharpened product thesis.
Information architecture, user journeys, technical constraints and a pragmatic roadmap.
Editorial visual system, motion language and prototype-driven product surface design.
Type-safe full-stack engineering with observability, performance budgets and CI from day one.
Phased rollout, telemetry, growth instrumentation and an always-on iteration cadence.
These are the actual technologies used in this project, not a curated shortlist.
Drone scouting and computer vision pest detection.
