AquaTrack — Helping African Small & Medium Fish Farmers Run Profitable Farms with AI

Role

Lead Product Designer

Timeline

3 Months

Industry

AgriTech / SaaS Product

Tools Used

Design: Figma

Development: Lovable (AI-assisted no-code platform)

Research: Google Forms, WhatsApp, Maze

Collaboration: Slack, Notion

Project Overview

AquaTrack is an AI-powered farm management platform helping African small and medium-scale fish farmers monitor ponds, track expenses, manage growth cycles, and get real-time recommendations, all in one simple dashboard.

As Lead Product Designer, I shaped the entire product experience, from user research and interface design to building and shipping a working MVP using no-code tools. I worked directly with farmers to validate features and iterate based on real-world usage.

The Problem

African fish farmers operate in chaos: scattered notes, no real-time tracking, and zero data insights. This lack of structure leads to high costs and uncertain profits.

Feed wastage

Poor growth estimation

High mortality

No financial visibility

"I know my fishes are growing, but I can't tell if I'm making profit or loss."

— Fish farmer, Lagos

My Role

Led product UX strategy and direction

Designed the complete web and mobile experience

Built and shipped the MVP using Lovable

Conducted user research with 30+ farmers

Prioritized features based on user feedback

Designed pitch deck and investor materials

Key Challenges

Challenge 01: Low tech literacy

Most farmers had never used a dashboard. Complex interfaces would fail.

Solution

Designed a mobile-first interface with large touch targets and visual icons.

Challenge 02: Intermittent internet

Farmers operate in rural areas with unstable connectivity.

Solution

Built offline-first features with data sync when online.

Challenge 03: Proving value quickly

Farmers wouldn't pay unless they saw immediate benefit.

Solution

Made the free tier generous and added AI recommendations that save money.

Solution Overview

Designed the system as a structured, cloud-based AI management platform controlled by a management system enabling the connected, market-driven farms.

Low-code development

Real-time data syncing

Mobile-first design

Smart recommendations

Design & Development Process

1. Research & Strategy

2 weeks

•Conducted interviews with 30+ farmers
•Analyzed competitive landscape
•Mapped user workflows and pain points

2. Design & Prototyping

3 weeks

•Created low-fidelity wireframes
•Built interactive prototypes
•Validated designs with users

3. Development & Shipping

3 weeks

•Built MVP using Lovable
•Integrated backend services
•Launched beta to first farmers

4. Iteration & Optimizing

1 week

•Gathered user feedback
•Fixed critical issues
•Optimized performance

Key Screens

The platform includes dashboards for farm management, batch tracking, harvest planning, pond monitoring, inventory management and financial reporting. Each screen was designed for simplicity and fast data entry, critical for farmers walking in the field.