GrowMore | GBot Software Consultancy
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AgTech

GrowMore

A Virtual Agronomist for New Zealand Farms

Client

GrowMore

Role

Full-stack development (Flutter + Python)

Year

2026

Platforms

iOS · Android · Web

Flutter Riverpod Firebase Python Cloud Functions

Least-cost fertiliser blends from raw soil tests

GrowMore is a decision-support platform for New Zealand farmers and agronomists. It turns soil and pasture test results into precise, cost-optimised fertiliser plans — the kind of analysis that normally takes a professional agronomist. GBot built the product end to end, from the Flutter apps to the optimisation engine behind them.

Overview

Soil testing produces a wall of numbers; turning those numbers into the right fertiliser plan is expert work. GrowMore captures a farm's tests and recommends the optimal blend for each block, balancing agronomic targets against cost and what suppliers actually stock — then packages it into orders and plans a farmer can act on.

The Challenge

Interpreting soil tests and translating them into a fertiliser blend has to hit nutrient targets across every paddock while keeping cost down and respecting real product availability. Done by hand it's slow, expensive, and inconsistent. GrowMore needed to make that expertise available to any farmer — with results trustworthy enough to spend money on.

What We Built

  • Soil-test capture and farm management — farms split into blocks and paddocks, each with its own test data and targets.
  • A nutrient engine that recommends optimal fertiliser blends across multiple suppliers and products.
  • Order placement with supplier and product comparison.
  • Server-generated PDFs — per-order and whole-farm plans — delivered by email.
  • Admin tooling for bulk product and price management.

Technical Highlights

  • A proprietary optimisation engine, running as a Python cloud function, computes the most cost-effective blend that meets each block's nutrient targets — serious math done server-side, behind a deceptively simple app.
  • A cross-language full stack: Flutter (Riverpod, auto_route) on the front end, Python cloud functions for optimisation and document generation.
  • Server-side PDF generation for orders and whole-farm plans, with queued email dispatch.
  • A nutrient model with target ranges and validation that keeps every recommendation agronomically sound.

Outcome & Impact

  • A production platform that puts agronomist-grade fertiliser planning in farmers' hands across iOS, Android, and web.
  • Recommendations that balance agronomic targets against real-world cost and supplier availability.
  • A backend that does the heavy computation, so the farmer just sees a clear, actionable plan.

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