AI for smallholder agriculture

FarmPilot팜파일럿

A pocket agronomist and market advisor for the world's smallest farms.

FarmPilot turns an ordinary smartphone into an AI copilot that helps a smallholder farmer protect a crop, time a sale, and get expert guidance spoken in their own language.

Built for the hundreds of millions of smallholder farms that feed much of Asia.
The problem

The farms that feed Asia have the least support.

Smallholdings under one hectare run most farms in Korea and across much of Asia, yet they operate on the thinnest margins and with the least access to the two things that decide a season's income: timely agronomy expertise and market information.

A pest caught a week late, or a harvest sold on the wrong day, can erase a season's profit. Climate stress is widening both gaps at once, with unfamiliar pest patterns and more volatile yields and prices. Expert advice exists, but not in the field, not in real time, and rarely in a form a busy farmer can act on.

How it works

Three models, one assistant a farmer can actually use.

01

Diagnose

Point the phone at a sick plant. A vision model identifies the pest or disease and suggests a treatment, running on the device so it works offline in the field.

Computer vision
02

Time the market

FarmPilot models price trend and volatility to help decide when and where to sell, turning market data into a plain recommendation instead of a spreadsheet.

Time-series modeling
03

Talk

Ask anything by voice, in your own language or dialect. A language model answers in words a farmer uses, so the tool serves people with low digital or text literacy.

Language model
See it work

A real prediction from the working model.

The diagnosis model is built and measured, not a mockup: 97.8% validation accuracy on the PlantVillage benchmark, in a 6 MB model light enough to run on-device. Below are actual outputs on held-out leaf images the model never trained on.

Tomato leaf with late blight
Diagnosis

Tomato · Late blight

99.8%

Act fast: remove infected plants, avoid overhead irrigation, and apply a labeled fungicide preventatively. Late blight can destroy a crop within days.

Potato leaf with early blight
Diagnosis

Potato · Early blight

100%

Rotate crops away from solanaceous hosts, remove infected debris, and apply a labeled fungicide starting at first symptoms.

Healthy apple leaf
Diagnosis

Apple · Healthy

100%

No disease detected. Continue routine monitoring and balanced watering, and re-check if new spots or discoloration appear.

These are PlantVillage benchmark images (single leaves on plain backgrounds), so real in-field accuracy will be lower. This is an early prototype and not a substitute for an agronomist. The model, training pipeline, and a runnable demo app are available to reviewers on request.

Why AI, why now

The interface is the innovation.

The hard part of agtech for smallholders is not the models, it is delivery. FarmPilot is designed around how a farmer actually works: on a basic phone, with patchy connectivity, no time to type, and no technical training.

On-device and offline-first. Diagnosis runs on the phone, so a dead zone in the field is not a dead end.

Voice and dialect native. The assistant meets farmers in spoken local language, not menus and forms.

Three model types, one surface. Vision, forecasting, and language fused into a single copilot a non-technical user can trust.

Why it matters for the planet

Loss reduction at the level of the people most exposed to climate change.

Every crop lost to a missed diagnosis, and every harvest sold badly, is food and income gone from a household with little to spare. Helping smallholders lose less and earn more is climate adaptation delivered to the front line.

Smallholders steward a large share of Asia's farmland and food supply while absorbing the sharpest edge of a changing climate. FarmPilot starts in Korea and is built for the smallholder pattern common across the APAC region.

Where we are

Early and deliberate.