FutureSeed AI
Photograph a sick crop and get the diagnosis and treatment in about 3 seconds, offline, free, in your own language.
See the farmer appPhotograph a sick crop and get the diagnosis and treatment on the spot. Built for the Filipino farmers who have a smartphone but no one to ask.
An offline AI that helps a farmer identify what is attacking the crop, apply the correct dose, and build the farm record that qualifies them for low interest financing.
“Of 15” figures are from our baseline survey of 15 farmers in Agusan del Sur, July 2026.
“Wala man Agri technician na muanhi.”
No agricultural technician ever comes here.
The model is small enough to run on a budget Android phone, so the whole diagnosis happens on the handset the farmer already owns.

01Step
Rice, corn, banana, cassava, coconut, or abaca. More crops are in training, and the app says which ones are not ready yet.

02Step
Take a few shots of the affected leaf. The app combines them into a single, more reliable reading, with no signal required at any point.

03Step
About three seconds later: the disease named, how confident the model is, how urgent it looks, what causes it, and which treatments to consider. Tap to hear it read aloud.



“Mao jud ni amo kinahanglan!”
This is exactly what we need.
From Quezon City’s own incubator to a fellowship in Singapore and the World Bank Youth Summit in Washington D.C., each of these programs put the same product through its own gate.
NUS ASEAN SPARK Fellowship 2026, Singapore

ASEAN Philippines National Innovation Day 2026, Top 10 finalist
World Bank Group Youth Summit 2026, Washington D.C.

First local-government-led startup incubation program in the Philippines

LIF Launchpad completed at TRL 4, toward SDG 2 Zero Hunger
A free tool in every farmer’s hand, and the intelligence layer that helps their agricultural organization act on it.
Photograph a sick crop and get the diagnosis and treatment in about 3 seconds, offline, free, in your own language.
See the farmer appTurn every member's scan into outbreak alerts, bulk-order demand, and loan-ready farm plans.
In development. An early prototype exists; the figures it shows are sample data.
See the dashboardStudent builders in Luzon and field advisors who live and work in the Mindanao farming communities we serve, including an agricultural organization manager and the founder of the farm store that opens these communities to us.

Jerome Ancheta
Machine Learning Lead

Dwayne Peña
Design Lead

James Semitara
Field Operations, Camiguin

Roselyn Galupo
Community Operations, Agusan del Sur

Wahid Ronda
Sustainable Agriculture
Existing tools assume both. That assumption is what leaves 7 million Philippine farming households outside the reach of agricultural technology.
Agricultural organizations, LGUs, schools and NGOs are how this reaches the farmers who need it. Tell us about yours and we’ll come back to you with what a pilot in your area would look like.
Be first to put a free, offline agronomist in your pocket. Leave your email and we’ll let you know the moment it’s ready.