Rice(Palay)
5 diseases detected
- Blast
- Bacterial Leaf Blight
- Brown Spot
- Sheath Blight
- Tungro
Includes a healthy reference
Early Access
FutureSeed AI
Photograph a sick crop and get the diagnosis and treatment in about 3 seconds, offline, free, in your own language.
Overview
An on-device AI app that diagnoses crop disease and pests from a photo and recommends treatment across organic, biological, traditional, and synthetic options, prioritizing the minimum effective intervention. Everything runs offline on a budget Android phone, and every record syncs automatically once a signal returns. The app is built around one cycle. Diagnose the problem, treat it right, and prove it. Proving it means a timestamped, photo-backed record of what was applied and when, the evidence that supports a crop-insurance claim and the farm track record that can qualify a farmer for lower-interest formal credit instead of informal loans. Today the app handles the diagnosis and the treatment guidance, while exact-dose guidance sized to the farmer's field and that application record lead the roadmap below.
Who it’s for: Smallholder Filipino farmers with budget Android phones and little or no connectivity, most without access to formal credit and financing inputs through informal loans at 5 to 10 percent monthly interest.
What the app does today
- On-device AI diagnosis in about 3 seconds, fully offline, no internet, no subscription, no data cost (~5MB TensorFlow Lite model)
- 31 disease and pest conditions across 6 crops, Rice, Corn, Banana, Cassava, Coconut, and Abaca, with more crops in training
- Multi-photo scanning: several shots of the same plant are combined for a more reliable read
- Results show a confidence figure, a severity call, a plain-language explanation, and audio playback for farmers who would rather listen than read
- Treatment guidance across 4 categories: organic, biological, traditional, and synthetic
- Cebuano, Filipino, and English interface; runs on budget Android phones
- Farm records that work offline, input calculator, expenses, harvests, and a season profit summary, all syncing automatically when signal returns
- Weather with a spray advisory, a store finder, and local market prices (these need limited signal)
What we’re building next
These are in development, not shipped. They lead the roadmap because our field testing ranked them highest.
Exact-dose guidance
In developmentTurning every diagnosis into the precise amount to buy and mix for the farmer's actual field size. Stretched dosing is the most expensive failure our testing quantified, which is why this leads the roadmap.
Timestamped application records
In developmentA photo-backed evidence trail built to support crop-insurance (PCIC) claims that adjusters currently deny for lack of proof, and to serve as the farm track record rural banks ask for when lending.
A model that knows when to decline
In developmentTeaching the model to name a nutrient deficiency instead of forcing a disease label, to ask for a closer photo when nothing diagnosable is visible, and to report a confidence figure that tracks reliability.
What it detects
The model recognises 31 disease and pest conditions across 6 major Philippine crops, with more crops in training. The 20 diseases named below are the ones we can list individually.
Corn(Mais)
3 diseases detected
- Northern Leaf Blight
- Common Rust
- Cercospora Gray Leaf Spot
Includes a healthy reference
Banana(Saging)
2 diseases detected
- Black Sigatoka
- Fusarium Wilt
Includes a healthy reference
Cassava(Balanghoy)
4 diseases detected
- Bacterial Blight
- Brown Streak Disease
- Green Mottle
- Mosaic Disease
Includes a healthy reference
Coconut(Niyog)
4 diseases detected
- Bud Rot
- Grey Leaf Spot
- Leaf Rot
- Stem Bleeding
Includes a healthy reference
Abaca
2 diseases detected
- Bunchy Top Virus
- Sigatoka
Includes a healthy reference
A look inside
Home 
Choose the crop 
Scan 
Result
Be first to try it
Free for farmers, permanently. No subscription, no data cost, no farmer fees, ever.