HarvestIQ
Tomato AI
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Bangladesh tomato intelligence
AI screening for tomato leaf disease, built for farmers, field officers, and agribusiness teams working in humid Bangladesh conditions.
Disease screening
Upload a clear tomato leaf image. HarvestIQ returns the closest disease class, confidence, field actions, and Bangladesh-specific notes.
The result will show disease class, confidence, advisory, image quality, and model limitations.
Prediction
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Field operations
The product surface is built for repeated crop scouting: fast upload, readable confidence, and practical advisory output.
Use the result as a first screening signal, then confirm with a field officer before treatment decisions.
Move from verbal symptom descriptions to photo-backed advisory conversations.
Capture predictions and farmer requests in one workflow for district-level follow-up.
Scientific roadmap
Launch with a transfer-learning plant disease classifier covering the common PlantVillage tomato classes.
Collect district, cultivar, season, phone-camera, and lighting metadata before claiming field accuracy.
Route uncertain predictions to agronomists and improve the model with verified field labels.
Tomato focus
Pilot HarvestIQ
Use HarvestIQ with farmer groups, input dealers, nurseries, or field-extension teams. Leads and prediction history are saved locally in data/harvestiq.sqlite.