Inspiration
Smallholder farmers across East Africa lose up to 40% of their yield to undiagnosed crop diseases. But the problem doesn't stop at the farm gate. Without formal production records, these same farmers are locked out of reliable buyers who need consistent supply and denied credit by banks that demand collateral they don't have. We saw an opportunity to turn crop health data into a farmer's greatest asset: a verifiable production history that opens doors to better markets and fair financing. VunaLink was born from the belief that the same technology that helps a farmer treat their crops today can prove their creditworthiness tomorrow.
What it does
VunaLink is an offline-first agricultural platform that helps smallholder farmers detect crop diseases, access affordable treatment recommendations, and build a financial passport from their production history. Core Features:
- Offline Crop Disease Detection: Farmers capture or upload images of affected crops. Using a TensorFlow-based ResNet-50 model trained on PlantVillage data, VunaLink identifies diseases with confidence scores—no internet required.
- Affordable Treatment Recommendations: After detection, the app provides actionable, locally available treatment options (organic sprays, neem oil, pruning techniques) with cost estimates and application instructions.
- Crop Health & Yield Tracker: Every detection, treatment, and harvest is logged, creating a timeline of the farmer's production history and crop management practices.
- Market Access: Buyers can view a farmer's crop health record to assess reliability and consistency, reducing friction in farmer-buyer relationships.
- Loan Eligibility Dashboard: VunaLink transforms crop health data and sales transactions into a creditworthiness score, giving banks and microfinance institutions proof of income and productivity when formal collateral doesn't exist.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for VunaLink
Built With
- data-science
- git
- tensorflow


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