FeedWise AI :Intelligent Livestock Feed Advisor

FeedWise AI is an app that helps Kenyan livestock farmers create affordable, balanced feed plans using the ingredients they have ,all based on the animal’s Characteristics.

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Inspiration

Coming from a small livestock farming household and a a graduate of Animal Science, my goal has been to provide solution from the problem we are facing. One of them is providing a balanced ration to our few animals in the homestead without spending an extra coin, and optimizing productivity. This made me think of a modern solution that takes seconds to make a ration, providing a good recommendation based on what one has. In addition, emergency cases such as Veterinarian who takes time was also one of the Motivation. Bonuses such as a fair market place , where farmers and professions can offer their goods and services at a reasonable price.

What it does

The app, Calculates a nutritionally sound ration. This will help farmers(especially small scale) . This will reduce the cost of feeding. The app also has the veterinary access, where there will be 24 hours, 7 days a week response. The app also has a market place for fair prices, where one can post what they offer.

How we built it

The app is built with Help of Ai(Bolt.new), with extra coding from my self. It uses Typescript and React. It also has a database in Super base. It is important to note that this is a trial app, and we are working on the live app.

Challenges we ran into

Data availability and accuracy: Sourcing reliable, county-specific livestock and feed data was difficult due to inconsistent or outdated public datasets.

Balancing rations with limited inputs: Designing an algorithm that gives optimal nutrition using only the farmer's available ingredients was technically complex and required domain expertise.

Accomplishments that we're proud of

Developed a working prototype of FeedWise AI with feed calculations tailored to livestock type, breed, age, and location.

Designed a dynamic feed formulation engine that uses only what the farmer already has in stock.

Created a scalable architecture for including professional vet services, a donation system, and a growing county-level database.

What we learned

Localization matters: Farmers' needs vary significantly across counties — climate, culture, and crop cycles must be considered.

Simplicity wins: Voice interaction and offline support are critical for adoption in low-connectivity areas.

Partnerships are key: Collaboration with agricultural institutions and vets greatly enhances both trust and data quality.

Feed costs are central: Optimizing local feed use can drastically improve profitability for small-scale farmers.

What's next for FeedWise AI :Intelligent Livestock Feed Advisor

Integrated Livestock Disease Diagnosis Add AI-based image and symptom recognition to help farmers detect and manage animal diseases early.

Expansion to the East African Community Adapt the app for Uganda, Tanzania, Rwanda, and beyond, using region-specific data and languages.

Local Offices in All 47 Kenyan Counties Set up physical presence to offer hands-on support, outreach, and field training through agro-partners.

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