FarmFlow AI is an AI-powered agricultural decision-support platform designed to reduce irrigation waste and help farmers make field-specific water-management decisions.
Instead of relying on fixed irrigation schedules, FarmFlow combines field location, soil characteristics, crop and growth stage, weather forecasts, rainfall, agronomic water-demand calculations, and machine-learning predictions to determine whether a field should be irrigated, how much water is needed, and the best time to irrigate.
The platform includes a conversational AI copilot that is grounded in the field's current state and FarmFlow's decision engine. Farmers can ask questions such as “Should I irrigate today?”, “Why should I wait?”, “What happens if there is no rain?”, or “Give me a 7-day irrigation plan.” When a question requires a calculation, the copilot uses FarmFlow's underlying tools and data rather than inventing an answer.
FarmFlow also provides a what-if simulator for changing rainfall, temperature, crop stage, and other conditions, allowing users to see how irrigation recommendations change. An environmental impact engine estimates water saved, pumping energy avoided, CO₂ emissions avoided, and potential cost savings.
The goal is simple: turn agricultural data into actionable irrigation decisions while making water conservation measurable.
Built for NextStep Hacks 2026 under the Earth Forward theme, FarmFlow focuses on sustainable agriculture, water conservation, and climate-resilient farming.
Built With
- fastapi
- llm
- machine-learning
- postgresql
- python
- react
- scikit-learn
- soilgrids
- typescript
- weather-apis