Farmers Guild

Note: Mock data is shown on the landing page as the app is not yet live.
dashboard
crop management tools
market analysis
disease detection

Inspiration

Farmers face major challenges unpredictable weather, fluctuating market prices, and limited access to expert advice. We built Farmers Guild to empower them with AI-driven insights, real-time data, and digital tools that make smart, data-backed farming decisions easy.

What it does

Farmers Guild is an AI-powered smart farming platform combining crop management, market analysis, weather forecasting, and disease detection.
Farmers can:

Manage and track crops through a modern dashboard
Get AI-based advice specific to each crop and growth stage
Detect plant diseases using computer vision
Access real-time government market prices and insights
Monitor expenses, ROI, and activities
Real-time market prices insights from government API

How we built it

Frontend: React + Vite, TailwindCSS
Backend: FastAPI with PostgreSQL
AI: LangChain + OpenRouter (Grok, DeepSeek)
APIs: OpenWeather, Government Market Price API
Infra: Docker & Docker Compose for containerization

Challenges we ran into

Designing persistent AI memory per crop and user
Merging multiple APIs (weather, market, AI)
Creating a fast, responsive UI that stays lightweight
Handling complex database relationships efficiently

Accomplishments that we're proud of

Developed an AI-powered crop management system that understands user activity and adjusts advice dynamically
Built a context-aware AI assistant that connects with disease data, crop logs, weather forecasts, and cost tracking for holistic recommendations
Integrated AI disease detection with confidence scoring and preventive suggestions
Designed a modern, dashboard that visualizes farm data intuitively
Combined real government market data with AI-driven insights for smarter crop selling decisions
Achieved containerized, scalable deployment using Docker and FastAPI

What we learned

we learned to manage stateful AI conversations, design for scalability, and use real-world data to make AI genuinely useful for farmers. Balancing technical depth with usability taught us how to build AI that truly serves people.