FarmGenie (GeoHack 2024)

Empowering farmers with real-time insights and expert guidance via AI-driven space

• Role: Backend (AI/ML Integration)

• Vision/Goal: In the ever-evolving agricultural landscape, farmers often face challenges in accessing up-to-date knowledge and resources to improve their farming practices. To address this, we have developed a comprehensive product that leverages the power of LLMs as Experts and Agents to create an interactive platform for farmers.

• Solution: Our platform utilizes LLMs and a Mixture of Expert (MoE) approaches to provide precise guidance on soil management, plant disease identification, and irrigation techniques. Built as a scalable web application with a Next.js frontend and backend, and supported by a Redis queue and multiple worker nodes, FarmGenie ensures robust performance. The system’s multilingual support, interactive community forum, and up-to-date knowledge base facilitate seamless, expert-driven assistance for both new and experienced farmers

• Features :

• Seamless Interface
  • Website:
  • Built with Next.js for both client and backend
  • Uses Redis queue and multiple worker nodes for scalability
• Dual Marketplace
  • Input Marketplace: For local sellers and dealers
  • Output Marketplace: For farmers
• Conversational AI Framework
  • Core Technologies: Mixture of Experts (MoE), Retrieval-Augmented Generation (RAG), and language translation
  • MoE Component: Three fine-tuned small language models for soil management, plant disease identification, and irrigation
  • Conversation Management: LLMs handle query classification, conversation flow, and language translation
• Community Forum
  • Website:
  • Facilitates knowledge sharing and peer learning
• Marketplace-Chatbot Framework
  • Technology: Combines Gemini and OpenAI GPT-4o
  • Function: Replaces traditional search with natural language instructions, enhancing user interaction with local retail shops
• Agricultural Schemes Platform
  • Website:
  • Features: Comprehensive database of government schemes, user-friendly interface, regular updates, and informative guides
• Technical Architecture
  • Frontend: Next.js with server-side rendering and static site generation
  • Backend: Next.js, handling request processing through Redis queue and multiple worker nodes
  • Database: PostgreSQL (Neon DB) for storing user, farmer, and retailer data
  • Deployment: Docker containers for consistent deployment
  • Scalability: Managed via Redis queue and worker nodes
  • Security: SSL/TLS encryption, user authentication, and input validation
• Tools:

Project Link