Vayazh - Leveraging AI and NLP to Empower Farmers with Real-Time Agricultural Insights

Vayazh, an AI-assisted agriculture advisor designed to support beginners, hobbyists, and small-scale agricultural producers in improving decision-making and productivity. The primary objective of this work is to enable accessible, accurate, and context-aware agricultural guidance by integrating domainspecific knowledge with real-time environmental data. Methodologically, Vayazh employs a fine-tuned Retrieval-Augmented Generation model trained on reliable agriculture datasets, covering crop care, pest control, irrigation management, and seasonal planning. The framework integrates real-time weather information to dynamically make suggestions depending on regional conditions like delaying irrigation when there is forecast rain. The most notable findings from early testing are that the integration of conversational AI with formalized farming knowledge and ecological sensing results in enhanced scheduling of tasks, increased user interaction, and greater compliance with ecologically sustainable farming practices. The work adds an AI platform that is scalable, user-focused, and improves agricultural results through proactive, tailored, and contextually associated support.