Agriculture remains a vital pillar of economic stability across many developing regions, yet smallholder farmers often face significant barriers in accessing timely and reliable expert guidance. The resulting knowledge gap between large agribusinesses and small-scale farms contributes to reduced yields, inefficiencies, and greater vulnerability to climate change and pest outbreaks. Addressing this challenge, this study introduces an AI-powered, real-time consultation platform designed to bridge the agricultural knowledge divide. Developed using the MERN stack (MongoDB, Express.js, React.js, Node.js) and enhanced by Firebase microservices, the system integrates live video consultations via WebRTC with AI-driven insights generated by OpenAI’s advanced natural language processing models. The platform enables farmers to connect directly with agricultural experts while receiving personalized, AI-based recommendations tailored to specific crops, diseases, and environmental conditions. With an emphasis on scalability, low-latency performance, and user accessibility, the system aims to democratize agricultural expertise and strengthen decision-making at the farm level. This paper details the platform’s architecture, implementation, and field validation, highlighting its potential to transform traditional agricultural advisory services and empower smallholder communities through intelligent, real-time support.

Keywords: Agricultural Advisory Systems, Artificial Intelligence (AI), Real-Time Consultation, Smallholder Farmers, Natural, Language Processing (NLP), Knowledge Gap Bridging