AgroAskAI: A Multi-Agentic AI Framework for Supporting Smallholder Farmers Enquiries Globally

📝 Original Info

• Title: AgroAskAI: A Multi-Agentic AI Framework for Supporting Smallholder Farmers Enquiries Globally
• ArXiv ID: 2512.14910
• Date: 2025-12-16
• Authors: Nadine Angela Cantonjos, Arpita Biswas

📝 Abstract

Agricultural regions in rural areas face damage from climaterelated risks, including droughts, heavy rainfall, and shifting weather patterns. Prior research calls for adaptive riskmanagement solutions and decision-making strategies. To this end, artificial intelligence (AI), particularly agentic AI, offers a promising path forward. Agentic AI systems consist of autonomous, specialized agents capable of solving complex, dynamic tasks. While past systems have relied on single-agent models or have used multi-agent frameworks only for static functions, there is a growing need for architectures that support dynamic collaborative reasoning and context-aware outputs. To bridge this gap, we present AgroAskAI, a multi-agent reasoning system for climate adaptation decision support in agriculture, with a focus on vulnerable rural communities. AgroAskAI features a modular, rolespecialized architecture that uses a chain-of-responsibility approach to coordinate autonomous agents, integrating realtime tools and datasets. The system has built-in governance mechanisms that mitigate hallucination and enable internal feedback for coherent, locally relevant strategies. The system also supports multilingual interactions, making it accessible...

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