This study documented the development and evaluation of a web-based integrated agricultural information and market linkage system with artificial intelligence-powered assistance for multi-sector farmers in Luuka District, Uganda. Smallholder farmers in Luuka District faced chronic challenges in accessing timely and relevant agricultural information, identifying reliable markets for their produce, and receiving expert agronomic guidance all of which contributed to persistent post-harvest losses estimated at 30–40% of total production and suboptimal farm incomes. The study employed a Design Science Research (DSR) methodology, progressing through needs analysis, system design, prototype development, deployment, and evaluation phases. The system was developed using PHP, MySQL, JavaScript, and integrated an AI-powered chatbot using the OpenAI GPT API. System usability was evaluated using the System Usability Scale (SUS) with 45 farmer users and 10 agricultural extension officers. The developed system achieved a SUS score of 78.4 (classified as 'Good'), with particularly high scores for information accessibility (4.32/5) and market linkage functionality (4.18/5). The study concluded that the system significantly improved farmers' access to timely agricultural information and market opportunities, and recommended scaling the platform to additional districts through phased deployment and sustained government and development partner investment.