The agritech industry in Bangladesh is undergoing a notable change, driven by new technologies and creative startups. Recent developments highlight the country’s commitment to modernizing agriculture, ensuring sustainability, and empowering smallholder farmers.
Sayed Zubaer Hasan, who started Krishi Shwapno, has made it onto Forbes’ 2025 list of ’30 Under 30 Asia’ due to his impact on agritech in Bangladesh. Krishi Shwapno offers a comprehensive solution for smallholder farmers, encompassing pre-harvest planning, soil testing, climate-resilient practices, and direct market access. By integrating technology with grassroots initiatives, the startup aims to transform farming from a subsistence activity into a sustainable enterprise.
On May 25, 2025, the Bangladesh Agro Conclave 2025 was held at Amari Dhaka, co-hosted by LightCastle Partners and the Sustainable Agriculture Foundation Bangladesh (SAF Bangladesh). The event served as a national platform to address systemic challenges and opportunities in Bangladesh’s agriculture sector, focusing on global competitiveness, technology adoption, and inclusive growth. Dr. Mohammad Emdad Ullah Mian, Secretary of the Ministry of Agriculture, emphasized the need for inclusive digitization in agriculture, stating, “Modern precision agriculture must be integrated coherently with our socio-economic scenario—we cannot leave our root-level farmers behind”.
iFarmer, a leading agritech company in Bangladesh, recently secured a $500,000 loan from the Pioneer Facility, an impact fund managed by Nexus for Development. This investment aims to provide critical working capital to iFarmer, enabling it to procure agricultural produce from smallholder farmers and purchase essential agricultural inputs directly from manufacturers. By bridging the gap between farmers and suppliers, iFarmer helps improve yields, enhance incomes, and promote sustainable agriculture practices. The Bangladesh Agricultural Research Institute (BARI) has developed an AI model designed to detect plant diseases at an early stage. Utilizing image recognition and machine learning, the system can accurately identify signs of disease in crops such as rice, jute, and vegetables, often before they become visible to the human eye. This innovation has the potential to safeguard millions of farmers’ livelihoods by enabling timely interventions .
