Abstract

The case study ‘AIBONO: Using AI to Aid Precision Farming’ describes how Vivek Rajkumar (Vivek) built and offered a full-stack agriculture production management platform to synchronize demand and supply in the fresh food segment. Using just in time technologies and farm analytics, AIBONO helped farmers grow crops as per market demand, assisted retailers in sourcing fresh fruits and vegetables directly from the farms throughout the year, and provided end consumers with the best of perishable produce. The case study first touches upon the myriad issues faced by Indian farmers such as low farm yield, inadequate storage facilities, inadequate transport logistics, and lack of an organized structure. Next, the case study describes AIBONO’s business model, beginning with the pilot stage when Vivek, armed with an engineering degree from IIT Madras, got into farming to solve the problems of farmers using digital technologies. Vivek began by farming paddy and banana on his ancestral land. Though he did not make a profit, he gathered a lot of farm data, including the amount of fertilizer and water used, the types of seeds used, etc., and built a digital platform that could provide real-time precision agriculture services to farmers by processing all the parameters on a farm. The case study then describes AIBONO’s initial Farm Management-as-a-Service business model that it implemented in the Nilgiris wherein farmers outsourced measurement, production management, and the decision-making processes to AIBONO. The case then focuses upon how the company scaled up operations to launch the ‘Smart Farming Collectives™’ initiative wherein partner farmers shared AIBONO’s resources and farmed collaboratively for mutual benefit and eventually emerged as a Seed-to-Plate™ company. The case study also brings to light how AIBONO transformed its revenue model over the course of its business evolution. The case study ends by touching upon the company’s future plans of capacity expansion, supplying produce to large organized retail chains, home delivery of perishable produce through last-mile delivery partners, and partnering with more young farmers who are well-versed in using the internet and electronic devices.

Learning Objectives

The case is structured to achieve the following Learning Objectives:

• Gain awareness of major issues impacting the vast Indian agriculture sector
• Examine how digital technologies can help synchronize demand with supply in agriculture
• Learn how supply chains in agriculture can be made lean
• Understand the importance of rapid learning and pivoting for start-ups
• Learn about the challenges that fresh food aggregators might face in India

Keywords

Supply Chain Management; Demand and Supply; Agriculture Technology; Predictive Analytics; Shared Economy; Logistics management; Entrepreneurship Development; Digital Technologies; Lean Supply Chain; Distribution Channel Members; Agricultural Economy