What Makes Cropin The Evident Winner Of The World Bank’s Agri Risk Innovation Challenge?


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Agriculture in Africa holds immense potential to overcome global food insecurity. It is not only the primary source of income and livelihood for nearly two-thirds of the continent’s population, but agriculture is also a significant contributor to the GDP. However, the disruptive effects of climate change have increased the risk of natural disasters. Extreme droughts have made it difficult for the farmers to cultivate crops, or even manage livestock, and unpredictable weather patterns have resulted in crop failures. The 2019 Synthesis Report on the State of Food and Nutrition Security and Vulnerability in Southern Africa estimated that approximately 41.2 million people were food insecure in 13 Southern African countries in the 2019/20 year.

With the objective to address and mitigate agriculture and food security risks in the South Africa Development Community (SADC), the World Bank recently announced three Agriculture Risk Innovation Challenges in association with Draper University. These challenges called for innovations that harness advanced technologies to collect and monitor datasets and indices that will enable the analysis of the impact of agri-stressors based on their different parameters.

In the challenge that brought together participants from 33 countries and a total of 120 proposals, Cropin emerged as the winner of the Bring your Own Agriculture Data challenge, the goal of which was to present a time series of agri-data, including yield, price, and production data for crops that are relevant to the SADC region in an electronic format.

Cropin’s digital innovation has proven to be an effective and smart solution to capture diverse datasets that aid in data-driven decision-making for various actors in the agri-ecosystem. This data on Cropin’s B2B platform empowers agribusinesses, governmental entities, financial institutions, NGOs, and development agencies to optimize their farming and business operations.


Cropin’s innovative solutions are strengthened by its capabilities of live reporting, analysis, interpretation, and insight that span across geographies. The multi-stakeholder platform delivers decision-making tools to ensure consistency, dependability, and sustainability to the actors at different levels of the hierarchy.

Cropin has partnered with several notable organizations in Southern Africa to digitally empower over 165,000 farmers who cultivate some of the prominent crops in the region such as cassava, cashew, and cotton. Cropin’s ICT-driven data collection enables organizations to create digital profiles of farmers based on their primary demographic and socioeconomic details, and also capture farm- and crop-specific details from sowing to harvest.

Field agents appointed by the organization capture farm-level data such as acreage and the exact location of the plot, the crop variety being cultivated that season, the harvest date and estimated yield, and the price that the farmer receives at scheduled intervals throughout the cropping season. Since the data captured by extension workers in an agribusiness or by aggregators of out-growers is based on actual observations at the ground level, it is highly accurate and reliable. As a result, authorized stakeholders will have access to a rich data pool with relevant information to create models for credit risk assessment.


The data collection is done through various survey forms using Cropin’s mobile application. These forms can be customized to the needs of the organization and made available in the local language for ease of use. The use of forms also ensures that the data is complete, cleaned, and ready to be used for analysis.

The availability of such accurate ground data has enabled Cropin to develop crop signatures that are region-specific. These signatures can then be used in proprietary algorithms to detect crops, calculate the acreage for each crop variety, and estimate the yield for each plot in a large region using satellite image analysis. Data of this nature captured across distinct geographies from over 6.1 million acres of farmland, which amounts to a total of over 0.2 trillion data sets, facilitates Cropin to train its AI/ML models. The repeated training and sanitizing of these crop models make it possible for Cropin to deliver accurate and reliable insights for 386 crops and 9,400+ crop varieties across 52 countries.

The regional level information delivered by Cropin can thus be used by financial institutions to understand crop growth patterns and assess the possible risk of crop failure. This availability of alternate agri-data reduces the need for manual appraisal of the farm and the farmer and also streamlines credit underwriting processes for financial institutions. The SaaS platform establishes the current and historical performance of every pixel at a regional level, which further assists lending institutions to hedge risks and arrive at informed business decisions.

Explore Cropin’s capabilities for your agribusinesses further. Get in touch with us today.

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Cropin Apps

Applications for

Cropin Apps is an integrated portfolio of highly customizable apps and solutions that capture and digitise agri-data from the farm to the warehouse to the fork. These applications are designed to scale digital transformation across agriculture and allied industries including forestry, commodity, banking and insurance.


ML-ready data pipelines for enhanced analytics

Cropin Data Hub is designed to deliver the power of unified data by enabling interfacing with all agri-data sources from on-the-field farm management apps, IoT devices, mechanization data from farming resources, drones in agriculture, remote sensing satellite information, weather data, and many more.                                                      


Access to field-tested machine learning models

Cropin Intelligence enables access to over 22 of Cropin’s contextual deep-learning AI models to help agri-businesses with insights and predictive intelligence. Built using the world's largest crop knowledge graph, these models have been field-tested and deployed worldwide while being fine-tuned to work with a range of specific crop varieties, conditions, and locations.

Prakhyath Hegde

About the Author

Prakhyath is the Senior Director of Technology at Cropin and has over 17 years of experience building large-scale software products from inception to commercialization. He enjoys understanding customer challenges and solving them by putting together technology, and he is adept at both bootstrapping and expanding new tech teams to high proficiency. Prakhyath is the author of multiple scholarly articles published by the IEEE and holds four international patents.