Agriculture Information Exchange Platform

Empowering smallholder farmers through inclusive AI solutions

The Agriculture Information Exchange Platform (AIEP) empowers smallholder farmers with high-quality advisory services. Developed by GIZ/BMZ Fair Forward and funded by the Gates Foundation, four Minimum Viable Products were tested with farmers and extension workers in Kenya and Bihar, India. These products used emerging technologies such as AI, inclusive design, and multi-channel approaches to address farming concerns such as crop planting, climate issues, and value chains. The platforms also provide guidance in local languages to improve access and adoption by farmers and extension workers.

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Why do we need agriculture information exchange platform?

Smallholder farmers in low and middle-income countries encounter significant challenges, leading to a decrease in productivity and profitability. The existing agricultural landscape poses obstacles such as:

The current support systems, particularly through extension services, are not effectively reaching and benefiting smallholder farmers at the required scale. The ratio of public extension workers to farmers is far higher than the recommended ratio of 1:100, ranging from 1:500 to 1:5000.
The cost of adopting new agricultural practices is prohibitively high, ranging from 16 to 35 dollars. While the existing digital farmer advisory services often lack access to high-quality, diverse, personalized, and dynamic information. These services also lack the capacity for two-way communication and customized channels tailored to smallholder farmers.

Smallholder farmers do not receive the right information at the right time in the right format and have limited options to ask technical questions, and together, with farmers, we can improve this!

Digital advisory solutions: transforming agriculture

Farmers in low and middle-income countries face challenges accessing effective advisory information, with only 47% currently receiving the services they need despite the availability of hundreds of digital solutions. Existing platforms often fail to address the needs of end users, particularly women and marginalized groups, due to gaps in dynamic, personalized, and automated content. To bridge this gap, the AI-based platform focuses on user-centered design, reducing barriers to adoption by offering services in local languages, tailored to specific contexts, and accessible to diverse users. This approach prioritizes reducing the gender and digital divide, empowering farmers to overcome challenges and improve their livelihoods.

Our approach

To realize this platform, GIZ Fair Forward, the Gates Foundation and four cohorts (see below) will develop four Minimum Viable Products (MVPs) for agricultural information exchange platforms in Kenya and Bihar, India. Until the end of 2024, these MVPs will be tested to serve low-literacy and low-digital-skill smallholder farmers, extension officers, and other intermediaries, with a special focus on women and marginalized groups. This platform will utilize newly available artificial intelligence (AI) and ML models, working in local languages and integrating data and technology assets from content and solution providers.

Cohorts are collaborative groups of diverse partners working together to develop MVPs.

Meet our four cohorts

Focused on rice, wheat, and maize, DynAG’s platform leverages a Retrieval-Augmented Generation (RAG) pipeline powered by Large Language Models (LLMs) like the GPT suite to deliver advisory services to farmers. The platform is accessible through chatbots, Android and Jio-based mobile applications, Interactive Voice Response (IVR) systems, and Short Message Service (SMS), ensuring broad accessibility. Equipped with machine translation and speech recognition capabilities, it supports communication in both English and Hindi, while utilizing the Consortium of International Agricultural Research Centers (CGIAR)’s data backbone for precise, data-driven insights.
Digital Green’s platform supports agricultural value chains such as dairy, coffee, and wheat in Bihar, India, and Kenya. It incorporates a Retrieval-Augmented Generation (RAG) pipeline, leveraging Large Language Models (LLMs) under evaluation, and delivers services via a mobile application, Telegram, and Interactive Voice Response (IVR). Key features like machine translation, speech technology, image recognition, and integration of weather data enable localized and actionable insights. The platform supports multiple languages, including Hindi, Swahili, Gikuyu, and Marathi, ensuring adaptability and accessibility across diverse regions.
This platform targets farmers in Kenya and Bihar, focusing on beans and wheat, respectively. It utilizes Interactive Voice Response (IVR), Short Message Service (SMS), and WhatsApp, built on a Retrieval-Augmented Generation (RAG) pipeline powered by Large Language Models (LLMs), with potential for intent and entity recognition. Features like machine translation and speech-enabled IVR support English, Hindi, and Swahili, ensuring accessibility across diverse regions. The initiative is part of a larger effort to advance voice technology for agricultural advisory services.
Tech for Her empowers women farmers in Bihar, India, and Kenya by focusing on tomatoes and cattle. The platform is accessible through Interactive Voice Response (IVR), WhatsApp, and a mobile application, leveraging Large Language Model (LLM)-powered intent and entity recognition for personalized chatbot interactions and speech-enabled IVR for voice support. AI-based video generation enhances engagement, providing tailored content. Available in English, Hindi, and Swahili, it addresses the unique needs of women in agriculture, fostering inclusivity and empowerment.

Key features of the platform

Who are the end users?

Our primary focus is on supporting users in Kenya and Bihar, India; especially:

Smallholder Farmers: These individuals are the backbone of agriculture, and we aim to provide them with trusted and personalized content directly.
Intermediaries: Those individuals who play a crucial role in connecting smallholder farmers to relevant information and services.
Extension Officers: A key group in the agricultural ecosystem, where our goal is to enhance their capabilities and service delivery models, especially addressing challenges such as gender representation among extension workers.

As digital technology grows, women and farmers with low literacy and digital skills risk exclusion from valuable information. Enhanced agricultural information exchange platforms can address this by delivering trusted, personalized content to farmers, supporting extension officers, and empowering women with tailored services.

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Who is behind this?

FAIR Forward – Artificial Intelligence for All Driven by the Deutsche Gesellschaft für Internationale Zusammenarbeit – GIZ’ and funded by Federal Ministry for Economic Cooperation and Development– BMZ strives for a more open, inclusive, and sustainable approach to AI on an international level.

Gates Foundation Guided by the belief that every life has equal value, the Gates Foundation works to help all people lead healthy, productive lives.

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