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MahaVISTAAR

MahaVISTAAR

India flag

India

Agriculture

High replicability and adaption

Implementing Organisation

OpenAgriNet (OAN)

India, Karnataka, Bengaluru

Other

Implementing Point of Contact

Kirti Pandey

Mission Director

Contributor of the Impact Story

OpenAgriNet (OAN)

Year of implementation

2024

Problem statement

India-s agricultural ecosystem is characterised by fragmented service delivery, siloed digital platforms, and uneven access to timely, localised information. Smallholder farmers, often operating in low-connectivity environments and across multiple regional languages - face barriers arising from limited digital literacy, language diversity, and reliance on informal advisory channels. Existing solutions remain platform-bound and difficult to scale, resulting in duplicated efforts and inconsistent service quality. These structural gaps highlight the need for interoperable digital infrastructure that can enable coordinated, inclusive, and scalable agricultural services.

Impact story details

OpenAgriNet (OAN) is a global, open network initiative, designed using DPI principles, combining open-network architecture, AI-enabled advisory, and institutional integration (e.g., identity, farm registries, schemes, markets) to support interoperable agricultural services. It brings together public digital infrastructure initiatives, governments, technology providers, and philanthropic organisations to build shared protocols, AI-enabled tools, and digital public goods that support agricultural services at scale. OAN is designed as an enabling layer rather than a single platform, allowing multiple implementations across contexts.

AI Technology Used

Machine Learning
Natural Language Processing
Speech Recognition
Generative AI
AI agents for information retrieval
orchestration
Multilingual language models

Key Outcomes

Other - Demonstrated ability to deliver interoperable, AI-enabled agricultural services at scale through a networked model rather than a single platform.

Impact Metrics

Implementation Context

Scaled

India (multiple states including Maharashtra, Bihar, Assam, Andhra Pradesh, and Karnataka), with pilots and planned deployments in Ethiopia and exploratory engagements in Rwanda, Nigeria, and Kenya.

Small and marginal farmers across Maharashtra, spanning multiple agro-climatic zones and over 50 crop types. The use case is designed for rural and semi-rural farmers, including those with limited literacy and digital access, and supports multilingual, voice-first interaction in Marathi, Hindi, and Telugu.

Key Partnerships

Government (Ministry of Agriculture & Farmers Welfare, State of Maharashtra), IndiaAI, Bhashini, OpenAI, AI4abharat NVIDIA, Philanthropic support - EkStep Foundation, Gates Foundation

Replicability & Adaptation

High

Proven across multiple state deployments in India with additional international pilots underway, using a modular, interoperable architecture that reduces dependence on local platform rebuilding.

Supporting Materials

* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.