Agriculture-Centric AI Development

How Gooey.AI works with Agricultural Institutions

Gooey.AI partners with agricultural institutions, NGOs, and governments to digitize and scale agricultural advisory. We help institutions transform their existing, trusted knowledge, such as extension manuals, research PDFs, training videos, and advisories, into multilingual AI agents that farmers can access through familiar channels including WhatsApp, and IVR-based agents for non-smartphone users. Our agriculture AI workflows have been used by 10,000s of farmers in Kenya, India, Ethiopia and Rwanda, enabling our partners to quickly reach farmers and agricultural extension agents in their own language.
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The core problems we solve are scale, cost, and relevance. Traditional extension systems struggle to serve large, diverse farmer populations and often deliver generic or delayed advice. Gooey.AI enables institutes to:
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- Reach tens of thousands of farmers at roughly one-tenth the cost of traditional extension
- Deliver specific guidance grounded in verified sources
- Integrate real-time data such as weather, farmer profiles, and market signals for timely, contextual recommendations
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Finally, Gooey.AI strengthens institutional learning by closing the feedback loop between farmers and extension providers. Our analytics dashboards quickly identify user cohorts based on location, gender and crop to analyze and categorize conversations for feedback and evaluation. Our API connectivity and function support enable partners to connect real-time weather and profile data to the finest frontier LLMs and language models.This two-way, data-driven approach enables agricultural institutes to improve extension quality, demonstrate impact, and support better farmer outcomes at scale.

Read more about the impact of our work:

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AI in Agriculture Recommendations for Global Impact Orgs

Watch our founder Sean Blagsvedt share insights from the AI Agriculture Landscape, covering architectures, evaluations, and investment recommendations for global impact organizations. He outlines how AI can be scaled responsibly to meaningfully serve smallholder farmers worldwide and help them thrive.

"With Gooey, we built in a day what our internal team had been working on for 3 months."
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"We had 3 developers working 3 months on an agriculture chatbot for Malawi farmers. In an afternoon, we were able to push our authoritative agronomy extension content into Gooey.AI and usability test a hallucination-free, multilingual WhatsApp RAG bot - with page-level citations, built-in speech recognition, analytics and evaluation."

Paul Essene

Senior Director Product & Technology Innovation @ Opportunity International
LinkedIn
Partnered with us
Agricultural Theory of Change

Case Studies - Embracing Participatory and Inclusive Processes

Case study

Transforming Smallholder Farming in Malawi and Kenya with Farmer.AI

FarmerAI is a multilingual, AI-powered agricultural advisory chatbot built by Gooey.AI in partnership with Opportunity International to support smallholder farmers in Kenya, Malawi, and Ghana. Accessible via WhatsApp, SMS, voice notes, and images, FarmerAI delivers on-demand, localized farming advice grounded in vetted agricultural knowledge, helping farmers get timely guidance on crops, livestock, and inputs—often reducing wait times from days to seconds.

Case study

Farmer.Chat: Making Vetted Agricultural Knowledge Accessible Through AI

Farmer.Chat is a multilingual, AI-powered farmer advisory service built by Gooey.AI and Digital Green to deliver trusted, hyperlocal agricultural guidance to smallholder farmers via WhatsApp, voice, and web. Grounded in vetted extension content and farmer knowledge, it enables farmers to ask questions in their own language and receive real-time, practical advice on crops, inputs, and climate challenges, bridging critical gaps in access to agricultural expertise.

Case study

Building Inclusive Agricultural AI with the Gates Foundation

Gooey.AI partnered with the Gates Foundation to tackle the challenge of building AI that works for low- and middle-income farmers in low-resource settings. By developing and evaluating speech, data, and AI pipelines and deploying advisory bots on WhatsApp and non-smartphone devices, Gooey helped scale agricultural AI in the field. This work has reached roughly 168,000 users across Farmer.Chat, DigiFarm, and Malawi, while also shaping ecosystem-wide decisions on where to invest for impact.

Agriculture Evaluation of LLMs

As part of our work with the Gates Foundation, we assessed the performance of leading LLMs on agricultural intelligence by comparing their responses to a golden Q&A set of common smallholder farmer questions. Models including Gemini 3, GPT-5.2, KissanAI, LLaMA-4 Maverick, Sarvam.AI, GPT-4o, and AgriLLM (Qwen-3) were evaluated against expert-validated English datasets from Clear Global and Opportunity International.

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