Over the past 15 years, Digital Green has been dedicated to solving this problem through digital agricultural extension. Working with the Ministries of Agriculture in India, Ethiopia, and Kenya, Digital Green has created nearly 8,000 farmer-to-farmer training videos in more than 50 languages, enabling extension agents to provide timely, locally-relevant information to more farmers. These videos have increased farmer income by an average of 24 percent.

Digital Green saw a chance to make an even bigger difference in farmers’ lives by harnessing generative AI. “With videos, we’ve been able to replicate success from farm to farm within a region, enabling farmers to learn from one another—while also growing a database of locally-derived agricultural best practices,” said Rikin Gandhi, CEO of Digital Green. “With OpenAI, we saw an opportunity to leverage this database to help farmers learn from one another at a previously unimaginable scale.”

With this vision in mind, Digital Green began developing Farmer.Chat on top of OpenAI’s technology suite. The first Farmer.Chat pilot was built on GPT‑4, which significantly reduced hallucinations⁠ relative to previous models. Farmer.Chat uses Retrieval Augmented Generation (RAG) to integrate Digital Green’s vast library of agricultural information with those of government partners, including training video transcripts, annotated call center logs, and crop research factsheets. India’s Ministry of Agriculture validates all documents in the knowledge base to ensure accuracy and reliability.

Additional precautions were built into the initial rollout. “To safeguard against the risk of the chatbot advising farmers in error, we carefully curated the chatbot’s knowledge base and deployed the chatbot as an assistant to extension agents, rather than deploying the chatbot directly to farmers. This enables another stage of human review,” Gandhi shared.