Aimed at Indian farmers and Extension Agents, this copilot uses a collection of documents and transcripts of 100s of videos representing best practices from the Indian Ministry of Agriculture and Digital Green's video transcripts & FAQs to answer common questions from Indian farmers. We load these documents + transcripts into a vector database and with each question, we search the DB and add the results to create an answer to the farmer's questions. Additionally, the copilot features WhatsApp follow-up and location buttons plus agentic web search to get local weather and prices. It also leverages ISDA's Africa soil API to look up soil information based on the user's location.

More info and technical walkthroughs can be found here

DEMO An interactive AI bot that's attempting to guide rural nurses to Nigeria with advice for pregnant mothers based on a PDF of the WHO guidelines (that doesn't hallucinate beyond answers generated from the WHO guidelines either). A collaboration between Gooey.AI and IPRD Solutions.

Read the case study! A multilingual AI chatbot developed by the International Organization for Migration (IOM – Tunisia) and Gooey. AI to help migrants navigate health services in Tunisia.
Please note: this chatbot cannot assist with medical emergencies.

Aimed at Kenyan farmers and extension agents, Farmer.CHAT can analyze crop photos, provide precise weather, price and soil analysis based on the user's lat /long. It understands audio messages in most languages, including English and Swahili. More info and technical walkthroughs can be found here

Compares Gemini3, GPT5.2, KissanAI, LLAMA4 Maverick, Sarvam.AI, GPT4o and AgriLLM (Qwen3) for their responses being similar to our golden QnA of common small shareholder farmer questions and answers (in English) from ClearGlobal and Opportunity Intl. What makes a good golden eval QnA?