Enterprise Knowledge Search
Bayer needed to help agronomists and other farmer-facing employees answer agronomy, farm management, and Bayer product questions more quickly and accurately, while simplifying crop protection decisions amid regulatory, sustainability, and cost pressures affecting farmers.
Reported impact
Bayer reports that E.L.Y. is improving employee productivity and response quality, helping frontline teams deliver faster and more accurate answers to farmers and agricultural customers while increasing user confidence in crop protection decisions.
Bayer built E.L.Y. (Expert Learning for You), a domain-specific generative AI assistant for its Crop Science organization, to give agronomists and other frontline staff faster access to vetted agronomic knowledge. The system combines Bayer's agronomic intelligence, product knowledge, and continuously refreshed agricultural information, then validates responses with Bayer agronomists to improve accuracy and compliance. For crop protection, Bayer and Microsoft developed E.L.Y. Crop Protection as a specialized agriculture-domain small language model based on Microsoft's Phi-3 SLM and made it available through the Azure AI model catalog. In practice, employees submit prompts about agronomy, farm management, and crop protection, the model generates contextually relevant answers, and Bayer's automated update processes keep the knowledge base current so teams can deliver faster, more accurate guidance to advisors, farmers, and agricultural customers.
Bayer feeds its agronomic intelligence, Bayer product knowledge, and updated agricultural information into E.L.Y., where Bayer agronomists continuously validate output quality. Prompts from frontline employees are answered by the domain-tuned assistant, and the E.L.Y. Crop Protection variant, built on Microsoft Phi-3 SLM and available through the Azure AI model catalog, serves crop-management guidance to advisors and farmers.
"Additionally, frontline employees report time savings of up to four hours per week, demonstrating how E.L.Y. has accelerated response times and improved customer interactions."
"Bayer has achieved over a 40 percent improvement in answering questions accurately compared to initial testing with ChatGPT."
"Continuously validated by Bayer agronomists, E.L.Y. is already enhancing productivity for over 1,500 frontline employees in the United States."
"Developed by the Crop Science division at Bayer in collaboration with Microsoft, E.L.Y. Crop Protection is a specialized Ag Domain small language model (SLM) based on Microsoft's Phi-3 SLM and is available on the Azure AI model catalog."
"Earlier this year, Bayer announced a pilot that utilizes generative AI (GenAI) to upskill agronomists and other farmer-facing employees, enabling them to quickly and accurately address questions related to agronomy, farm management, and Bayer agricultural products."
"Focus group testing indicates that 90 percent of E.L.Y.'s users are willing to continue using it and recommend it to a colleague."
"This new domain-specific GenAI model, called E.L.Y. (Expert Learning for You), positions Bayer as an agri-food frontrunner in developing contextually relevant and compliant responses to user prompts."
"To ensure high accuracy, the team has implemented automated processes to keep the system updated with the latest agricultural information."
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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