{"id":79319,"date":"2026-06-19T09:49:07","date_gmt":"2026-06-19T09:49:07","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/79319\/"},"modified":"2026-06-19T09:49:07","modified_gmt":"2026-06-19T09:49:07","slug":"agmri-ai-agent-now-in-use-for-field-level-agronomic-decisions","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/79319\/","title":{"rendered":"AGMRI AI Agent Now in Use for Field-Level Agronomic Decisions"},"content":{"rendered":"<p>INDIANAPOLIS, IN.\u00a0\u2013 Intelinair has launched the AGMRI AI Agent, an AI capability inside the AGMRI platform that lets agronomic advisors and growers ask questions and receive field-level answers in seconds. Now live, the AGMRI AI Agent is built on the agronomic data already in AGMRI: multi-source imagery, soil characteristics, weather, input applications, field boundaries, and historical yield outcomes.<\/p>\n<p>The AGMRI AI Agent is purpose-built for agronomy, not adapted from a general-purpose AI tool. Advisors and growers are using it to ask questions such as \u201cWhich hybrids performed best on my high-productivity ground last season?\u201d or \u201cWhere should I prioritize replant across these fields?\u201d and receive answers grounded in their own data, eliminating hours of manual report pulling and cross-referencing.<\/p>\n<p>\u201cAgriculture has never had a shortage of data; it has had a shortage of time,\u201d said Conner Schmidt, Commercial Leader of Intelinair. \u201cAdvisors are managing hundreds of grower accounts, and every recommendation carries weight. The AGMRI AI Agent gives them a way to surface the right insight on the right acre, instantly, without sacrificing the agronomic rigor behind it, and teams are already putting it to work this 2026 crop season.\u201d<\/p>\n<p>What the AGMRI AI Agent does<\/p>\n<p>Agronomic advisors and growers are using the AGMRI AI Agent across five core use cases:<\/p>\n<p>  Hybrid placement and performance: Identifies which hybrids perform best by county, soil type, or productivity zone, and how to manage them in the coming season. In-season decision support: Pairs current crop and weather conditions with historical performance to guide replant, nitrogen timing, and fungicide application. Reports and grower deliverables: Generates field reports, summaries, and shareable documents directly from the conversation. Trial data analysis: Performs comparative analysis of trial results across environments, hybrids, and management practices. Breakeven and profitability analysis: Calculates breakeven yield at the field or hybrid level, factoring in land, machinery, seed, chemical, and fertility costs.  <\/p>\n<p>Availability<\/p>\n<p>The AGMRI AI Agent is live now and integrated directly into the AGMRI platform for all AGMRI customers. To learn more or request a demonstration, visit<a href=\"http:\/\/intelinair.com\" rel=\"nofollow noopener\" target=\"_blank\"> intelinair.com<\/a>.<\/p>\n<p>About Intelinair<\/p>\n<p>Intelinair is the Indianapolis-based agtech company behind AGMRI, a cloud-based agronomic intelligence platform that integrates imagery, weather, soil, input, and yield data to deliver field-level insights to growers, agronomists, and advisors across millions of acres. Learn more at<a href=\"http:\/\/agnewscenter.org\/r\/9c7473b4bd462641b6ff13d22?ct=YTo2OntzOjY6InNvdXJjZSI7YToyOntpOjA7czoxNDoiY2FtcGFpZ24uZXZlbnQiO2k6MTtpOjIwNDt9czo1OiJlbWFpbCI7aToyMjI7czo0OiJzdGF0IjtzOjIyOiI2YTMzOWQ2MDMyYzVjODQxMzE0Mjk1IjtzOjk6InNlbnRfdGltZSI7aToxNzgxNzY3NTIwO3M6NDoibGVhZCI7czo2OiI1MzIyNDIiO3M6NzoiY2hhbm5lbCI7YToxOntzOjU6ImVtYWlsIjtpOjIyMjt9fQ%3D%3D&amp;\" rel=\"nofollow noopener\" target=\"_blank\"> intelinair.com<\/a>.<\/p>\n<p style=\"text-align: right;\">\u2013 <a href=\"https:\/\/agpr.com\/\" rel=\"nofollow noopener\" target=\"_blank\">AgPR<\/a><br \/>The news release distribution service for agriculture<\/p>\n","protected":false},"excerpt":{"rendered":"INDIANAPOLIS, IN.\u00a0\u2013 Intelinair has launched the AGMRI AI Agent, an AI capability inside the AGMRI platform that lets&hellip;\n","protected":false},"author":2,"featured_media":79320,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[405,7537,35459,43228,35460,134],"class_list":["post-79319","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-ai-agents","tag-artificial-intelligence-agents","tag-corn","tag-soil-science","tag-soybeans","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/79319","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=79319"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/79319\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/79320"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=79319"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=79319"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=79319"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}