AI-powered agricultural intelligence · Davis, California

Turning years of academic research into crop-nutrient science the industry and humanity can use.

We process the agricultural literature and data. AI extracts claims, maps nutrient–crop relationships, and scores the evidence. We then bench validate it and build the AI foundation model for deep understanding and growing any produce.

5894 Claims

17839 Papers

87 Crops

90 Nutrients

01 The Engine 22,500+ research papers scanned by multiple AI models. Findings structured as cultivar × parameter × nutrient × outcome. UC Davis faculty review the top results. Enter the engine 02 The Process Scan papers. Extract claims. Resolve conflicts. Validate at the USDA-ARS lab. Loop. See the pipeline 03 The Position Specific cultivars, measured growing conditions, measured nutrient outcomes. Cultivation protocols for growers. See findings