Calice is an Argentine agtech building AI models that simulate crop field trials in silico, helping seed companies test how new varieties will perform without running every experiment in real fields. Its NODES platform combines genetics, climate data, soil parameters, and growing conditions to forecast yield, stress tolerance, and other traits across geographies — reportedly cutting the number of physical field trials needed by up to 80% and shortening time-to-market for new varieties by up to 50%.
The technical core blends mechanistic crop models with machine learning fit on the seed company's own historical trial data, satellite imagery, and environmental layers. Calice reports its predictive models reach over 90% accuracy versus field outcomes on proof-of-concept projects for crops including soy, maize, barley, and rice.
Calice was founded in 2022 by Ramiro Olivera, Esteban Hernando, Andrés Rabinovich, and Pablo Romero, and is headquartered in Buenos Aires with a commercial office in San Francisco to support engagement with US and global seed companies.
In May 2025 Calice closed a $2.5M seed round led by Astanor Ventures — the Brussels-based food and ag impact fund managing roughly €1B — with participation from Draper Cygnus, Xperiment Ventures, AIR Capital, Innventure, and GrainCorp Ventures. The capital is being used to expand the data science team, deepen integrations with seed-company breeding pipelines, and extend coverage to additional crops and geographies.
Calice's differentiator is the combination of agronomic depth, multi-region data coverage, and an in-silico product that targets a clear ROI line item — the cost and time of physical breeding trials. Its risk is the same as any biology-meets-AI startup: predictions must hold up across novel conditions and earn trust from conservative breeding organisations.