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Top San Diego, CA Agriculture Companies (4)

Artificial Intelligence • Hardware • Internet of Things • Machine Learning • Agriculture
San Diego, California, USA
29 Employees

Livestock farms produce 30% of the protein in the global diet and contribute to the jobs of 1.7B people. Vence's platform is helping the industry become more efficient and productive while helping the environment at the same time. We reduce the cost of sustainably raised meat by eliminating the need for both infrastructure (fences) and labor on livestock farms while giving customers real-time control of animals at the same time. Our AI/ML also provides farmers with additional insight into animal behavior, health and fertility.


Biotech • Agriculture
San Diego, California, USA
25 Employees

Cellibre is a best-in-class manufacturing technology company.. Employing an organism-agnostic approach, we turn cells into specialized, sustainable factories for the manufacture of globally significant products at scale. Our world-class scientific team has led programs from napkin to commercial, pioneering revolutionary breakthroughs in energy, ingredients, medicines and more.


Biotech • Agriculture
San Diego, California, USA
74 Employees

The Center for Aquaculture Technologies (CAT) is at the leading edge of genetic innovation within the aquaculture industry. Employing strategies that are both results-oriented and designed for maximum value, CAT provides advanced genetic services that enhance profitability while upholding sustainable practices.


Robotics • Software • Analytics • Agriculture
San Diego, California, USA
13 Employees

SlantRange remote sensing and analytics systems deliver the data that drives precision agriculture. We provide a comprehensive, highly scalable, and patented crop data system that accurately collects and processes remotely sensed data, performs advanced analytics, and quickly visualizes and surfaces actionable insights for input suppliers and growers alike. Our solution is flexible and has been adapted to the specific information needs and operational constraints of some of the most challenging data problems in agriculture.