Leading provider of agricultural analytics, Sentera, has expanded its Series C funding round. The round was led by Conti Ventures and S2G Ventures. Sentera expects to have fully funded its capital requirements following this round.
The Sentera data science ecosystem combines aerial data collection with machine learning engines to provide more accurate plant-level measurements and insights. In addition to providing essential data to validate outcomes, augment product development, and support sustainability initiatives, its customers, including agriscience leaders in research and product development, can advance their work.
The company serves customers in more than 45 countries and has experienced 40% year-over-year growth driven by its innovative data capture technology, advanced machine learning, digital phenotyping, and localized data models.
Brian Wenngatz ,Sentera's CEO said "Our data science ecosystem gives us unique tools and flexibility that our customers need to drive innovation through their product development roadmaps – whether it's developing the next-best biological, using precision data to transform product application, or unlocking precision weed chemistry with a solution that benefits everyone in the value chain."
Senter's data science ecosystem features an advanced geospatial data platform powered by deep learning and agronomic machine learning that delivers comprehensive phenotyping and product performance insights. In addition, plant-level tracking and modeling regionally estimate yield, nutrient absorption, and crop quality attribute. The company integrates public and proprietary data to provide high-accuracy insights efficiently and quickly.
Sentera stands at the head of digital technology with its suite of products, aerial sensors and georeferencing system for its data science ecosystem, optimizing weed management strategies. With this tech, it will be possible to identify weed species in the field and create precision prescription maps for variable-rate treatment applicators - a considerable step up from traditional practices in light of herbicide resistance and changes to weed growth patterns.