MINNEAPOLIS – Leading agricultural insights company Sentera announced today that it has acquired Insight Sensing.
Insight Sensing, a company founded by two PhD graduates from the University of Minnesota, has developed a groundbreaking technology platform that delivers field-specific insights to agronomists. The technology is powered by machine learning using on-farm data. Insight Sensing was supported by the National Science Foundation Small Business Technology Transfer program, providing the opportunity for the team to initially focus on delivering a product for in-season nutrient management, with a particular focus on nitrogen management in potato production.
“As a leader in delivering time-sensitive agricultural insights, Sentera is ideally positioned to commercialize and build upon our machine learning platform technology to further optimize decisions and improve outcomes,” said Brian Bohman, Chief Executive Officer of Insight Sensing. “We are ready to immediately contribute to Sentera’s mission and vision by providing growers, advisors and customers throughout the farm-based supply chain with new tools to increase efficiency and build confidence in their decisions.”
Sentera’s existing technology centers around FieldAgent®, a software platform built to serve companies in food and agriculture by integrating data from satellites, on-field equipment, weather, soil, drones, sensors, and field observations. FieldAgent delivers comprehensive field performance data that informs decisions and streamlines operations. The platform processes data through powerful models, machine learning and artificial intelligence tools – some of which include stand count, tassel count, weed maps, nutrition reporting, and carbon and sustainability scoring. With FieldAgent, customers receive insights that help optimize both agronomic and business outcomes across the food and agriculture value stream.
“Integrating Insight Sensing’s existing technology into FieldAgent will accelerate the adoption of machine learning tools by giving Sentera’s customers direct access to applications suited to their specific needs” said Zach Marston, Principal Scientist at Sentera. “We expect to unlock a whole new class of analytics and reporting products, and we’re excited to see the potential of this technology as it continues to be developed.”
With the acquisition of Insight Sensing, Sentera is continuing its mission to focus on creating insights that are timely, accurate, affordable, and actionable while accelerating adoption of its solutions through expanded capabilities and partnerships.
“Insight Sensing is complementary to Sentera in many ways, and integration of this technology will allow us to better serve and expand each of our customer segments” said Eric Taipale, Chief Executive Office of Sentera. “We are particularly excited about launching an in-season nutrient management product in 2022 as well as integrating Insight Sensing’s technology with FieldAgent to develop new products and services that will expand all areas of our business.”
About Sentera
Sentera delivers time-sensitive agricultural insights that optimize agronomic decisions and improve outcomes. Our products make it easy to integrate in-field data insights with the digital ag platforms in use by more than 80 percent of the growers in North America. Our integrated software and sensor products deliver fast, accurate information that improves outcomes for growers, advisors, and downstream customers.
About Insight Sensing
Insight Sensing supports agricultural decision making by providing agronomists with data-driven insights by leveraging their own on-farm data. A company founded by Brian Bohman and Tyler Nigon, two PhD graduates from the University of Minnesota, Insight Sensing builds on decades of foundational precision agriculture and remote sensing research and technologies. Supported by the National Science Foundation Small Business Technology Transfer program, Insight Sensing has developed a geospatial machine learning platform to power the next generation of agronomic insights.
SOURCE Sentera
