RESSON: Predictive Analytics for Growers

Jeff Grammer, CEO
Data and analytics have come a long way taking a massive leap from corporate closed spaces to the vastness of crops or more accurately – the modern agriculture technology. With the proliferation of novel, hi-tech data gathering techniques involving satellite, drones, cameras, sensors and GPS tracking — agriculture technology has evolved to develop the tools for unlocking the next wave of productivity gains. An ability to capture digital information at the farm gate is growing rapidly. However, the key is turning that flood of information into simple, decision-supporting tools. Leading this technology evolution which is currently underway from precision agriculture to decision agriculture is RESSON.

Founded in 2013, RESSON’s goal has always been to empower growers around the world with digital tools to enable the use of their field data to make better-informed decisions and improve productivity from every acre of their farm. By equipping growers with these high-level productivity enhancement tools, RESSON strives to make data-driven farming a reality. Combining the latest advancements in computer vision, machine learning, and big data analytics, RESSON’s technology delivers growers with actionable insights using their field data. Data-driven farming or decision agriculture is the thoughtful use of the right farm data, at the right time, to make better decisions that improve long-term profitability. RESSON also works with strategic partners and third-party service providers to bring a complete, scalable end-to-end solution to the growers. Today, RESSON is a fast-growing company, with field operations across four continents, diverse geographies, and multiple crops.

The predictive analytics solution from RESSON is significantly more efficient than the conventional NDVI maps. Derived from satellite and drone imagery, RESSON’s satellite and drone imagery are used for virtually scouting every part of the field to detect, classify, and geo-locate specific anomalies, pests, and diseases. The company’s simple and intuitive cloud-based analytics platform helps to better manage yields, crop inputs, and agronomy decisions.


By equipping growers with these high-level productivity enhancement tools, RESSON strives to make data-driven farming a reality


The key differentiation that RESSON’s technology brings is the unparalleled level of granularity to monitor and isolate specific issues based on the crop, the region, and all the way down to individual plants.

RESSON’s analytics solution also integrates data from satellites, drones, close-proximity cameras and in-field sensors to provide a comprehensive picture of exactly what is happening in every part of the farm. By combining data from multiple sources along with recent breakthroughs in artificial intelligence (AI) and power of cloud computing, RESSON’s technology provides an exceptional capability to continuously monitor, analyze, and predict crop health and threats before they can be detected by human eyes. Moreover, Resson’s platform eliminates the tediousness of manual field scouts of the entire property to find problem areas, where growers can now detect intricate crop issues and anomalies in the shortest time.

RAMAS® (RESSON Agricultural Management and Analytics System) is an integrated crop assessment system, which can identify, classify, and localize anomalies with respect to crop production. RAMAS uses the powerful concept of cause and effect to correlate data patterns and adaptive intelligence to analyze information. It provides a web-based dashboard and easy-to-use tools to help simplify agronomy decisions.

RESSON aims to help growers gain a better understanding of their farms, save time and money, and produce greater yields from every part of their farm.

Company
RESSON

Headquarters
Fredericton, NB

Management
Jeff Grammer, CEO

Description
RESSON is a bioinformatics and predictive analytics company that uses large scale data analytics, to help growers boost productivity and profits with near real-time predictive analysis for crop management

RESSON