We understand what farmers need and we are aware about the state-of-art technologies to address the farmers' need. At the end of the day it's all about making the farms profitable. We are crunching data, hacking models, exploiting the machine learning algorithms assisted with domain specific knowledge to make the farms profitable.
Agricultural big data is a big concern. Agronomic data analysis and interpretation is vital to make informed business decisions. We develop systems and processes to collect, clean, store, catalogue, visualize and analyze the fastest growing tons of agricultural data, which are coming from unlike sources. We build the grower’s trusted advisors to provide field-level insight for their profitable farms.
We provide technologies and tools that help the agricultural industry to handle complexity of data and information. Data scientists and machine learning experts in our team provide essential solutions to intersect data from different sources in order to gain insights.
Data and information holds the key to several essential questions in agriculture. Big data is necessary to detect and explain the variability in various spatial levels – field, region, country or global level. It also helps us to go back in time and check what happened in a particular field 10 years ago and how that may impact on tomorrows production, thus helps the agricultural industries to attain the market need in near-real-time fashion. We provide tools and services which make existing data useful and easy to integrate in existing systems and processes.
We believe that if the smallest agricultural unit, the farms, become profitable, then the rest of the agricultural value chain will thrive. So, we monitor the field variability, yield threats and associate business risks. We combine the monitoring results with our agronomic models to simplify the complexities and derive the precision decision for fields and thus ensure thriving the agricultural value chain.