4 Agritech Companies Supporting Farmers in Embracing Predictive Farming Methods

In the realm of agritech, advanced technologies are revolutionizing agriculture and enabling farmers to adopt predictive farming approaches. In India, numerous agritech companies are pivotal in supporting farmers, aiding them in data-driven choices to enhance productivity and sustainability.

These agritech companies harness state-of-the-art technologies like satellite imagery, weather data, machine learning, and artificial intelligence to furnish farmers with predictive insights and suggestions. By scrutinizing extensive datasets, these platforms provide valuable information on crop health, pest outbreaks, yield forecasts, and more.

Through the adoption of predictive farming techniques, farmers can optimize their agricultural methods, minimize crop losses, and boost overall productivity. These technologies empower them to

1. Agribazaar: Agribazaar’s full-stack technology engine is digitizing the entire agri-value chain – from the farm to the fork, unlike most Indian agritech players, who are limited to either pre-harvest, input yields, post- harvest or agri-financing sections.Before a farmer decides to sow a crop, a crop advisory on the crop type, yield estimate and input costs are prepared based on the land and crop history. 

The entire land, crop and farmer’s sowing history of the past years is fed into the agribazaar technology platform.  Through sophisticated Machine Learning (ML), the crop advisory services issued to the farmer ensure that the harvesting crop has optimum / the best resources for the highest yield. Data points like soil information, hydrology, etc., are captured through machine learning (ML) to predict crop yield.

Individual reports/advisory is generated for each farm based on necessary inputs and alerts like rainfall forecasts for less or more water usage and electricity consumption patterns. The platform also analyzes the soil health and crop needs and advises on fertilizer and pesticide application usage in an optimum manner as per the agri-nutrient composition of individual farms/soil.

2. Absolute: It offers software solutions to control farm hardware systems, and collects data on a regular basis from IoT devices, sensor suites, hardware systems, and satellite sources. It then feeds it into proprietary machine-learning algorithms to produce actionable insights.

Absolute currently has a plant bioscience R&D platform BioX, a farm operating system (FARM OS), and a global trade platform for the produce. Absolute’s Farm OS generates actionable insights based on inputs from the likes of sensors, satellite feeds, and others to the farmers for optimal growing conditions throughout the crop cycle. 

3. CropIn: Cropin is a global ag-ecosystem intelligence provider. Cropin’s suite of products enables various stakeholders in the agri-ecosystem, including financial services providers, to adopt and drive digital strategy across their agricultural operations.

Using cutting-edge technology like artificial intelligence, machine learning, and remote sensing, Cropin creates an intelligent, interconnected data platform. Cropin helps organizations digitize their operations from farm to fork and leverage near real-time farm data and actionable insights to make effective decisions.

Cropin Grow is an AI-enabled farm management and monitoring platform that maximizes per-acre value, improving farming operations’ efficiency, predictability, and sustainability. Plot-level Intelligence is a crop and plot-level predictive intelligence powered by field-tested AI/ML models. It provides granular and actionable insights at a plot level to help improve farm operations & profitability using deep learning techniques.

4. RMSI Cropalytics: RMSI Cropalytics aims to stack relevant agriculture data to throw a sharp light on crop acreages, health, and agrarian distress hotspots to enable inputs, finance, risk coverage, and output buyers to reach those who need it when they need it.

RMSI Cropalytics focuses on data analytics that combines the application of AI to satellite images with advanced modeling, machine learning, and crop and meteorological domain expertise to provide solutions to decision-makers in government, crop insurance, agriculture input sector, commodity trading, and the social sector.