AgriSense is dedicated to conducting comprehensive research and analytics within the agriculture sector. With a specific focus on Pakistan, AgriSense collects and compiles vast amounts of agricultural data, which is then stored in a centralized database. This data is meticulously organized and visualized to provide valuable insights for various stakeholders.

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Problem Statement

Crop growers and agribusinesses can both benefit from insights obtained using agricultural analytics. The biggest challenge related to agriculture analytics is the availability of desired data. We have painstakingly gathered and cross-referenced agricultural data from multiple reliable sources in Pakistan, and used it for analysis and prediction at the Mouza level. This wealth of data and its analysis is called “AgriSense”. Along with our team of on-ground agriculture experts we can collect, archive and process data required by your organization.

A problem for an AgriSense project might focus on a specific challenge or opportunity in agriculture that could be addressed through the use of technology and data. such as:

  • Limited access to real-time data on crop health and weather patterns, leading to suboptimal decision-making and resource allocation on farms
  • Poor soil quality and degradation, resulting in lower yields and reduced profitability for farmers
  • Inefficient water management practices, leading to waste and environmental degradation
  • High labor costs and labor shortages, resulting in reduced productivity and profitability for farmers
  • Ineffective pest and disease management practices, leading to crop damage and yield loss.

Proposed Solution

Agricultural data in Pakistan is scattered and fragmented due to various stakeholders collecting and retaining data in their own formats. AgriSense by Concave Analytics solves Pakistan’s agriculture data problem. We save stakeholders time by collecting, transforming, analyzing, and visualizing data. Our expert analysis uncovers unparalleled insights for opportunities and smart decisions.

This can be achieved by using sensors, remote sensing technologies, and machine learning algorithms to analyze data and give recommendations to farmers.
The use of robotics and automation helps to reduce labor costs and improve efficiency in tasks such as planting, harvesting, and sorting.
The use of data-driven predictive models, remote sensing technologies, and integrated pest management practices can help farmers to identify and manage pests and diseases before they become a problem.
Technologies such as precision irrigation and soil moisture sensors can be used to optimize water  use on farms, reducing waste and minimizing the environmental impact.
Technologies like precision agriculture, soil sensors, and satellite imagery can be used to assess soil health and identify areas that require remediation. This data informs targeted soil management practices, such as precision fertilization and irrigation, to improve soil health and productivity.


  • Customized solutions
  • Sustainability
  • Real-time monitoring
  • Integration of multiple data sources
  • Collaboration and knowledge sharing

brand health analysis + agriculture statistics of pakistan
brand health analysis + agriculture statistics of pakistan

Product Features

  • Analysis of crop health
  • Weather monitoring and analysis
  • Soil management tools
  • Integrated pest management tools
  • Analytics and reporting
  • Collaboration and knowledge sharing

Ready to optimize your farming decisions with real-time data and insights?

Contact us today for a comprehensive solution designed to transform your agricultural data into actionable insights.