Land O'Lakes and Asahi drive digital transformation in agriculture operations
Azure Data Manager for Agriculture enables agricultural organizations to unify data from diverse sources (drones, sensors, weather, equipment) into a single platform. Customers like Land O'Lakes have used the solution to eliminate dependence on frequent farm visits, increasing their digital reach and monitoring capability. The platform leverages Microsoft Copilot templates for natural language querying across the farm's aggregated data. Security and compliance are central, with Azure's extensive cybersecurity infrastructure backing the solution. Through the use of actionable AI insights, Asahi partners with Tenso AI to apply prescriptive modeling for crop quality and yield management. The platform supports scalable insights for over 100,000 premium subscribers, providing operational efficiencies and sustainability gains. Bayer partners strategically to bring agricultural datasets, models, and workflows into the platform, enhancing solution effectiveness.
- Organization
- Land O'Lakes
- Industry
- Agriculture
- Location
- United States
Reported outcomes
Strategic outcomes
Primary read
Use case focus
Showing 3 of 4
- 1Unified Farm Data Integration and Management
- 2Natural Language Insights for Crop Monitoring
- 3Remote Crop Health Monitoring via Generative AI
- Agricultural data resides in disparate, siloed formats across drones, sensors, irrigation and weather systems.
- Managing farm operations at scale is hindered by manual, time-intensive processes and limited data visibility.
- Farmers lack real-time, actionable insights for predictive and prescriptive crop management.
- Sustainability and efficiency are difficult to improve without a holistic, data-driven platform.
- Implemented Azure Data Manager for Agriculture to unify and standardize data from various agricultural sources.
- Used Microsoft Copilot templates for natural language queries on farm data.
- Partnered with Bayer and solution providers like Tenso AI to build prescriptive AI models for crop and yield optimization.
- Delivered secure, compliance-ready cloud infrastructure via Azure.
- Eliminated dependency on physical farm visits for data collection.
- Enabled over 100,000 premium subscribers to monitor crop health remotely and gain actionable insights.
- Improved operational efficiency and scalability for Land O'Lakes and Asahi.
- Facilitated more sustainable farming practices and better crop quality outcomes by leveraging predictive insights.
Architecture
The solution integrates disparate data sources such as drones, irrigation systems, soil moisture probes, and weather stations via connectors into Azure Data Manager for Agriculture. Data is stored in a standard model, enabling processing, transformation, and retrieval. Microsoft Copilot templates provide a natural language interface for querying and extracting insights from this unified dataset. Prescriptive AI models developed by partners like Tenso AI operate on this data to inform growers, while Bayer supports integration with industry-standard workflows.
Sources & evidence1
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