SEGES Innovation
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SEGES Innovation has 2 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 1 country.
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Hyperscaler mix
See whether SEGES Innovation's cases are powered by Microsoft, AWS, GCP, or multiple providers.
How SEGES Innovation builds AI
Build / Buy / Compose across this company's documented cases
1 of 2 cases classified (50%) · Compare all use-case types
Use case portfolio
Use case types at SEGES Innovation
Agriculture data platform leads with 1 of 2 documented cases; 2 distinct types appear across the visible portfolio.
Technology snapshot
What SEGES Innovation uses across visible cases
Computer Vision appears in 1 of 2 indexed cases; 5 named technologies are mentioned, led by Azure Data Lake.
Capability mix
All Use Cases (2)
SEGES Innovation delivers unified agricultural insights with interactive analytics
SEGES Innovation, a subsidiary of the Danish Agriculture & Food Council, sought to provide agricultural professionals in Denmark with a unified, credible data reporting platform. The challenge stemmed from growing data volumes and fragmented reporting, affecting scalability and consistency. By implementing Power BI Embedded, SEGES Innovation developed semantic models and interactive dashboards that served as a single source of truth for agricultural data. These capabilities were integrated into a web portal, offering interactive, scalable reports for improved decision-making. The solution enables users across Denmark’s agricultural advisory sector to access tailored data visualizations and analysis, ensuring consistency and trust in business insight. Features such as object-level security, backup/restore, and seamless integration with existing infrastructure enhanced governance and resilience. Business users gained improved accessibility, interactivity, and the ability to make timely, informed decisions, creating measurable value for Denmark’s agriculture ecosystem.
SEGES Innovation revolutionizes sustainable agriculture with AI-powered predictive analytics
SEGES Innovation, Denmark's leading agricultural knowledge and R&D center, embarked on a digital journey to enable farmers and food producers to lead in sustainable agriculture. Leveraging decades of agriculture data, SEGES collaborated with Microsoft and the partner twoday kapacity to modernize its machine learning operations. Their challenge lay in managing vast datasets, ensuring high-yield, healthy livestock, and accurate crop forecasting, all while maintaining environmental and economic sustainability.Historically dependent on fragmented on-premises solutions, SEGES faced inefficiencies in maintenance and scalability, hampering rapid model deployment and innovation.By building a custom MLOps platform powered by Azure Machine Learning, Azure Synapse Analytics, Azure Data Lake, and Azure Databricks, SEGES streamlined the entire machine learning lifecycle—transforming training, deployment, and monitoring of predictive models for cattle health and crop yield forecasting.The organization uses real-time data from IoT sensors and cameras integrated into their data estate, enabling a 90% accuracy rate in predicting cattle health events and precise crop yield estimations per field. Automated retraining, scalable deployment, and governance brought maintenance costs down by over 95% and non-labor costs by more than 80%.The reduction in labor hours allows SEGES to focus on new product innovation and broader farmer outreach, while ongoing improvements help meet Denmark’s and global sustainability goals.
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