Bayer AG
Turning Fragmented Farm Data Into AI Recommendations That Cut Chemical Usage by 90%
Restructured fragmented agricultural data into a scalable AI platform, improving delivery performance and enabling real-time recommendations that reduced chemical usage by up to 90%.
- Client
- Bayer AG
- Sector
- Agriculture
- Engagement
- 2021 - 2024
Context
The engagement landscape
Restructured fragmented agricultural data into a scalable AI platform, improving delivery performance and enabling real-time recommendations that reduced chemical usage by up to 90%.
Challenge
What needed to change
Agricultural applications and field data sources were operating in silos, while a bloated data lake failed to provide the structure needed for reliable AI insights or scalable delivery.
Intervention
How EnCoCo responded
EnCoCo restructured the data landscape into a governed data mesh, led three cross-functional teams through agile transformation, and shaped a multi-cloud AI platform with stronger pipelines, feedback loops, and delivery discipline.
Pull quote
“The real bottleneck was not the AI itself, but the lack of order, governance, and a workable operating model behind it.”
Story
How the work unfolded
Starting point
At Bayer, EnCoCo entered a landscape full of potential but tangled in complexity. Applications like MagicTrap and MagicScout operated in silos, and a massive data lake tried and failed to unify information coming from drones, robots, farmers, and field helpers.
The core problem was not the lack of AI models. EnCoCo found that the real bottleneck was architectural and organizational: without order, governance, and a workable operating model, insights remained unreliable and impact stayed limited.
How EnCoCo responded
EnCoCo led a system-wide cleanup by untangling data pipelines, standardizing schemas, and migrating inconsistent datasets. The monolithic data lake was restructured into a data mesh with clearer domain ownership and governance, creating a stronger foundation for scalable AI-driven services.
With that foundation in place, EnCoCo shaped and led three cross-functional teams with a shared direction. They reworked delivery processes, introduced continuous deployment pipelines, and created faster feedback loops, increasing performance by more than 80% while improving morale and execution quality.
What changed
When budget changes forced a full cross-cloud migration, EnCoCo turned the disruption into another modernization step. The resulting platform delivered real-time disease and pest insights, enabled highly targeted treatments, and reduced chemical usage by up to 90%, improving both sustainability and food safety.