AI Computer Vision Solution for
Smart AgriFood
Optimize growth, planning, and productivity.
AI Computer Vision brings visual intelligence to the heart of AgriFood operations.
From flowering to fruit ripening, it enables real-time monitoring of crop development stages—helping cooperatives, producers, and agribusinesses make smarter decisions based on precise visual data.
By integrating seamlessly with ERP platforms, sensors, satellite imagery, and even WhatsApp-based advisory systems, our solution simplifies harvest planning, resource management, and regulatory reporting.
Manufacturing Pain Points:
High Labor Dependence
Lack of Real-Time Crop Monitoring
Inefficient Harvest Planning
Water Waste and Ineffective Irrigation
Compliance and Traceability Pressure
Limited Integration with Digital Tools
Supporting scalable, data-driven AgriFood strategies
Providing accurate, real-time crop visibility
Enabling proactive and demand-driven harvest planning
Improving resource use, including water and labor
What benefits can you expect?
Case Studies
Doga sought to eliminate manual inspection and implement a fully automated vision-based defect detection system on its metal parts lines. The ultimate goal was to fully remove human intervention in quality inspection while preparing the system for future enhancements, such as automatic side flipping and the arrangement of conforming parts.
AI Computer Vision Solution for Smart AgriFood
Frequently Asked Questions
What agricultural stages or elements can the AI detect?
The system is trained to identify critical crop development phases such as flowering, fruit set, ripening, and more. It can also detect anomalies like pest damage, irrigation issues, or underperformance.
Do we need special cameras or hardware?
No. The solution is fully software-based and works with standard camera feeds or images captured via mobile, drone, or installed field cameras.
Can it integrate with our ERP or planning systems?
Yes. It’s built to integrate easily with agricultural ERPs and data platforms, allowing for automated synchronization of work orders, production records, and harvest planning.
How accurate is the detection?
The system delivers >90% precision in identifying crop stages and anomalies, ensuring data-driven decisions and efficient resource use.
How do farmers or field technicians interact with the system?
They can receive alerts and submit updates through WhatsApp or a mobile app, ensuring real-time communication without requiring new tools or technical skills.