DALTEX has selected an agricultural AI platform to manage farming operations across its 54,000 acres in Egypt. The potato producer announced the full integration of ORTH, an operating system built by Aydi Technologies, to connect field crews, crop history, and irrigation management. Specifically, the technology unifies operational records across agronomy teams to raise yields, cut losses, and maintain crop quality for international markets.
Operational Integration Across Farming Units
Founded in 1964, DALTEX produces more than 500,000 tons of produce each year. The company employs over 9,000 workers and ships more than 300,000 tons of potatoes annually to buyers across 75 countries. Managing production at this volume requires precise field coordination. Consequently, the group implemented ORTH to consolidate planting histories, irrigation schedules, and soil records onto a centralized digital interface within its economy supply chain.
Decision Support for Field Crews
Agronomists and farm managers use conversational queries to retrieve recommendations on product application, chemical dosage, and timing. The software uses historical internal data alongside real-time satellite imagery and weather forecasts to detect agronomic risks early. As a result, field teams receive automated alerts to address conditions before crop quality deteriorates. In addition, the system enables individual agronomists to monitor larger areas while keeping treatment protocols consistent across all farm sites.
“ORTH has been critical in enabling our production teams to weigh diverse inputs and make the right decision quickly. In a fast-paced season, faster calls and communication are everything. You need a copilot, and that’s exactly what ORTH is for.”
Ibrahim Elnaggar, Director of Operations, DALTEX
Adoption of the Agricultural AI Platform
According to developer data, this agricultural AI platform currently serves more than 300,000 growers globally across irrigation, crop nutrition, and pest protection. In surveys conducted by the provider, 73% of active users reported higher yields, reduced harvest waste, and better produce quality. By applying the system from initial planting to final packing, DALTEX aims to minimize sorting losses and preserve contract standards for its export destinations.
Data Systems and Resource Management
The deployment represents an expanding role for modern apps and data architectures within commercial agriculture. By centralizing field metrics, agricultural producers can optimize water use and fertilizer applications while protecting soil health over successive growing cycles. Moreover, enterprise deployment of the agricultural AI platform reflects broader modernization efforts in North African farming, where commercial exporters increasingly rely on predictive software to maintain food security standards and secure export revenue.
