Jeco Energies

Jeco Energies is a global player specializing in high-voltage cabins and industrial electrical installations. Since June 2022, the organization has operated as a unified group comprising several specialized companies. Together, these entities manage the maintenance and servicing of thousands of high-voltage and medium-voltage cabins, ensuring reliable energy infrastructure for clients around the world.

Problem Statement

‍With the integration of multiple companies and a massive portfolio of thousands of voltage cabins, Jeco Energies faced a significant administrative challenge. The process of generating maintenance quotations was labor-intensive and manual. Critical information regarding the specifications and condition of individual cabins was scattered across various unstructured formats, including technical drawings, photographs, textual descriptions, and email chains. This fragmentation made it difficult to quickly access accurate data, resulting in slower turnaround times for quotes and inefficiencies in maintenance planning.

Our Solution

‍We partnered with Jeco Energies to overhaul their administrative workflow through advanced automation and Artificial Intelligence. We deployed AI models capable of processing and extracting data from single line diagrams. We converted them into a structured, digital format. This created a centralized comprehensive profile for each cabin. This structured data can be used to further optimize the creation of maintenance quotes, significantly reducing manual input.

Results & Impact

The implementation of this AI-driven solution has transformed Jeco Energies' maintenance operations:

• Increased Efficiency: The time required to generate maintenance quotes has been drastically reduced, allowing the team to respond to client needs faster.
• Data Centralization: Thousands of cabins now have accurate, digital profiles, eliminating the need to search through archives or disparate files.
• Scalability: As the group continues to grow, the automated system can easily handle an increasing volume of maintenance requests without a proportional increase in administrative workload.
• Improved Accuracy: By relying on extracted data rather than manual entry, the risk of human error in technical specifications and pricing has been minimized.

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