Panel is collaborating with Indra Systems in the development of the EYWA platform. EYWA replaces the current decoupled monitoring system with integrated network monitoring. To achieve this, the current architecture supporting the system has been modified to design a platform that allows for more agile and efficient management of service flows and incidents, enabling integrated omnichannel visualization of the entire monitoring system.

The EYWA system, based on big data and machine learning technologies, aims to improve ENAIRE's efficiency and productivity by optimizing the handling of complex situations and facilitating decision-making to reduce the impact of incidents. From the outset, the technology used is a key element to give visibility to this strategic vector, and the proposed architecture supports the generation of dashboards and reports as an omnichannel information stream, allowing monitoring of the operation and services provided by ENAIRE both in real time, showing the availability of the network of services provided, and offline, providing statistics and indicators of the services.

A DevOps team has also been created to manage the EYWA development lifecycle, based on automated infrastructure deployment and Continuous Integration and Continuous Delivery (CI/CD). Panel also collaborates on the development of backend and business intelligence modules, as well as complete testing management, ensuring the quality, reliability, and performance of each component before its production launch.

AI and machine learning technologies have also been used for example, Develop predictive models to predict the estimated number of flights operated by Enaire, with a time horizon of up to 365 days, and broken down by airline regions and globally. And hUsing Generative AI, the process of creating the "day's commentary" has been improved. This summary, which was previously done manually twice a day and includes the most significant events that have occurred so far, is now generated automatically.