Evren Platform

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EVREN Platform

The Presidency of the Republic of Turkey's Defense Industry Directorate is conducting various studies to strengthen the domestic and national defense industry ecosystem, develop strategic capabilities in the field of artificial intelligence, and support academy-industry collaboration.

Within this scope, an end-to-end MLOps platform called "EVREN" has been developed to provide technical support for artificial intelligence development processes and to increase the capacity of qualified human resources in this field.

The EVREN Platform offers a high-performance infrastructure that enables the management of data preparation, data labeling, model training, testing, publication, and operational use processes of artificial intelligence models through a single central structure. The use of the platform, particularly in the research activities of our academics, the project implementation processes of our undergraduate and graduate students, and scientific studies conducted in the field of artificial intelligence, will contribute to increasing our country's artificial intelligence production capacity.

The platform operates with a credit-based ecosystem model based on user contributions to the system. Within this model, users can earn credits for contributions such as dataset uploading and data labeling, and then utilize these credits to develop artificial intelligence using high-capacity GPU resources. This aims to facilitate access to expensive hardware resources for researchers and students and to create a sustainable AI production cycle based on scientific/technical contributions.

The platform can be accessed at https://evren.ssyz.org.tr, and login is possible via identity verification through the e-Government portal. Furthermore, a sample of the relevant document is attached to support the experience and initial use of the platform. Users who access the system via the QR code included in the attachment will receive initial usage credits. These promotional credits are valid until July 31, 2026.

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Read Count: 312
Create Date: 6/19/2026
Last Modify Date: 7/14/2026 11:17:15 AM

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