Türkiye on Sunday launched a new national artificial intelligence platform named EVREN, aimed at strengthening the country's defense industry.
EVREN serves a broad range of users, from defense industry firms and technology companies to academics, entrepreneurs and students, bringing data, AI models and high-performance computing power together on a single platform, according to a statement from the Presidency of Defense Industries (SSB).
Prompt, response and usage data on the platform are processed on high-performance GPU infrastructure located in Türkiye, preventing sensitive data from being transferred to cloud services abroad.
It can be accessed at evren.ssyz.org.tr using e-Government (e-Devlet) authentication.
EVREN operates through a contribution-based credit model rather than direct paid access.
Users can earn credits by uploading datasets, labeling data or sharing their trained models.
The credits can be used for model training and large language model (LLM) inference operations through the platform's high-performance GPU pool.
The system aims to make users active participants who contribute to the development of the EVREN ecosystem rather than merely receiving services.
EVREN offers end-to-end data labeling and model training capabilities for computer vision tasks such as object detection, segmentation and classification.
An inference layer covering 11 open-weight large language models has also been activated on the platform.
Existing applications can connect to EVREN's infrastructure through its API architecture, real-time response support and automatic model routing features.
To encourage broader use of the infrastructure, API calls made through Nov. 1, 2026, will be offered without limits and without deductions from users' credit balances.
EVREN has reached 7,500 active users in a short period and is intended to contribute to the development of Türkiye's AI ecosystem and efforts under the Artificial Intelligence Action Plan.
The platform will be further developed with domestically developed large language, image and audio models, while its computing infrastructure will be strengthened through a distributed GPU management approach.
