Across industries and sectors, startups and SMEs are already leveraging the power of the BSC AI Factory to accelerate their innovation. From high-performance simulations to data-driven optimisation and AI model deployment, these use cases show how our infrastructure, support, and services help transform complex challenges into measurable outcomes.

In high-risk industrial environments, such as factories handling hazardous materials, maintaining real-time connectivity is critical. Challenges include tracking vehicle movements, monitoring operations, and ensuring rapid technical response.

The BSC AI Factory supported this use case in delivering a robust 5G + Edge solution that enables real-time video analytics, remote assistance using AR/VR, and automated guidance systems. The result: safer operations, smarter logistics, and increased efficiency.

Outcomes:

• Lower infrastructure costs (CAPEX) and controlled operational expenses (OPEX) thanks to flexible deployment.

• Automated vehicle guidance using LED signage powered by routing algorithms and video analysis.

• Enhanced preventive and corrective maintenance through AR-assisted remote support.

A major cybersecurity client faced the challenge of processing large volumes of sensitive data in real time. Their previous system couldn’t handle the scale, and data verification using traditional tools was time-consuming and inefficient — putting clients at risk.

By implementing larger indexed files and an easy-to-use storage management platform, Qbeast transformed the client’s infrastructure. The solution improved file monitoring, optimised processing, and enabled faster threat detection through advanced visibility tools.

Outcomes:

• Query processing time reduced from 38 minutes to under 1 minute, accelerating threat response.

• Improved data performance, management, and cost-efficiency through optimised file structures.

• Enhanced monitoring and visibility using Qbeast’s Universal Storage Engine.

The proposed project aims to develop a cutting-edge AI platform powered by a domain-specific Large Language Model (LLM) uniquely tailored for the Turkish language. The platform will enhance information extraction, semantic analysis, and decision-making processes in data-intensive sectors, particularly in legal, financial, and administrative domains. Leveraging prior experience from TÜBİTAK-supported initiatives, including semantic search, document classification, and legal reasoning tools, this project moves a step further by integrating deep language understanding with scalable automation.

A key innovation is the creation of the most advanced Turkish LLM, which will be trained to understand the complex morphological structure, agglutinative syntax, and domain-specific terminologies of Turkish—areas where existing international models like GPT, LLaMA, or Qwen underperform. The Turkish LLM will serve as the foundation of Mecellem, an intelligent knowledge processing platform developed by New Mind. Mecellem will allow users to upload documents, extract structured knowledge, and interact with AI through a natural language interface.

Outcomes:

• Preprocess and analysis of documents
• Adapt dynamically to different sectors via model customization
• Answer user queries through chat-based AI interaction

• Conduct semantic reasoning

• Generate and enrich knowledge graphs (KGs)

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