ORBISIS does not treat artificial intelligence as a standalone hardware or GPU selection. A successful artificial intelligence investment is made possible through a custom-designed architecture, the right choice of technology, and a sustainable infrastructure approach. Therefore, ORBISIS offers end-to-end artificial intelligence and data platforms by analyzing customers' goals and workloads to determine the needs-specific topology and the correct GPU class.
Our goal is to create secure, scalable, and long-term manageable structures that enable customers to generate real value from data.
Custom-Designed Architecture and Topology Approach
Not every artificial intelligence project is the same. The type of model to be used, data size, number of concurrent users, and growth targets directly affect the infrastructure architecture. Instead of standard solutions, ORBISIS designs customer-specific topologies to create the most accurate structure.
In this context;
- Multi-GPU architectures on a single server
- Scalable, multi-node AI cluster structures
- Architectures where training and inference environments are separated
- Infrastructures specialized for Large Language Model (LLM) and analytical workloads
are planned according to the needs of the customers.
High-Performance Network Infrastructures for Artificial Intelligence
One of the most critical elements determining performance in artificial intelligence platforms is the network infrastructure. Powerful GPUs cannot provide the expected efficiency when not supported by the correct network architecture.
ORBISIS designs end-to-end artificial intelligence infrastructures specifically for AI workloads with;
- 800G and above high-bandwidth network connections
- Low-latency and lossless network designs
- High-speed Ethernet and InfiniBand architectures
In this way, distributed training processes are accelerated, and AI services running in production environments operate stably and without interruption.
The Right GPU Approach for Enterprise Artificial Intelligence Workloads
ORBISIS positions the GPU not as a standalone product, but as an integral part of the artificial intelligence architecture. GPU selection is made by considering the balance of performance, cost, and scalability.
Large-Scale Model Training
Deep learning and large language model (LLM) training require high memory capacity and intense parallel processing power. In these scenarios, GPU classes offering high performance at the enterprise level are preferred (A100, H100, etc.).
Training & Inference
In some enterprise scenarios, model training and the production environment run on the same infrastructure. In these cases, GPU architectures that can run both training and inference workloads in a balanced manner are used (A100, etc.).
Production Environments and Inference
In real-time artificial intelligence applications, stability, energy efficiency, and continuous service capacity are at the forefront. GPU classes optimized for image processing, video analytics, and enterprise AI services are preferred (L40S, etc.).
Large Language Models (LLM) and Enterprise Artificial Intelligence Applications
Large Language Models (LLM) play a critical role in document analysis, enterprise information access, intelligent assistants, and decision support systems. ORBISIS ensures the controlled use of these technologies with custom and secure LLM platforms for customers.
In-house data is processed within closed-circuit and secure environments, and artificial intelligence applications are implemented by considering data security and regulatory requirements.
Integrated Artificial Intelligence Approach with Data Platforms
A strong data infrastructure lies at the heart of artificial intelligence solutions. ORBISIS combines data from different sources into central data platforms, making it ready for artificial intelligence applications.
In this context;
- Data collection and integration layers
- Analytical and big data platforms
- Data architectures supporting artificial intelligence and machine learning workflows
are planned end-to-end.
Secure, Traceable, and Sustainable Structures
Enterprise artificial intelligence platforms are designed based on security, traceability, and operational continuity.
- Role-based access management
- Data security and isolation
- Performance and capacity monitoring
- Resource utilization optimization
In this way, customers manage their artificial intelligence investments in a controlled and sustainable manner.
Why ORBISIS?
ORBISIS positions artificial intelligence by considering not only today's but also future needs.
- Custom-designed architecture and topology design
- Selection of the right GPU class and network infrastructure
- Scalable and future-ready solutions
- End-to-end consultancy, installation, and operation support
With ORBISIS, your artificial intelligence investments come to life with a strong infrastructure and the right strategy.