Private AI inference
Low-latency model serving with vLLM, SGLang, Ollama and OpenAI-compatible endpoints.
SUPERCOMPUTING · WARSAW, POLAND
AI infrastructure built around your workload.
Dedicated GPU servers, private AI clusters and high-memory systems for inference, fine-tuning, rendering and scientific computing.
Up to 8 TBDDR5 ECC memory
1–8 GPUsper server node
Up to 400Gcluster networking
ONE PLATFORM, MULTIPLE WORKLOADS
Compute for production AI.
We size the platform around model size, VRAM, token throughput, memory bandwidth, storage I/O and east-west traffic—not around a fixed catalogue.
Fine-tuning & agents
LoRA, domain adaptation, RAG pipelines and autonomous DevOps or enterprise agents.
Generative media
Video, image and 3D workflows for Wan, LTX, diffusion pipelines and GPU rendering.
Scientific computing
Simulation, computational biology, engineering, analytics and data-intensive research.
OPTIMIZED AI RACK SOLUTION
From one server to a private AI cluster.
A balanced architecture keeps expensive accelerators supplied with data and leaves a clear path for future expansion.
CPUAMD EPYC host platform
MemoryLarge DDR5 ECC footprint
GPUDense NVIDIA acceleration
StorageNVMe Gen5 data tier
Fabric25G–400G networking
Dedicated nodeMulti-node clusterFull AI rackPrivate AI cloud
ACCELERATED COMPUTING
NVIDIA RTX PRO 6000 Blackwell Server Edition.
Enterprise acceleration for AI inference, visual computing, rendering, simulation and dense multi-GPU servers.
- 96 GB GDDR7per GPU
- Up to 8 GPUsin supported server platforms
- AI + renderingone infrastructure layer
CPU & MEMORY FOUNDATION
AMD EPYC 9005 for AI inferencing.
High core density, broad PCIe Gen5 connectivity and large memory capacity for feeding GPUs, running agents and hosting CPU-efficient models.
- Up to 8 TB RAMfor memory-intensive workloads
- PCIe Gen5for GPUs and high-speed NVMe
- High core densityfor orchestration and inference
MODEL & SOFTWARE STACK
Deploy what your team already uses.
Infrastructure can be delivered as bare metal, a managed cluster or an hourly cloud environment, depending on the workload.
LLM serving
Kimi, GLM, DeepSeek and custom Hugging Face models.
vLLM · SGLang · OllamaVideo generation
Private production pipelines for generative video and media workflows.
Wan · LTX · LoRAEnterprise agents
RAG, coding agents, document intelligence and internal assistants.
Private APIs · observabilityINDUSTRY APPLICATIONS
Where private compute creates value.
Dedicated infrastructure provides predictable performance, stronger data control and clearer long-term economics.
Pharma & biotech
Discovery pipelines, medical imaging and computational biology.
Fintech
Fraud detection, risk analysis and private document intelligence.
Manufacturing
Computer vision, digital twins and predictive maintenance.
DevOps agents
Code generation, CI/CD analysis and automated operations.
E-commerce
Search, recommendations and catalogue automation.
Marketing & media
Video generation, rendering and content localization.
2026–2031 CAPACITY ROADMAP
Expand capacity without replacing the platform.
A modular architecture can grow from a dedicated node to rack-scale and multi-rack deployments as production demand increases.
20261 node
20272 nodes
20284 nodes
2029Rack
2030Cluster
2031Multi-rack
OWN THE COMPUTE
Purchase AI infrastructure and colocate it with EWADC.
For persistent workloads, owned hardware can deliver stronger long-term economics than permanent hourly cloud consumption.
START WITH THE WORKLOAD
Build your private AI infrastructure.
Tell us the model, dataset, throughput and deployment model. We will design the compute around it.
Request a configuration