Aura Digital
София · 42.69°N 23.32°E
BG EN
Services · AI infrastructure

GPU servers & AI infrastructure for business

We design, assemble and launch GPU servers for AI training and inference — turnkey, from hardware selection to data-center deployment and rental income.


01

Configuration design

We pick the hardware for your workload and budget — with a real ROI analysis before a single component is ordered.

  • GPU selection: NVIDIA RTX 5090, RTX PRO 6000, H-series
  • CPU / RAM / storage balance for training or inference
  • ROI analysis: rent out (Vast.ai) or own use
  • Cooling and power for 24/7 full load
aura@spec: ~ ONLINE
$ aura config --workload=training
GPU · 8× RTX 5090 · 256GB VRAM
CPU · 2× EPYC 9754 · 256 threads
RAM · 768GB DDR5 ECC
✓ configuration ready to order

02

Assembly & stress test

We assemble with precision, burn-in test and validate stability under full load.

  • Precision mounting in a rack chassis
  • Burn-in under 100% GPU load
  • Thermal and power control (N+1 redundancy)
  • Full validation before deployment
aura@bench: ~ ONLINE
$ nvidia-smi --query-gpu=util,temp
GPU 0 · 99% · 64°C · OK
GPU 1 · 99% · 66°C · OK
stress · 72h · 0 errors
✓ burn-in passed

03

Data-center deployment

We deploy the server on colocation — network, redundant power and monitoring.

  • Colocation in a professional data center
  • Network connectivity and security
  • Redundant power (UPS / generator)
  • Uptime and load monitoring
aura@dc: ~ ONLINE
$ aura deploy --colo
rack · power · network ✓
uptime monitor · ON
✓ server online

04

Monetization & support

We set the server up for rental income on GPU marketplaces and handle ongoing support.

  • Vast.ai / RunPod listing and setup
  • Price and utilization optimization
  • Ongoing support and updates
  • Income and load reporting
aura@vast: ~ ONLINE
$ vast set-offer --gpu=rtx5090
listed · 8/8 GPU
util · 94% · 24/7
✓ income active
Real scale

A delivered client project

Eight custom GPU servers built for a client to rent out via Vast.ai — full cycle from configuration to deployment.

64×RTX 5090 GPUs
2,048CPU threads
6,144GBRAM
8servers

Who it is for

A fit for businesses and teams that work seriously with AI.

  • Companies training or running their own AI models
  • Teams self-hosting LLMs (Llama, Mistral, Qwen) in production
  • Investors in GPU hardware for rental income
  • AI startups for whom public clouds get expensive

Frequently asked questions

Do you build custom GPU servers?

Yes. We handle the full cycle — configuration design, component ordering, assembly, stress testing and data-center deployment.

What hardware do you use?

NVIDIA RTX 5090 and RTX PRO 6000, AMD EPYC processors, Supermicro motherboards, DDR5 ECC memory and NVMe storage — selected for your workload (training or inference).

Can I rent the GPU server out?

Yes. We set the server up for GPU marketplaces such as Vast.ai and RunPod and run an ROI analysis on the expected income.

What is colocation and do I need it?

Colocation means hosting the server in a professional data center with redundant power, cooling and network. We arrange it if you have no facility of your own.

Do you work with clients outside Bulgaria?

Yes. We work bilingually (Bulgarian and English) and serve clients across the EU — including with European data residency in mind.

What does the price depend on?

On the configuration — number and model of GPUs, CPU/RAM, storage, cooling, and the scope of deployment and support. We quote after a short scoping of your needs.

Need GPU infrastructure?

Describe your workload — we will propose a configuration, ROI and timeline.

Request a consultation
Call Us