Private
AI Factory
Your own enterprise AI infrastructure — full control over data, compute and models. Design, deploy and operate on-premise or private cloud AI at any scale.
Pain points
Challenges we solve
Restrictions on using public clouds for AI workloads due to security or regulatory requirements
Data localisation and protection requirements that prevent use of external AI services
Insufficient control over infrastructure, data access and model operations
No in-house expertise to launch and scale AI infrastructure at enterprise level
6-step methodology
How we deliver it
Current infrastructure analysis
Detailed assessment of existing compute, networking, storage and cooling to understand baseline and gaps
Target architecture design
Design of the target AI infrastructure architecture: GPU cluster, storage, networking topology and AI platform
Component selection
Selection of compute (NVIDIA DGX/HGX), storage systems, networking and management software aligned to workload requirements
Site readiness assessment
Evaluation of power capacity, cooling systems, physical space and network connectivity requirements
Deployment & integration
Equipment delivery, physical installation, software configuration and integration with existing IT systems
Testing & knowledge transfer
Full system testing under production load, performance validation, documentation and team knowledge transfer
Interactive tool
Configure your AI infrastructure
Select workload type and organisational scale to get a recommended infrastructure specification.
Deliverables
What you get
Deployed AI infrastructure
Scalable AI compute cluster with full performance validation and monitoring
Full data control
All data, models and computations remain within your perimeter — no external dependencies
AI workload environment
Ready-to-use environment for inference, fine-tuning, training and development workloads of any scale
Documentation & runbooks
Complete technical documentation, operational runbooks and team training
Monitoring & alerting
Configured observability stack for GPU utilisation, temperature, storage and network metrics
Scaling roadmap
Architecture blueprint for future capacity expansion and new workload onboarding
ROI
Estimate your savings
ROI estimator
Based on Noventiq project benchmarks
Why us
Why clients choose Noventiq
Enterprise-grade experience — practical expertise building production AI infrastructure for corporations and government agencies across industries
Full project lifecycle — we own every phase from architecture design through procurement, deployment and knowledge transfer
Modern platform expertise — deep knowledge of NVIDIA DGX/HGX, InfiniBand, NVIDIA AI Enterprise and Run.AI
Corporate & government sector — experience with strict compliance, security and localisation requirements
Technology
Tech stack
NVIDIA Compute
Networking
Storage & Management
Timeline
Project timeline
Real results
Case studies
Large Kazakhstan university
AI research infrastructure for one of the largest universities in Kazakhstan — high-performance computing cluster for scientific workloads and AI experiments.
Telecom operator
AI development and commercial services infrastructure for a major telecom operator — private AI Factory enabling proprietary model development and internal service deployment.
Ministry of Digital Development
Participation in national AI infrastructure development for a Central Asian country's Ministry of Digital Development.
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