Facility Layers
Infrastructure layers for enterprise AI workloads
Semitron connects GPU systems, rack infrastructure and facility readiness so enterprise AI projects can move from equipment selection to reliable operation.
GPU Systems & Integration
View technology portfolio
AI compute systems prepared for real workloads
Semitron scopes GPU servers, AI workstations and validation environments for private inference, RAG, OCR, simulation and data processing workloads.
What it includes
- GPU server and workstation configuration
- Burn-in, validation and handover documentation
- Private AI workload sizing and deployment notes
Best suited for
- Enterprise AI pilots
- Inference and RAG environments
- High-density training or simulation projects
Rack Infrastructure
View compute roadmap
Rack planning for dense, serviceable deployments
Rack-level planning connects servers, storage, switching, cabling, secure access and remote operations into a deployment that can be installed and maintained cleanly.
What it includes
- Rack layout and deployment checklist
- Power path, cabling and network access planning
- Monitoring, remote management and operational readiness
Best suited for
- AI server rooms
- Colocation rack deployments
- Storage and switching integration
Compute Facility Readiness
Discuss facility planning
Power, cooling and site readiness for AI infrastructure
Facility readiness aligns power distribution, thermal planning, secure connectivity, data residency and partner evaluation for Canada-based compute capacity.
What it includes
- Power and cooling partner evaluation
- Data center readiness and connectivity review
- Phased facility capacity roadmap
Best suited for
- Canada-based AI capacity planning
- Enterprise infrastructure expansion
- Long-term managed compute services
Plan the infrastructure before the workload arrives
Semitron can help align hardware selection, rack design and facility readiness into one coherent deployment path.