Infrastructure engineered for AI.
Build the high-throughput, low-latency network and data-centre foundations required by AI workloads.
Architecture before products.
Build the high-throughput, low-latency network and data-centre foundations required by AI workloads. GBTECH approaches this area as part of the wider technology environment, with attention to integration, operations, resilience and maintainability.
What this capability can include.
GPU Infrastructure
Designed as part of a maintainable, secure enterprise architecture.
High-Performance Networks
Designed as part of a maintainable, secure enterprise architecture.
East-West Traffic
Designed as part of a maintainable, secure enterprise architecture.
Data Centre Fabric
Designed as part of a maintainable, secure enterprise architecture.
Leaf-Spine Architecture
Designed as part of a maintainable, secure enterprise architecture.
High-Speed Ethernet
Designed as part of a maintainable, secure enterprise architecture.
Storage Connectivity
Designed as part of a maintainable, secure enterprise architecture.
Low-Latency Networking
Designed as part of a maintainable, secure enterprise architecture.
AI Clusters
Designed as part of a maintainable, secure enterprise architecture.
Power & Cooling Considerations
Designed as part of a maintainable, secure enterprise architecture.
Network Segmentation
Designed as part of a maintainable, secure enterprise architecture.
AI Workload Security
Designed as part of a maintainable, secure enterprise architecture.
Hybrid AI Infrastructure
Designed as part of a maintainable, secure enterprise architecture.
Observability
Designed as part of a maintainable, secure enterprise architecture.
High-throughput east-west connectivity.
AI clusters can place unusual demands on bandwidth, latency, storage connectivity, power, cooling and observability. The infrastructure must be engineered around workload behavior rather than generic AI branding.