Enterprise AI Factory Engineering and Deployment
SkyBiometry engineer enterprise AI factory infrastructure for organisations whose workloads have outgrown standard data centre architecture. Every component, from compute density to network fabric, is designed around the demands of training and inference at scale.
AI Factory Infrastructure, Engineered for Production Scale
The team building your AI factory is the same team that will operate it once it is live. That single line of accountability is the reason regulated enterprises and AI-first companies choose SkyBiometry over generalist integrators and hyperscaler partners.
GPU Cluster Design (H100, H200, Blackwell-Ready)
Architecting high-density compute for maximum FLOPs utilization. The compute layer is where any AI factory either succeeds or stalls, which is why we design bespoke compute nodes that account for the massive power and thermal requirements of the latest silicon. By optimizing rack density and power distribution, we ensure your infrastructure is “Blackwell-ready,” allowing for seamless upgrades as hardware evolves while preventing thermal throttling during 24/7 training cycles.
High-Performance Storage (NVMe, BeeGFS, GPUDirect)
Eliminating I/O bottlenecks to keep GPUs fully saturated. AI workloads require massive throughput to keep processors from idling. We deploy parallel file systems like BeeGFS and leverage NVIDIA GPUDirect Storage to create a high-speed highway between your data lake and GPU memory, bypassing the CPU to drastically reduce latency and training times.
RDMA / InfiniBand Networking
Unlocking linear scaling through low-latency fabric interconnects. In distributed training, the network is the backplane of the computer. We implement non-blocking InfiniBand fabrics with Remote Direct Memory Access (RDMA), enabling nodes to communicate with microsecond latency so your cluster performs like a single, massive supercomputer.
Kubernetes & Kubeflow for AI Workloads
Streamlining the ML lifecycle with cloud-native orchestration. We abstract the complexity of hardware management by deploying a robust Kubernetes layer optimized for AI. With Kubeflow, your team can automate experiments, manage notebook deployments, and orchestrate complex training pipelines, significantly increasing developer velocity.
Secure, Multi-Tenant Environments
Securing your intellectual property in high-performance shared environments. We implement rigid logical and physical isolation to support multiple teams or clients on a single cluster. Using advanced RBAC and encrypted interconnects, we ensure that sensitive datasets and proprietary weights remain secure, which is what makes shared infrastructure viable for enterprise AI factory deployments.
Contact us
Planning an AI factory build or evaluating partners for an existing project? Tell us about the workload, the timeline and the constraints you are working with. Fill out the form, and our team will get back to you as soon as possible.
