Elite AI Infrastructure Engineering
Stop Wasting Compute.
Start Scaling Intelligence.
The definitive standard for on-prem GPU cluster consulting. We bridge the gap between expensive silicon acquisition and production-grade AI performance.
The Challenge of Modern AI Ops
For the modern enterprise, the decision to build on-prem GPU clusters is driven by a need for data sovereignty, predictable TCO, and performance consistency. However, simply buying H100s or B200s is only 20% of the journey. The real bottleneck lies in the "Silicon Gap" - the failure to align hardware architecture with actual GenAI and LLM workload demands. Without expert GPU cluster consulting services, companies face stranded compute, massive queue times, and unoptimized throughput.
Common Problems We Fix
We solve the engineering friction between your data science teams' expectations and your infrastructure's reality.
Low Utilisation
Most clusters hover at 15-20% actual usage. We leverage GPU utilization optimization techniques to drive 80%+ efficiency across workloads.
Queue Chaos
Stop the research team's "starvation." Our GPU scheduling consulting eliminates queue bottlenecks via fair-share and priority-based access.
Wrong Sizing
Under-provisioning VRAM for fine-tuning or overspending on InfiniBand for light inference. We provide workload-led GPU cluster architecture consulting.
Security Gaps
Regulatory failure in high-stakes industries. We specialize in air-gapped AI consulting for defense, finance, and healthcare.
Low Utilisation
Tap to flip
Most clusters hover at 15-20% actual usage. We leverage GPU utilization optimization techniques to drive 80%+ efficiency across workloads.
Queue Chaos
Tap to flip
Stop the research team's "starvation." Our GPU scheduling consulting eliminates queue bottlenecks via fair-share and priority-based access.
Wrong Sizing
Tap to flip
Under-provisioning VRAM for fine-tuning or overspending on InfiniBand for light inference. We provide workload-led GPU cluster architecture consulting.
Security Gaps
Tap to flip
Regulatory failure in high-stakes industries. We specialize in air-gapped AI consulting for defense, finance, and healthcare.
Expert Service Modules
DataCouch provides modular private ai infrastructure consulting. Whether you are at the "whiteboard" stage or struggling with a post-deployment bottleneck, our engineering team integrates seamlessly to deliver results.
Workload-led infrastructure design is the foundation. We do not start with hardware; we start with your parameters. We calculate precise VRAM needs for LLM fine-tuning, training, and inference concurrency before a single server is ordered.
- Workload-driven capacity planning (VRAM, TDP, IOPS)
- Interconnect design (InfiniBand vs RoCE v2)
- Storage architecture for GPUDirect Storage (GDS)
We specialize in Kubernetes GPU consulting and HPC GPU cluster consulting. Our team builds the orchestration layer – whether Slurm for massive batch training or Kubernetes (with NVIDIA GPU Operator) for dynamic inference serving.
- Automated driver and CUDA toolkit orchestration
- Multi-node / Multi-GPU scale-out enablement
- Container runtime optimization (Enroot, Pyxis, Docker)
The biggest driver of GPU cluster TCO consulting is utilization. We implement high-granularity scheduling that allows for job preemption, hard quotas, and fractional GPU usage (MIG) to maximize every single clock cycle.
- Fairness algorithms and multi-team quota management
- Real-time utilization dashboards and alerting
- Fractional GPU allocation via NVIDIA MIG
Deploying AI in restricted environments requires a unique set of skills. We provide enterprise AI infrastructure consulting specifically for air-gapped operations, ensuring safety without sacrificing developer experience.
- Localized container registries and mirror repositories
- Network segmentation and zero-trust access controls
- Compliance-ready audit trails for compute usage
Maximizing ROI on Your Private AI Infrastructure
An unoptimized GPU cluster is an expensive liability. Our GPU cluster tco consulting looks beyond the initial hardware purchase price. We analyze power consumption, cooling efficiency, operational overhead, and reliability to ensure your on-prem choice actually delivers the cost savings versus the cloud.
By focusing on GPU utilization optimization, we often help clients achieve 3x more research throughput on their existing hardware, effectively tripling their infrastructure value without increasing their footprint.
80%+
TARGET GPU UTILISATION
~0ms
STANDARD COMPUTE GOAL
Production Hardening
A "Day-2 Ready" cluster requires more than just drivers. We implement the Ops in AI Ops.
Observability:
Real-time DCGM exporter metrics, job health, and queue latency monitoring.
Automation:
Self-healing nodes that automatically cordon off GPUs with excessive XID errors.
Patch Management:
Zero-downtime rolling upgrades for NVIDIA drivers and Kubernetes versions.
Our Engagement Approach
We follow a rigorous, workload-first methodology to ensure your deployment is successful on day one.
Discovery
Detailed workload analysis and hardware benchmarking.
Design
Custom architecture blueprints and capacity plans.
Build Capability
Platform enablement, hardening, and multitenancy setup.
Validate
Stress-testing interconnects and training throughput.
Handover
Deep-dive training and production runbooks
Tangible Deliverables
We don't just provide abstract advice. We deliver the code, scripts, and documentation required for elite execution. Our on-prem ai infrastructure consulting results in a complete artifact package that stays with your organization.
- Reference architecture and target-state technical design
- Sizing & capacity plan (VRAM, Concurrency, IOPS)
- Scheduler & multi-tenancy model (Quotas & Fairness)
- Security blueprint & Segmentation strategy
- Observability plan & Utilization dashboards
- Production runbooks for patching & upgrades
Designed for Enterprise Stakeholders
Platform Engineers
Focus on InfiniBand stability, driver orchestration, and Kubernetes scaling.
AI/ML Researchers
Focus on zero-wait queues, fractional GPU access, and lowlatency training.
Security & CISO
Focus on data residency, air-gapped compliance, and workload isolation.
Finance & Leadership
Focus on TCO reduction, ROI tracking, and long-term infrastructure longevity.
Frequently Asked Questions
Deep-dive answers to your technical and strategic concerns.
Yes. DataCouch provides end-to-end GPU cluster consulting services. This includes the initial high-level reference architecture and hardware sizing, followed by technical hands-on platform build capability. We assist with OS hardening, InfiniBand fabric configuration, driver orchestration, and scheduler setup to ensure a production-ready handover.
We use a workload-first sizing methodology. For inference, we prioritize token-per-second latency and memory bandwidth (HBM). For fine-tuning and training, we focus on parameter counts, batch sizes, and model parallelization (tensor, pipeline, data parallel). We calculate the exact VRAM overhead to prevent out-of-memory errors while avoiding over-provisioning that inflates your TCO.
Absolutely. We specialize in air-gapped AI consulting for regulated industries. We help you build a fully self-contained AI infrastructure, including localized artifact repositories (such as Harbor or Artifactory), mirrored package mirrors, and secure bastion deployment workflows that ensure security without crippling the developer experience.
The choice depends on your primary workload and existing team skills. Slurm is the industry standard for large-scale, batch training jobs typical of foundation model development. Kubernetes (via the NVIDIA GPU Operator) is superior for dynamic, microservices-based inference and enterprise integration. As part of our Kubernetes GPU consulting, we help you weigh these options or implement hybrid models.
You receive a complete Production Handover Package. This includes the target-state design document, hardware capacity plans, automated deployment scripts, security audit reports, and operational runbooks. Our goal is to ensure your platform team has the build capability to manage, update, and scale the cluster independently.
Ready to Own Your Compute?
Stop struggling with low utilization and queue chaos. Talk to a platform expert about scheduling, sizing, and elite private AI infrastructure engineering today.