CHALLENGES

AI Ambitions Are Outpacing Infrastructure Readiness

Most enterprises want to run AI workloads in-house, but lack the compute density, data pipelines, and operational maturity to do it reliably.

GPU shortages and long lead times delaying AI initiatives

Power, cooling, and density constraints in existing data centers

Data pipelines too fragmented to feed models reliably

Unpredictable capital costs for uncertain AI ROI

Security and governance gaps around model and data access

Skills gaps managing GPU clusters and MLOps tooling

Core Capabilities

Full-Stack Observability:

End-to-end visibility from mainframe to microservices to mobile with all telemetry (metrics, logs, traces, events) in context.

Davis® AI:

Advanced root cause analysis, anomaly detection, and remediation guidance at scale.

Out-of-the-Box Alert Coverage & Davis® AI:

Detects issues others miss by combining broad default alert coverage with causal AI to uncover problems before users notice.

Grail™ + DQL:

High-speed, schema-on-read querying of logs, events, business, and security data.

Application Security:

Real-time vulnerability detection, exploit prevention, and Kubernetes Security Posture Management (KSPM).

Custom Workflows:

Build tailored automation and platform extensions for unique business requirements.

Open Standards & Integrations:

Built-in support for OpenTelemetry, OpenSLO, and 750+ supported technologies.

Auto-Discovery & Auto-Instrumentation:

OneAgent® detects, instruments, and baselines every component automatically.

Auto-Baselining & Continuous Updates:

Learns “normal” behavior, adapts dynamically, and updates agents automatically to minimize maintenance.

Real-User & Synthetic Monitoring:

Advanced digital experience monitoring across web, mobile, and API layers.

Cloud-Native & Kubernetes Insights:

Real-time observability for microservices, serverless workloads, and container platforms.

WHY HPE

Purpose-Built for Training and Inferencing

HPE's AI infrastructure portfolio pairs dense GPU compute with the storage, networking, and orchestration AI workloads demand — delivered on-prem, at the edge, or as-a-service.

Arctiq designs, deploys, and manages the full stack so your data science teams can focus on models, not infrastructure.

HPE GreenLake for AI

Consumption-based access to GPU-accelerated infrastructure

HPE ProLiant & Cray Compute

Dense, liquid-cooled compute for training at scale

HPE Alletra Storage for AI

High-throughput storage tuned for training and inference pipelines

HPE Aruba AI-Ready Networking

Low-latency fabric connecting GPU clusters end to end

CORE CAPABILITIES

What Arctiq + HPE Deliver Together

GPU Cluster Design

Right-sized, liquid-cooled compute architectures for training and fine-tuning workloads.

AI Data Pipelines

High-throughput storage and data movement tuned for model training and inference.

MLOps Enablement

Orchestration, model versioning, and monitoring integrated into your workflow.

Consumption-Based Economics

GreenLake billing that scales with usage instead of upfront capital risk.

Power & Density Planning

Data center readiness assessments for GPU power, cooling, and rack density.

Managed AI Operations

24x7 monitoring and lifecycle management of GPU clusters and pipelines.

USE CASES WE DELIVER

Where Arctiq + HPE Fit Your AI Roadmap

Foundation Model Fine-Tuning

Stand up GPU clusters for fine-tuning and domain-adapting foundation models.

Enterprise Inferencing at Scale

Deploy low-latency inferencing infrastructure for production AI applications.

Data Center AI Retrofits

Upgrade power, cooling, and density to support GPU-dense compute.

Sovereign & Private AI

Keep sensitive data and models on-prem or in a private GreenLake cloud.

MLOps Platform Buildout

Implement orchestration and monitoring tooling for model lifecycle management.

Managed AI Infrastructure

Offload day-to-day operations of GPU clusters to Arctiq's 24x7 team.

WHY ARCTIQ + HPE

Deployment Expertise for Production AI

Certified

HPE deployment and architecture specialists

Enablement-first

Approach that ensures client autonomy long-term

Cross-industry

Public sector, healthcare, finance, manufacturing, and more

Book an AI Infrastructure Consultation

We'll assess your current environment and map a path toward production-ready AI infrastructure.

AI and GPU readiness assessment

GreenLake economics and cluster sizing

Architecture review for training and inferencing at scale

Schedule Your Consultation

Talk to our HPE specialists about your infrastructure roadmap.

Infrastructure Built to Run AI at Scale

Arctiq + HPE deliver purpose-built compute, storage, and networking for training, fine-tuning, and inferencing — without the guesswork of building it yourself.