Private Inference API
Accelerated Compute

Enterprise AI.
On-premises, without operational complexity.

A fully integrated, enterprise-grade AI platform that is installed in days, runs in your own environment, and stays compliant and operational without overloading your IT teams.

01

System
complexity

Designing a complete AI stack is complex. GPUs, networking, storage, software, and scheduling must function as one integrated system to deliver reliable performance.

02

Integration
risk

Even validated components often fail once combined. Without deep AI infrastructure expertise, integration becomes slow, fragile, and unpredictable.

03

Operational
burden

Running AI on-premises extends far beyond the initial build. Firmware, drivers, CUDA, networking, and security must remain aligned over years, not weeks.

The challenge isn’t deploying AI on-premises. It’s keeping it production-ready over time.

Integrated
by design

A complete AI stack combining compute, storage, networking, and software. Delivered as a single, validated system, fully integrated and ready to run production workloads in days, not months.

Curated
flexibility

Choose GPU models that match your workloads and budget, and select from supported enterprise storage vendors from architectures Nebul can operate and support long-term.

Built to run
for years

The Pod is designed for continuous operation, with lifecycle alignment across firmware, drivers, CUDA, and system software, all handled by Nebul, so your teams are not burdened with these tasks.

GPU
compute

NVIDIA GPUs selected and configured to match your workload profile, from efficient inference to large-scale training, delivered within validated system architectures.

AI software
stack

A production-ready NVIDIA AI software stack aligned with the underlying hardware and networking, enabling workloads to run immediately without complex setup.

High-speed
networking

AI-ready networking optimized for GPU-to-GPU communication, ensuring predictable throughput and efficient scaling across nodes under sustained load.

Enterprise
storage

Integrated enterprise storage options from supported vendors, selected to match performance, capacity, and data-intensive AI workloads without forcing vendor lock-in.

System
integration

All components are assembled, integrated, and validated as a complete system before deployment, reducing integration risk and accelerating time to production.

Lifecycle
& support

Nebul owns system-level lifecycle alignment across firmware, drivers, CUDA, and platform software — keeping the Pod stable, secure, and supported over time.

Regulated and data-sensitive environments

Organizations in healthcare, government, legal, and finance where AI workloads and data must remain on-premises or in controlled colocation environments.

AI workloads that need to run on-premises

Use cases that require local processing, low latency, or deployment at the edge. Scenario's where public cloud infrastructure is not an option.

Strategic infrastructure ownership

Companies that view AI infrastructure as a long-term strategic asset and want full control over performance, cost, data, and platform evolution.

Design your Nebul
On-prem AI Pod

Talk to an expert