# NeuralMesh Axon: Unlock The Full Potential of Your GPUs

NeuralMesh Axon unlocks the full potential of GPUs by using local NVMe that usually sits idle and isolated. That keeps expensive accelerators running models instead of waiting on I/O from separate silos.

**Type:** Solution Brief

## Challenges

- GPU servers underutilized due to storage bottlenecks and I/O wait
- External storage appliances add cost, rack space, power, and latency.
- NVMe supply constraints and rising prices delay infrastructure expansion.

## Solution

NeuralMesh Axon is software-defined storage with memory-grade performance, running directly on our GPUs. Seamlessly fuse compute and storage to shatter AI performance barriers and radically reduce infrastructure and costs.

## Benefits

- Predictable, ultra-low-latency performance at massive scale.
- GPU utilization exceeding 90% — 3x the industry average.
- Eliminate dependence on external storage appliances and NVMe procurement cycles.

## Introduction

AI has reached a tipping point: from research projects in isolated labs to global-scale production systems powering every sector — from advanced language models and generative AI to high-frequency trading, autonomous vehicles, and next-generation life sciences.

Yet, as AI pioneers race to deploy larger models and push new boundaries, they face critical infrastructure bottlenecks. Traditional architectures, reliant on external storage systems and legacy data pipelines, can’t keep up with the explosive growth in GPU compute demands and the sheer volume of data flowing into and out of these systems.

GPU servers today ship with powerful local NVMe storage and high-speed interconnects designed to accelerate AI workloads. In most large-scale deployments, these resources sit idle or isolated; each server's storage is invisible to the rest of the cluster. Organizations are forced to overspend on separate storage silos, create unnecessary data copies, and endure performance bottlenecks that leave their most expensive assets, GPUs, waiting on I/O rather than running models.

These inefficiencies aren't just a technical problem — they're a business risk. They slow innovation, inflate operational costs, and raise energy consumption. And they're compounding: NVMe supply constraints and rising prices mean organizations that depend on procuring new drives to scale face delays, budget pressure, and growing infrastructure complexity. NeuralMesh Axon offers a fundamentally different path — extract full value from the infrastructure you already have.

## The Solution: NeuralMesh Axon

NeuralMesh™ Axon™ is a groundbreaking GPU-native storage solution engineered to unlock the full potential of your AI factory. Rather than bolting on external storage, NeuralMesh Axon embeds high-performance, software-defined storage directly within your GPU servers, transforming local NVMe resources into a powerful, ultra-low latency storage fabric. By moving storage closer to the GPUs, NeuralMesh Axon empowers organizations to:

**Lower Costs and Simpler Infrastructure**  
NeuralMesh Axon eliminates the need for dedicated external storage appliances, complex network fabrics, extra cooling, and rack space. It also removes dependence on NVMe procurement cycles. The result? Up to 50% lower infrastructure costs, faster time to insights, and reduced operational complexity.

**Unmatched GPU Efficiency**  
Eliminate I/O wait and data starvation. Training workloads achieve GPU utilization exceeding 90%, a 3x improvement over the 30% industry average. Every GPU cycle focused on delivering results, not waiting on storage.

**Built for Flexibility**  
Deployable on-premises or in the cloud, NeuralMesh Axon’s containerized architecture supports agile scaling and seamless integration with modern orchestration tools. Grow your AI factory as your models and business evolve, without rip-and-replace headaches

**Lightning-Fast AI Workloads**  
NeuralMesh Axon delivers up to 5x faster outcomes by removing data movement delays and ensuring GPUs have immediate, local access to critical data. Train, tune, and infer with the confidence that your infrastructure won’t be the bottleneck.

## Technical Highlights

- **GPU-Native and Software-Defined: **Runs fully containerized on GPU servers, leveraging existing NVMe devices without requiring specialized hardware.
- **Predictable Resource Management: **Pins and pre allocates resources (CPU, memory, NVMe, and network) to guarantee consistent performance and eliminate noisy neighbor effects.
- **Massively Parallel Distribution: **Writes and reads are distributed across GPU nodes for scalable, linear performance without ephemeral caches.
- **Cloud and Hybrid Ready: **Supports leading cloud GPU instances, allowing for seamless hybrid or fully cloud based AI factory deployments.

## When to Choose NeuralMesh Axon

Ideal for large-scale environments with 100+ GPUs, including enterprise AI factories, Neocloud providers, and advanced LLM or multi-modal model deployments where ultra-low latency, high throughput, and GPU-native storage integration are critical.

- **Underutilized GPU Servers: **You have GPU hardware that sits idle due to storage bottlenecks — NeuralMesh Axon can unlock its full potential.
- **Supply Chain Constraints: **NVMe availability or cost is constraining your infrastructure expansion
- **Rapid AI Expansion: **You need to move quickly to support new AI or generative AI workloads but want to avoid costly new storage infrastructure.
- **Budget Constraints: **You’re operating under tight capital or operational expenditure constraints and need to extract maximum value from existing resources.

## Proven at Scale

NeuralMesh Axon is already delivering results across leading AI organizations. Cohere cut inference deployment time from 5 minutes to 15 seconds with 10x faster checkpointing, enabling their team to bring new models to market faster than ever before. CoreWeave embedded Axon across its cloud platform to give customers maximum GPU utilization from day one — with no separate storage infrastructure required. Oracle validated Axon on OCI H100 instances, confirming production-grade performance for the mixed workload patterns common in large-scale AI training and inference. The Center for AI Safety eliminated dedicated storage silos entirely, increasing GPU utilization and reducing cloud costs without adding a single piece of new hardware.

## Deployment Considerations

To maximize the performance of NeuralMesh Axon, most environments should leverage the Kubernetes Operator—ideal for cloud and service provider deployments requiring advanced data protection and seamless orchestration. NeuralMesh Axon is optimized for balanced resource use, with around 4 CPU cores per NVMe drive and 100 GB of huge pages per server. For large-scale AI factories, enhanced data protection (RAFT9 with +4 parity) and thoughtful failure domain design deliver resilience and efficient updates, while maintaining homogeneous hardware and buffer nodes ensures smooth, reliable operations.

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