Introduction: High-Performance AI Without the Cost and Latency of the Cloud
AI workloads require low latency, high-performance compute, and full control over execution environments—but traditional cloud AI platforms introduce unpredictable network delays, data security concerns, and high operational costs.
Zero Gap AI Compute delivers cloud-like scalability with near-prem AI infrastructure, allowing enterprises to run AI where it performs best—closer to their data sources, without reliance on hyperscale cloud providers.
With dedicated Bare Metal AI Servers, flexible Virtual Machines, scalable Containers, and fully managed AI Model Hosting, enterprises can deploy AI workloads with the optimal combination of performance, control, and flexibility.
AI should not be locked inside distant cloud data centers. It should be deployed near your operations, where it is most effective, responsive, and cost-efficient.
Why AI Compute at the Edge?
AI workloads need more than just raw compute power—they need to operate where data is generated, with low latency, security, and scalability in mind. Traditional cloud AI forces businesses to send massive datasets to distant cloud regions, introducing network delays, security concerns, and unpredictable costs.
Zero Gap AI Compute is built to solve these challenges by providing high-performance AI infrastructure inside 36 metro areas, physically closer to enterprises and their operations. This near-prem AI compute model ensures that AI workloads can run with ultra-low latency, maintain full data sovereignty, and scale efficiently without reliance on the public cloud.
The Problem with Traditional Cloud AI
Public cloud AI infrastructure forces enterprises to:
- Send workloads to centralized cloud regions, increasing network latency
- Depend on public internet connections, reducing security and reliability
- Pay high data egress fees to retrieve model outputs and inference results
- Operate within shared, multi-tenant environments, leading to unpredictable performance
The Zero Gap AI Compute Advantage
By placing AI compute inside 36 U.S. metros, Zero Gap AI provides the speed, privacy, and flexibility enterprises need to run AI models efficiently.
- Ultra-low latency execution – AI runs closer to operations, eliminating network delays
- Private AI infrastructure – No multi-tenant cloud environments, ensuring predictable performance
- No egress fees – AI results stay within private infrastructure, reducing operational costs
- Seamless scalability – Choose between bare metal, VMs, and containers for different workloads
AI should not be limited by cloud bottlenecks. It should run where it delivers the best results—with full control over performance, security, and cost.
Zero Gap AI Compute Options
Zero Gap AI Compute provides multiple deployment options, ensuring enterprises can choose the right environment for their AI workloads.
Bare Metal AI Servers – Maximum Performance, Full Control
For customers who need direct hardware access and zero virtualization overhead, bare-metal GPU and CPU servers provide exclusive access to high-performance AI infrastructure.
- Raw Power & Full Control – No hypervisor overhead, direct hardware access for maximum compute efficiency
- Optimized for AI/ML – Dedicated NVIDIA H100, GH200, and L40 GPUs for high-performance training and inference
- Custom OS & Frameworks – Deploy your own AI software stack with full administrative access
- Exclusive Access – Reserved servers ensure consistent performance for mission-critical AI applications
Ideal for: Large-scale AI model training, high-performance computing (HPC), and workloads requiring full hardware control.
Virtual Machines (VMs) – Flexible, Secure AI Compute
For workloads that require a full OS environment with strong isolation, VMs provide a customizable, dedicated compute experience.
- Multi-Tenant Secure Isolation – Each VM runs in a fully isolated environment, ensuring strong security and compliance
- Custom OS & Applications – Choose your preferred OS with full root/admin access
- SSH-Enabled Access – Manage your VM like a standalone server with remote access
- GPU-Powered AI Instances – Provision VMs with dedicated or shared NVIDIA GPUs for training and inference
Ideal for: AI development, enterprise applications, and environments that require custom configurations.
Containers & Orchestration – Scalable, Cloud-Native AI
For cloud-native AI applications, our container platform provides lightweight, scalable, and portable AI execution.
- Containerized AI Workloads – Deploy AI models using Docker and Kubernetes
- Elastic Scaling – Rapidly scale inference and training jobs across multiple nodes
- Orchestrated Environments – Use Kubernetes (K8s) for automated deployments and failover
- API-Driven Deployment – Easily spin up, scale, and manage containers programmatically
Ideal for: AI-powered SaaS platforms, edge AI inference, and containerized ML workflows.
AI Model Hosting – Fully Managed Inference-as-a-Service
For customers who want to run AI inference without managing infrastructure, our AI Model Hosting service provides a scalable, fully managed inference environment.
- Inference-as-a-Service – Upload models via API and instantly deploy them for real-time inference
- Ultra-Low Latency Execution – Run models closer to users for rapid decision-making
- Scalable AI Pipelines – Easily integrate with existing AI workflows
- Multi-Framework Support – Deploy models built with TensorFlow, PyTorch, ONNX, and more
Ideal for: AI application developers, SaaS providers, and businesses requiring AI inference at scale.
Zero Gap AI vs. Public Cloud AI Providers
Public cloud AI providers offer massive compute resources, but they are designed for generic, centralized workloads that require sending data over long distances to hyperscale cloud regions. For AI applications that demand real-time inference, privacy, and consistent performance, this model does not work.
Zero Gap AI Compute delivers the same scalable AI infrastructure but at the edge, eliminating cloud dependencies, egress fees, and long-distance latency. Enterprises can deploy AI on dedicated, high-performance infrastructure that provides predictable costs, stronger security, and full control over workload execution.
Zero Gap AI Compute delivers the best of both worlds—scalable AI infrastructure with cloud economics but deployed at the edge, near your operations.
Use Cases & Real-World Deployments
Zero Gap AI Compute delivers near-prem AI infrastructure for enterprises that require low-latency, scalable AI execution without relying on public cloud providers. By deploying AI workloads closer to operations, organizations achieve higher performance, greater security, and more predictable costs.
AI Model Training & Large-Scale Inference
- ✔ Train, fine-tune, and deploy large AI models without sending data to the cloud
- ✔ Near-prem GPU clusters optimized for LLM inference, multimodal AI, and machine learning
- ✔ Reduce cloud costs by running AI training and inference on private AI compute nodes
Multi-Video AI Processing & Real-Time Analytics
- ✔ Process massive volumes of video data for security, automation, and industrial AI
- ✔ AI-powered surveillance, smart traffic management, and workplace safety monitoring
- ✔ Seamless AI workload distribution between multiple locations via private fiber or 5G
Enterprise AI & Private Cloud Compute
- ✔ Run enterprise AI workloads on dedicated, near-prem infrastructure with full control
- ✔ AI-driven business intelligence, automated workflows, and private AI model execution
- ✔ Secure, high-performance compute with no egress fees or shared public cloud environments
Get Started with AI Compute at the Edge
Zero Gap AI Compute is designed for enterprises that require low-latency, high-performance AI infrastructure
without the limitations of public cloud providers. Whether you are running real-time inference, training large models, or deploying containerized AI applications, our near-prem AI compute solutions provide the flexibility, security, and scalability your workloads demand.
Your AI Deployment Journey
We make it easy to deploy and scale AI at the edge. Here’s how:
Define Your AI Needs
Our team will assess your AI workloads to determine whether
virtual machines, containers, bare metal, or AI model hosting
is the best fit for your deployment.
Choose Your Compute Infrastructure
Select from scalable VMs, high-performance bare metal GPUs, or containerized AI environments.
Need real-time processing? We’ll ensure your compute is deployed in the
optimal near-prem location for the lowest latency.
Deploy, Scale, and Optimize
We design, deploy, and manage your AI infrastructure, ensuring
seamless scaling across near-prem compute, private fiber, and 5G connectivity.
As your AI workloads grow, Zero Gap AI Compute adapts with you.
Let's Get Started
AI shouldn’t be limited by cloud bottlenecks or legacy infrastructure. Let’s build a smarter, more powerful AI system—together.