WiLine Edge Cloud Documentation
Welcome to the WiLine Edge Cloud (WEC) documentation — everything you need to set up your account, deploy instances, and manage storage, networking, and billing. Choose a topic below to dive in.
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What is WiLine Edge Cloud?
WiLine Edge Cloud is the only AI-first edge cloud platform built for real-time AI workloads — combining GPU density, ultra-high-capacity connectivity, data sovereignty, and nationwide U.S. scalability in a single platform.
Unlike hyperscalers built for centralized data centers, WEC brings compute directly to where your data lives. With 15 U.S. edge regions, NVIDIA and AMD Instinct GPUs, instant provisioning, and all data processed exclusively within U.S. borders, WEC is purpose-built for the next generation of AI applications — from LLM inference to computer vision to autonomous AI agents.
The Cloud, Re-Architected
Why edge-native matters
Hyperscalers were designed for a world of centralized compute — large data centers serving requests that travel hundreds of miles to reach your users. That model creates unavoidable latency, unpredictable egress costs, and data residency risks that modern AI workloads can't tolerate.
WiLine Edge Cloud was built from scratch to solve this. By deploying NVIDIA and AMD GPUs directly at the network edge across 15 U.S. regions, WEC eliminates the round-trip to a central data center, keeps all data within U.S. national borders, and gives you instant, API-driven access to GPU compute without the overhead of traditional cloud infrastructure.
Optimized for Every Workload
Instance tiers
WEC offers three purpose-built instance categories, each optimized for a distinct class of workload. All tiers share the same edge-native infrastructure, data sovereignty guarantees, and instant provisioning.
- Deep Learning & AI/ML
- LLM Inference & AI Agents
- Computer Vision
- High-performance Rendering
- Video Transcoding
- Scientific Simulations
- Batch Processing
- High-traffic Web Servers
- CI/CD Pipelines
- Scientific Computing
- Financial Modeling
- In-Memory Databases
- Real-Time Analytics
- High-performance Caching
- Big Data Processing
- SAP HANA
WEC vs. Hyperscale Edge
Competitive comparison
The fundamental difference is architecture. Hyperscalers offer edge zones as an extension of their centralized cloud — still virtualized, still in rented facilities, still subject to egress fees and data residency ambiguity. WEC is edge-native by design.
| WiLine Edge Cloud | AWS Wavelength | Azure Edge Zones | Google Distributed | |
|---|---|---|---|---|
| Architecture | Edge-native, no hypervisor tax | Virtualized, centralized DC | Virtualized, centralized DC | Virtualized, centralized DC |
| GPUs | NVIDIA & AMD Instinct at the edge | Limited edge GPU availability | Limited edge GPU availability | Limited edge GPU availability |
| Regions | 15 U.S. edge locations | Select metro edge zones | Select metro edge zones | Select metro edge zones |
| Data sovereignty | All data within U.S. borders | Varies by region config | Varies by region config | Varies by region config |
| Provisioning | Seconds | Minutes | Minutes | Minutes |
| Compliance | SOC 2 Type II | SOC 2 + others | SOC 2 + others | SOC 2 + others |
| Storage | NVMe + S3 Object Storage | EBS / S3 - egress billed | Azure Blob - egress billed | GCS - egress billed |
WEC Capabilities Overview
Platform architecture
From incoming workload to edge execution — every layer of WEC is purpose-built for AI inference at the network edge.
