AI & Machine Learning
Inference is better at the edge
Run LLMs and SLMs on distributed GPU infrastructure. Low-latency inference, cost-effective training, and global scale.
Purpose-Built for AI Workloads
Infrastructure designed from the ground up for machine learning.
GPU Compute at the Edge
NVIDIA GPUs deployed globally for low-latency inference. Run models closer to your users.
Model Hosting
Deploy and scale ML models with automatic load balancing and version management.
Sub-100ms Inference
Edge deployment means faster responses. Critical for real-time AI applications.
Global Distribution
Serve AI workloads from 60+ locations. Automatic routing to the nearest GPU cluster.
Flexible Infrastructure
From shared GPUs to dedicated clusters. Scale compute up or down as demand changes.
Cost-Effective Training
Access GPU compute at a fraction of hyperscaler prices. No egress fees for model deployment.
Built for Every AI Use Case
Real-Time Inference
Deploy models for instant predictions – image recognition, NLP, recommendations.
LLM Applications
Host and serve large language models with low latency and high throughput.
Computer Vision
Process video and images at the edge for surveillance, quality control, and more.
Training Workloads
Access affordable GPU compute for model training and fine-tuning.
Why Edge for AI?
Traditional cloud providers charge premium prices for GPU compute and add steep egress fees. Edge offers a better way.
Example Savings
A100 GPU Instance
Ready to deploy AI at the edge?
Get started with GPU compute today. No commitment, pay only for what you use.