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EDGE AI

Edge Intelligent
Inference Platform

3000+ global GPU edge clusters with model preloading and smart caching. Cold start under 100ms — inference right next to your users.

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edge-ai · inferenceLIVE
3000+Global GPU Nodes
8msInference Latency
Token throughput
12.8K tok/s
GPU utilization
87.3%
P99 latency
8.2ms
cold start <100ms · OpenAI compatible · streaming
3000+Global nodes
15Tbps+Scrubbing capacity
99.99%Uptime SLA
<50msGlobal avg latency

Trusted by leading companies worldwide

Industry Challenges

Core Challenges in Edge AI Inference

Enterprises face latency, cost and operations pressure when deploying AI at the edge.

Unpredictable Latency
Cross-ocean requests to centralized GPUs cause 2+ second first-token delays, destroying real-time interaction.
First token 2s+
Severe Cold Start
Large models take 10-30s to load; serverless cold starts stack on top — unacceptable waits.
Load 10-30s
Skyrocketing GPU Costs
A100/H100 on-demand pricing is expensive; resources idle at low tide; scaling reacts slowly.
10x cost variance
Data Compliance & Security
GDPR requires local processing; cross-border auditing is complex; weight protection is hard.
GDPRWeight protection
Core Capabilities

Edge Infrastructure Built for AI Inference

Full-stack optimization ensures every inference runs on the optimal node.

Global GPU Edge Clusters
100+ GPU clusters worldwide with NVIDIA A100/H100, auto-scaling for peaks.
A100/H100Auto-scalingGlobal
Model Preloading & Caching
Popular models pre-deployed to edge nodes with distributed weight caching.
Cold start <100ms
Smart Load Balancing
Multi-dimensional routing by latency, load and cost with canary model releases.
Latency-firstCost-optimizedCanary
Real-time Inference Monitoring
Visual dashboard with live throughput, GPU utilization and latency distribution.
LIVE12.8K tok/sP99 8.2ms
One-Click Deploy API
OpenAI API compatible — one-line switch with streaming and function calling.
OpenAI compatibleStreaming
Flagship Model Coverage
GPT-4o, Claude 3.5, Llama 3, Qwen 2.5, Stable Diffusion, FLUX and Whisper out of the box — private models supported.
LLMAIGCVoiceMultimodal
EDGE AI ◆LOW LATENCY ◆SMART INFERENCE ◆GLOBAL GPU ◆COLD START <100ms ◆OPENAI COMPATIBLE ◆AUTO SCALING ◆NEARBY SERVICE ◆EDGE AI ◆LOW LATENCY ◆SMART INFERENCE ◆GLOBAL GPU ◆COLD START <100ms ◆OPENAI COMPATIBLE ◆AUTO SCALING ◆NEARBY SERVICE ◆
Use Cases

Full-Scenario AI Inference Coverage

-65% latency

Smart Customer Service

LLM-powered service with smooth streaming; first token under 200ms.

3x faster

Real-time Content Generation

AIGC image, video and copy generated in real time at high concurrency.

E2E <500ms

Voice Interaction

Speech recognition and synthesis end-to-end under 500ms.

Decision <10ms

Autonomous Driving & IoT

Inference offloading to edge GPUs for millisecond-level decisions.

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Workflow

Four Steps to Global Edge Inference

01
API Integration
OpenAI-compatible — just replace base_url. One line, zero business changes.
02
Smart Routing
Requests auto-route to the nearest GPU node by latency, load and cost.
03
Edge Inference
GPU clusters execute nearby; preload cache kills cold starts; streaming output.
04
Return Results
Encrypted delivery with full observability and 99.99% availability.

Frequently Asked Questions

What AI models are supported?

GPT, Claude, Llama, Qwen, Stable Diffusion, Whisper and more — plus private model deployment on edge GPU clusters.

How do I integrate?

OpenAI API compatible: replace base_url and you are done. Streaming and function calling supported.

How much latency reduction?

Nearby inference cuts end-to-end latency from hundreds of ms to under 10ms; LLM first token under 200ms.

How is data security ensured?

Local processing near users, encrypted weight storage, full-path TLS — GDPR-ready.

What is the pricing model?

Pay per actual usage (tokens / GPU-seconds). No minimums, no idle charges.