Edge Intelligent Inference Platform
3000+ global GPU edge clusters with model preloading and smart caching. Cold start < 100ms. AI inference happens right next to your users.
Global GPU Nodes
Edge inference, nearby service
Inference Latency
Millisecond response
Core Challenges in Edge AI Inference
Enterprises face latency, cost, and operations challenges when deploying AI models at the edge
Unpredictable Latency
Cross-ocean requests to centralized GPU clusters cause 2+ second LLM first-token delays, destroying real-time interaction
Severe Cold Start
Large models take 10-30s for initial loading. In serverless scenarios, function cold start plus model loading creates unacceptable wait times
Skyrocketing GPU Costs
A100/H100 on-demand pricing is expensive, resources idle during traffic lows, and auto-scaling responds too slowly
Data Compliance & Security
GDPR and cybersecurity laws require local data processing, cross-border auditing is complex, model weight protection is difficult
Edge Infrastructure Built for AI Inference
Full-stack optimization from hardware to software, ensuring every inference runs on the optimal node
Global GPU Edge Clusters
100+ GPU clusters across major regions worldwide, equipped with NVIDIA A100/H100 GPUs, auto-scaling for traffic peaks
Model Preloading & Caching
Popular models pre-deployed to edge nodes, distributed weight caching, cold start < 100ms, eliminating first-load wait
curl -X POST https://edge.yewsafe.com/v1/models/deploy \
-H 'Authorization: Bearer $API_KEY' \
-d '{"model": "llama-3-70b", "regions": ["asia", "europe"]}'Smart Load Balancing
Multi-dimensional intelligent routing based on latency, load, and cost. Auto-selects optimal GPU node with model version canary release
Real-time Inference Monitoring
Visual inference dashboard with real-time token throughput, GPU utilization, latency distribution, and auto-alerting
One-Click Deploy API
OpenAI API compatible, one-line code switch, supports streaming and function calling, zero-modification integration
npm install @yewsafe/edge-aiFlagship Model Coverage
Edge deployment and accelerated inference for mainstream AI models
LLM Large Language Models
Accelerated inference for GPT-4o, Claude 3.5, Llama 3, Qwen 2.5 and more
AIGC Image Generation
Edge deployment for Stable Diffusion, FLUX, DALL-E 3 image generation models
Voice & Audio
Real-time inference for Whisper, TTS, RVC voice models for conversational scenarios
Multimodal Models
Global distribution for GPT-4V, Gemini Pro, CogVLM vision-language models
Four Steps to Global Edge Inference
API Integration
OpenAI-compatible format, just replace base_url, one line of code, zero business changes
Smart Routing
Requests auto-route to nearest GPU node, multi-dimensional evaluation of latency, load, and cost
Edge Inference
GPU clusters execute model inference, preload cache eliminates cold start, streaming output in real-time
Return Results
Encrypted result delivery, full-chain observability monitoring, 99.99% availability guaranteed
Full-Scenario AI Inference Coverage
From real-time conversations to content generation, targeted optimizations for every scenario
Smart Customer Service
LLM-powered intelligent customer service with streaming output for smooth conversations, first token < 200ms
Real-time Content Generation
AIGC image, video, and copy generation in real-time, edge inference accelerates creation with high concurrency support
Voice Interaction
Speech recognition and synthesis end-to-end < 500ms, for smart assistants, simultaneous interpretation, and voice navigation
Autonomous Driving & IoT
Vehicle/device inference offloading, edge GPU handles complex models for millisecond-level decision making
Frequently Asked Questions
Common questions about Edge AI Inference service
Our technical team is ready to answer any questions about edge inference.
Start Your Edge Inference Journey
Free trial, experience millisecond-level AI inference
