Three-Layer Optimization Architecture

Intelligent Platform Solution

Building AI computing infrastructure that connects M types of scenarios and models with N types of hardware and chips, with full-stack cloud-edge-end layout forming three core product matrices.

Three Core Product Lines

Full-chain coverage from cloud computing scheduling to edge intelligent deployment

Cloud AI Computing Platform

AI Cloud

Cloud service platform with heterogeneous computing power, unified management of diverse compute resources, providing standardized training, inference, and data services.

Enterprise AI Research Institutions Large-scale Model Training
Intelligent Agent Development Platform

Intelligence Platform

One-stop platform empowering Agentic AI developers, from supporting large models to driving intelligent agents with complete development environment.

AI Developers Model Vendors Agent Application Teams
Edge AI Optimization Solution

Edge Intelligence

Extreme utilization of limited hardware resources, end-side hardware-software integration, achieving high-performance multimodal reasoning at low power consumption.

AI PC Smart Cockpit Smart Terminal Vendors

Three-Layer Optimization Architecture

Solving heterogeneous computing compatibility and efficiency through model-system-chip three-layer collaborative optimization

Model Layer Optimization

Model compression, pruning, quantization, sparsification, MoE architecture optimization

System Layer Optimization

Operator optimization, distributed training framework, inference engine, compute scheduling algorithms

Chip Layer Optimization

Custom accelerator design, 3D stacking architecture, heterogeneous die interconnect, instruction set optimization

AI Cloud Technical Architecture

Layered technical architecture supporting full-category chip hybrid training

Application Layer

  • Finance & Healthcare
  • Smart Manufacturing
  • Creative Generation
  • Autonomous Driving
  • Deep Research

Platform Services

  • Model Services
  • Agent Framework
  • Development Tools
  • Security Sandbox
  • Elastic Inference

AI-Native Infrastructure

  • Elastic Training
  • Distributed Inference
  • Cross-cluster Management
  • RL Framework
  • Serverless Container

Heterogeneous Compute Base

  • NVIDIA GPU
  • AMD GPU
  • Compute Accelerators
  • XPU Agents
  • Storage Agents

Thousand-Card Scale Hybrid Training

World's first thousand-card heterogeneous chip hybrid training platform

97.6% Utilization

Cluster compute utilization up to 97.6%

FlashDecoding++

Self-developed GPU inference 2-4x speed improvement

Full-Category Chip Support

Supports NVIDIA, AMD and multi-vendor chips

Intelligence Platform Technical Architecture

Core technical architecture for the Agent era

1.0

Supporting

Large Model ChatBot

2.0

Tool-based

Intelligent Agent

3.0

Symbiotic

AGI

Cross-Domain Compute Scheduling

Cross-vendor, cross-region compute unified management and scheduling

MaaS Services

Full support for multi-vendor chips, providing standardized model services

Full-Chain Support

From environment setup, tool integration to deployment, evaluation

Swarm Scheduling

Supporting large-scale multi-agent collaboration for complex tasks

Agentic Infra Architecture

Agent Application
Embodied AI
Autonomous Driving
Image/Video Generation
Deep Research
Vibe Coding
Agent Infrastructure
Agent Infra
General LLM
Code Model
Vision Model
Speech Model
Embedding & Retrieval
Framework
Environment
Security Sandbox FaaS
Context
Long/Short-term Memory RAG ICL
Tools
MCP Function Call
Identity gateway
Agent Router Security
Observability
Agent Trace
AI Infrastructure
AI-Native Infra
Elastic Service
serverless Container Orchestration
Training Service
Fault-tolerant Training MoE/Hybrid Training
Inference Service
Distributed Inference Auto-scaling
RL Service
RL Framework Elastic RL Training
Multi-cluster Management
Compute Scheduling Cross-domain Inference
Cloud Native
K8S Cloud Native Infrastructure
Core API & CRD
Scheduler
Runtime
Network
Logging
Monitoring
Storage
Cluster Manager
IaaS Infrastructure
NVIDIA GPU Cluster
CPU
Memory
GPU
OS
Storage
Network
AMD GPU Cluster
CPU
Memory
XPU
OS
Storage
Network
Other Compute Cluster A
CPU
Memory
XPU
OS
Storage
Network
Other Compute Cluster N
CPU
Memory
XPU
OS
Storage
Network
Intelligence Platform Infrastructure Agent Swarm
MaaS
Auto-select SOTA Model API Calls
Agent Execution Trace
Agent Evaluation
Agentic Data
Continuous Training
Model Agents
Multi-Agent Collaboration
Manager Agents
PaaS
PaaS MCP
Resource Agents
Multi-Agent Collaboration
Monitor Agents
IaaS
IaaS MCP
XPU Agents
Multi-Agent Collaboration
Storage Agents

Edge Intelligence Technical Architecture

Breaking the "Impossible Triangle" of Smart Terminals: Intelligence Improvement, Energy Reduction, Space Cost Reduction

🧠

Multimodal Lightweight Model

World's Leading Multimodal Lightweight Model

Supports image, audio, and text processing, 3B parameters achieving 21B-level intelligence, 300% inference speed advantage over same-precision models.

⚙️

Model Inference Engine

Sparse Reasoning + Weight Quantization

Self-developed LLM inference engine, deeply optimized for PC/mobile environments, supporting cross-platform multi-backend (CPU/GPU/NPU/iGPU).

💾

AI Inference Chip IP

15x Energy Efficiency Improvement

Self-developed LLM inference LPU IP, supporting text-to-text/image/video multimodal tasks, 3D stacked heterogeneous integration architecture.

300%

Inference Speed Advantage

40%

Memory & Energy Reduction

15x

Energy Efficiency Improvement

Learn More About AI Technical Architecture

Our technical team can provide customized AI computing solutions based on your needs