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Solutions · LLM · Generative AI · Computer Vision

Enterprise AI

Discover how artificial intelligence drives innovation, enhances productivity, and delivers measurable ROI across diverse business sectors.

LLMGenerative AIComputer visionRAGLoRA
01 — Industries

Six industries already running on it.

Six sectors and the workloads they run.

Education

Personalize learning experiences, automate grading, and provide intelligent tutoring for students.

  • Personalized learning paths
  • Automated assignment grading
  • AI-powered tutoring systems

Healthcare

Enhance diagnostic accuracy, predict patient outcomes, and optimize treatment plans with AI.

  • Medical image analysis
  • Predictive analytics
  • Drug discovery assistance

E-commerce

Improve customer experience, optimize pricing strategies, and personalize product recommendations.

  • Personalized recommendations
  • Dynamic pricing optimization
  • Fraud detection systems

Marketing

Analyze customer behavior, automate content creation, and optimize marketing campaign performance.

  • Customer segmentation
  • Automated content generation
  • Campaign performance prediction

Manufacturing

Predict equipment failures, optimize production schedules, and improve quality control processes.

  • Predictive maintenance
  • Supply chain optimization
  • Quality control automation
02 — Model selection

Choose the perfect model. Train it your way.

Select the language model that best fits your unique requirements and customize its training through our intuitive platform to build an AI solution tailored specifically for your business.

Table 1 — Self-hosted model comparison
AttributeMistral 7BMistral AIChatGLM 3Tsinghua University × Zhipu AILLaMA 3Meta
Parameters7B6B8B / 70B
Language supportEnglish · Multilingual (Mistral)Chinese · EnglishEnglish · Multilingual
FeaturesFast Execution · Mixture of Experts · GPT-3.5-like PerformanceOpen Source Commercial · Low GPU Requirements · Strong Chinese CapabilitiesOpen Source · High Performance · Active Community
Use casesCode Assistant · Internal Dialogue System · Private Chat ServiceChinese Customer Service · Internal Knowledge Query · Enterprise Internal AssistantChatbot · PDF & Q&A · RAG Document Query
LicenseApache 2.0 (Commercial use allowed)Open Source (Commercial use allowed)Open Source (Non-commercial use)
Recommended forTechnical organizations needing high performance, complex reasoning, and flexible deploymentSMEs requiring enhanced Chinese language processing with commercial useGlobal enterprises needing robust multilingual capabilities and flexible deployment
Models are installed from the platform marketplace and run entirely on customer infrastructure.
03 — Fine-tuning

Three steps, no code.

Transform AI capabilities with our intuitive three-step approach—simplifying model customization from data upload through training to deployment, with zero coding required.

01

Data Ingestion

Securely upload your training data

  • Support for PDF, TXT, CSV, and other common formats
  • Multiple upload methods: drag-and-drop, API integration, or local sync
  • Automatic encryption for secure data storage
02

Training & Monitoring

Fine-tune with visualization and checkpoints

  • Multiple fine-tuning methods: LoRA, SFT, and RAG
  • Intuitive visual interface—no coding knowledge required
  • Save multiple checkpoints and compare model performance
03

Deployment & Testing

Launch and validate your custom model

  • Flexible deployment options: local or API integration
  • Built-in testing interface for validation
  • Comprehensive permission controls and offline mode support
04 — Path

Installed, tuned, served — all inside your perimeter.

Models are installed from the platform marketplace and never leave the customer's infrastructure.

Fig. 01 — Self-hosted model path
PLATFORM MARKETPLACEone-click installation · version management
LLaMA 38B / 70B
ChatGLM 36B
Mistral 7B7B
RAG DOCUMENT QUERYPDF & Q&A
INTERNAL KNOWLEDGE QUERYenterprise internal assistant
CHINESE CUSTOMER SERVICEprivate chat service
CODE ASSISTANTinternal dialogue system

Model names and use cases are those published in the platform's model library; deployment stays on customer infrastructure throughout.

Request a Custom Deployment Consultation

Our technical specialists will develop a tailored implementation plan with comprehensive support

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