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Admin console overview

The Cherry Studio Admin Console is a centralized management platform designed for enterprise users, offering comprehensive AI service management, user permission control, and resource configuration.

Admin console demo

1. Demo Environment

2. Core Modules

๐Ÿ‘ฅ User and Permission Management

Provides fine-grained user and permission controls to ensure enterprise security and compliance.

  • User Management: Bulk import and manage employee accounts, set access permissions and usage quotas, monitor usage and activity, support multiple authentication methods (local auth, SSO)
  • Group Management: Create and manage departments or project groups, batch-assign group permissions and resources, flexible org structure management

๐Ÿค– AI Service and Model Management

Centralized management of enterprise AI models for flexible usage and cost control.

  • Provider Management: Built-in support for 40+ AI providers (Alibaba Cloud Bailian/Tongyi Qwen, DeepSeek, Zhipu GLM, Moonshot Kimi, Volcengine Doubao, etc.), with custom provider support for OpenAI / Anthropic / Gemini API protocol formats
  • Default Models: Set platform default assistant model, topic naming model, and translation model, configure usage quotas and rate limits per model

๐Ÿ“‹ Assistant Management

Manage enterprise AI assistants to provide users with pre-configured conversational assistants.

  • Assistant List: Create and manage enterprise AI assistants, set visibility and group permissions
  • Advanced Configuration: Prompt settings and visibility control, model selection and parameter tuning, knowledge base and MCP tool binding, assistant publishing and validation

๐ŸŽญ Agent Management

Manage enterprise AI agents with more powerful autonomous task execution capabilities.

  • Agent Creation and Configuration: Visual creation wizard, custom persona and behavior rules, configure available tools/APIs and knowledge base associations
  • Agent Marketplace: Internal enterprise agent sharing and template management

๐Ÿ“ฆ Resource Library

Centralized management of enterprise AI resources, containing five modules:

  • Agent Skills: Manage skill modules available to agents, support manual upload or marketplace download, control availability by group
  • Assistant Templates: Manage reusable assistant configuration templates, import from marketplace or create manually
  • Knowledge Base: Multi-source data ingestion (PDF, DOCX, TXT, etc.), automatic parsing and smart chunking, vectorized retrieval with reranking
  • Mini Programs: Add and manage mini program apps, configure name, icon, URL, and permissions
  • MCP Servers: Configure enterprise MCP Server endpoints and tools, set access permissions, auto-distribute configs by user permissions

๐Ÿ“Š Usage Analytics

Comprehensive data analysis and usage monitoring to help administrators understand platform usage.

  • Usage Overview: Token consumption and request count statistics, multi-dimensional analysis by user, model, and time period, trend and distribution visualization charts
  • Leaderboard: User usage rankings, sort by request count and token consumption, filter by group

โš™๏ธ License Management and System Settings

  • License Management: View license status and expiry, monitor licensed user count, license activation, update, and renewal
  • System Settings: System configuration and parameter management, security policy settings, data backup and restore

โ„น๏ธ About

  • Application Information: View system version and build information, client and Docker image download links
  • Release Notes: View update details and release notes for each version
  • Technical Support: Access official support contacts and service channels

3. Admin Console Highlights

๐ŸŽจ User Experience

  • Modern UI design, clean and intuitive
  • Responsive layout for multi-device access
  • Rich data visualization

๐Ÿ”’ Security

  • Multi-layer security protection
  • Complete audit logs
  • Encrypted storage for sensitive data

๐Ÿš€ Performance

  • High-performance backend architecture
  • Supports large-scale concurrency
  • Smart caching and optimization

๐Ÿ”ง Extensibility

  • Modular design for easy expansion
  • Open API interfaces
  • Plugin-friendly development

4. Use Cases

  • Enterprise AI platform management: unified management of internal AI resources and services
  • Team collaboration platform: configure dedicated AI tools and knowledge bases for teams
  • AI service hub: build an enterprise AI service platform for business systems
  • Knowledge management system: build enterprise knowledge bases for accumulation and sharing