Application types

Large language models have limitations in processing private knowledge, accessing real-time information, following fixed procedures, and planning complex tasks. To overcome these challenges, Model Studio provides two application types: agent applications, workflow applications. By integrating capabilities such as knowledge base retrieval, external tool calls, and memory, Model Studio lets you build AI applications that solve business problems. Important

• Console restrictions: Only International Edition users who created applications before April 21, 2025 can access the Application Development tab, as shown in the following figure.

  This tab contains the following features: Applications ( agent application and workflow application), Components ( prompt engineering and plug-in), and Data ( knowledge base and application data). These are all preview features. Use them with caution in production environments.

• API call limits: Only International Edition users who created applications before April 21, 2025 , can call the application data, knowledge base, and prompt engineering APIs.

Quick selection

• Agent application:

  • Driven by prompts, these applications autonomously understand user intent, make decisions, and call external tools such as knowledge bases and MCP services to complete tasks.

  • Best for open-ended conversational applications, such as customer support, knowledge Q&A, task assistance, and travel planning.

• Workflow application:

  • These applications use visual node orchestration to chain multi-step, complex tasks into a stable, controllable, and repeatable execution path.

  • Suitable for automating fixed processes, such as generating reports, processing orders, managing multi-step approval flows, and labeling data.

Application comparison

Dimension	Agent	Workflow
Typical use cases	Customer support, knowledge Q&A, task assistance, and travel planning	Automated report generation, order processing, multi-step approval flows, and data labeling
Development approach	Natural language configuration (no-code)	Visual node orchestration (low-code)
Process determinism	Autonomous AI decision-making and dynamic planning The LLM autonomously plans task steps based on the prompt.	Precisely controlled by a predefined process Each step is defined by a preset node, ensuring deterministic logic.
Best for	Business users, product managers, and operations personnel	IT operations personnel, business analysts, and implementation consultants
Skill requirements	Low	Medium

Get started

You can create an application in the console:

• Agent application

  • To create and configure, see: Agent application.

• Workflow application

  • To create and configure, see: Workflow application.