The Role of an Agent

The core role of an Agent is to act on behalf of the user — autonomously assessing situations, executing necessary tasks, and providing intelligent solutions as a true partner.

• Problem-Solving Ability: Understands user requests and independently selects the most appropriate execution path.

• Context Retention: Utilizes memory to maintain the continuity of conversations and tasks.

• Automation Expansion: Extends beyond simple dialogues to execute complex processes through the use of nodes and abilities.

• Personalized Actions: Easily performs customized tasks by invoking user-designed abilities.

Structure and Operating Principle of an Agent

An Agent performs real tasks based on a Large Language Model (LLM).

Through a conversational interface, it enables human-like interaction and uses memory to continuously maintain context with the user.

This allows the agent to go beyond simple responses — demonstrating autonomous capabilities that include planning, execution, and feedback.

Agents in Agentria can operate independently or in combination with nodes and abilities to perform richer functions and more customized actions.

• Components: AI Agents are built from nodes — the smallest functional units that perform specific operations.

• Data Flow: Data is processed in a clear sequence of Input → Process → Output.

  • Input: Defines the data and parameters required for the AI Agent’s task.

  • Process: Internal nodes process the data, passing information through node connections. This is where the agent’s autonomous operation occurs.

  • Output: Returns the final result, providing the functional completeness of the AI Agent.