This diagram shows a simple view of how Agent AI works.
Agent AI is not just a single AI model. It works by combining Models, Tools, and Knowledge, and then improving through Evaluation.
1. Models: Understand and Predict
Models are like the brain of Agent AI. They help the system analyze data, detect problems, predict outcomes, and suggest possible actions.
2. Tools: Connect and Act
Tools allow Agent AI to connect with real systems, such as MES, ERP, IoT sensors, databases, and other software. Through tools, Agent AI can get real-time data and support action.
3. Knowledge: Guide the Decision
Knowledge includes SOPs, rules, historical data, and business context. It helps Agent AI make safer, more reliable, and more practical decisions.
4. Evaluation: Learn and Improve
After a decision or action is made, Evaluation checks the results, such as accuracy, safety, cost, and execution outcomes. This feedback can guide changes to the agent’s prompts, tools, or decision workflow; evaluation alone does not automatically retrain the model.
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