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Hands-on Tutorials

Hands-on Tutorial Overview: A Smart Agent Building Guide from Beginner to Advanced​

To help users gain a deep understanding of how smart Agents are built and applied in real-world scenarios, this tutorial is designed around three progressive and representative practical cases, covering the complete build path from a basic Q&A assistant, to a complex business process assistant, and finally to the rapid reuse of existing workflows. By studying these three cases, users will fully master how to choose the appropriate building approach based on actual business needs and improve their digital intelligent work capabilities.

🧩 Case 1: Build a Simple Knowledge Q&A Agent from Scratch​

This case is designed for beginners and focuses on how to create a knowledge-base-driven intelligent Q&A Agent from scratch. This Agent can automatically retrieve information from the enterprise knowledge base and provide intelligent responses to user questions, thereby improving knowledge acquisition efficiency.

In specific scenarios, for example, M365 operations engineers often need to consult a large number of technical documents, operation guides, and troubleshooting cases during daily maintenance work. Faced with a wide variety of scattered document resources, manual searching is often inefficient and prone to repetitive work.

Through the guidance of this tutorial, users will learn how to quickly build a usable intelligent Q&A assistant on the SERVICEME NEXT platform and complete the following:

  • Knowledge base integration and management
  • Agent capability configuration and debugging
  • Optimization of question recognition and answer matching mechanisms

This Agent can be widely applied to scenarios such as internal enterprise IT support, employee self-service, and training material retrieval.

🧠 Case 2: Build a Complex Business Process Agent with Workflow​

When business requirements go beyond simple Q&A, such as needing to operate across multiple systems and handle multi-step business logic, an Agent created in the basic way is no longer sufficient. In this case, the Workflow mechanism provided by SERVICEME NEXT can be used to achieve more advanced intelligent agent capabilities.

This case will guide users through a real business process example to build an intelligent Agent with capabilities such as "judgment, decision-making, external service invocation, and loop execution," covering the following key capabilities:

  • Workflow node configuration and connection methods
  • Conditional judgment and data processing
  • Multi-system integration and task chain management
  • Failure handling and exception branch design

This type of Agent is suitable for scenarios such as complex form approval, automated data processing, and cross-system task orchestration, and is an important tool in enterprise intelligent transformation.

⚡ Case 3: Quickly Create a Workflow Agent Using a Configuration Code​

When there is a need to quickly reuse an existing mature workflow, the rapid deployment of an Agent can be achieved through the configuration code sharing mechanism. This case uses the "Sensitive Word Extraction" assistant as an example to demonstrate how to quickly share complex workflow capabilities across teams through a configuration code.

The feature of quickly creating a workflow Agent through a configuration code provides users with an efficient and convenient Agent reuse solution, greatly improving the efficiency and consistency of workflow deployment, with the following advantages:

  • Efficient reuse, saving development costs, and one-click copying of mature Agent templates
  • Maintaining consistency in workflow processing standards within teams or organizations
  • The same core workflow can be adapted to different business scenario requirements through fine-tuning

This Agent creation method is suitable for cross-team collaboration and multi-scenario business expansion where mature workflows need to be copied and deployed quickly and in a standardized manner.

Through these three hands-on tutorials, users will gradually build a systematic understanding of smart Agent construction methods and be able to flexibly choose technical paths according to their own business scenarios, achieving an intelligent leap from automated Q&A to automated execution.