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Data-Based Agent

After completing the configuration of Data Sources, Data Catalog, and Business Domains in the Data Asset module, these data can be applied to the Agent to realize data-driven intelligent Q&A or business automation capabilities.

Such Agents are called Data-Based Agents (Data Agents), which can directly access tables and views in the business domain to provide more accurate and evidence-based answers or operations.

Configuring Data Sources in Basic Agent​

  1. Go to the Basic Agent Configuration Page;
  2. Find the "Data Source" area and click the "+" button on the right;
  3. Select the data source to add from the pop-up list (which corresponds to the previously configured business domain);
  4. Click Confirm and save the Agent configuration;
  5. Publish the Agent.

After completion, the Agent can call tables or views from the data source in real-time during Q&A, enabling queries and answers based on actual business data.

Configuring Data Source Nodes in Advanced Orchestration Agent​

  1. Open the Advanced Orchestration Assistant page;
  2. Click "Add Node" and select Data Source Node as the node type;
  3. Choose the corresponding data source (i.e., business domain) from the list;
  4. Place the node at the appropriate position in the workflow and connect it with other logic nodes (such as conditional judgment, API calls, knowledge Q&A, etc.);
  5. Save and publish the workflow.

After publishing, the Agent will automatically call the configured data source nodes according to the orchestration logic during execution, thereby introducing real-time data into Q&A or business decision-making.

Notes and Best Practices​

  • Keep Business Domain and Data Synchronization Consistent
    If the table structure or fields in the business domain are updated, resynchronize in the Data Asset module; otherwise, the Agent may encounter missing fields or query errors during calls.

  • Data Source Permission Control
    Ensure that the data sources bound to the Agent have access authorization to avoid insufficient query permissions or connection failures.

  • Use Data Nodes Reasonably
    In advanced orchestration, place data nodes reasonably according to business logic to avoid repeatedly calling the same data multiple times in a single session, improving response speed and performance.

Q&A Effect of Data-Based Agent​

After configuring the data source, enter the Agent conversation interface to test the ticket analysis assistant. Below is an example interaction flow:

  1. Enter a natural language request in the dialog box

    Help me count all ticket data by ticket type and generate statistical charts

As shown in the figure:

  1. The Agent will first extract all ticket data from the data source and classify and summarize based on the category field, outputting the count statistics for each ticket type;

  1. Then, the system will automatically generate a bar chart based on the statistical data to visually display the comparison of the number of various ticket types, helping users quickly identify high-frequency issue types;

  1. Below the chart, the system also provides an Intelligent BI Analysis Area, supporting the following functions:
    • Data Preview: View the raw data used to generate the chart;
    • Chart Editing: Switch the bar chart to line chart, pie chart, etc., and customize X-axis and Y-axis fields;
    • SQL Query View: View and copy the SQL query behind the current analysis for further analysis or reuse;
    • View Data: Click to jump to the original data table view;
    • Intelligent Insights: Click to have the system provide automated insights based on the current data, such as trend analysis, anomaly detection, etc.

Data Preview:

Chart Editing:

SQL View:

The overall Q&A effect is as follows:

By configuring business domains into the Agent, SERVICEME achieves a complete linkage from data assets to intelligent agents, enabling the Agent to no longer rely solely on knowledge Q&A but to perform intelligent queries, analysis, and decision-making based on real enterprise data.