After conducting a test run, the detailed analysis of the test results is essential for assessing the performance of the AI agent and identifying potential optimization potentials. Test results show whether the AI agent is reacting as expected or if adjustments are required.

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Viewing Test Results

  • In the Test Runs Overview, select the desired test run, and click the arrow on the right.
  • The detailed view of the test run is displayed, including status, tested AI agent, runtime, and test result.
  • The overview also shows whether the parameter transfer was successful and if there were deviations or errors.

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Analyzing Test Results

  • By clicking the arrow on the right of the individual test results, the sidebar with test details opens.
  • There, the results are divided into two categories:
    • Received: The actual reaction of the AI agent.
    • Expected: The defined, correct answer, which is compared with the received result.
  • If a deviation is present, it can be analyzed why the AI agent reacted differently than expected.

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Accepting Test Results or Continuing Analysis

  • If the received answer is correct, it can be accepted as a new test result.
  • If there are deviations, it should be checked whether a modification of the AI agent is necessary.
  • In case of critical errors, a more detailed analysis of the training data or logics may be required.

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Conclusion

The evaluation of test results is essential to ensure the quality and reliability of the AI agents. By comparing received and expected results, weaknesses can be recognized and specifically optimized.