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Documentation Index

Fetch the complete documentation index at: https://docs.enneo.ai/llms.txt

Use this file to discover all available pages before exploring further.

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

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View Test Results

  • In the Test Runs Overview, select the desired test run and click on 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 whether there were deviations or errors.

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Analyze Test Results

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

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Accept Test Results or Continue Analysis

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

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Conclusion

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