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Documentation Index

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When your AI Employee fails to accurately respond to a question, it is often due to the lack of explicit information or the absence of relevant data in the datastore it accesses. To enhance the accuracy of your AI Employee or to uncover knowledge gaps, integrating a Q&A datasource is recommended. This approach enables the AI Employee to access explicit answers to specific questions. Consider a scenario where an AI Employee is queried, “What’s nuclear fusion?” Without information on nuclear fusion in its datastore, the AI Employee might respond, “I’m sorry, I don’t have the information you’re looking for”
ℹ️ In this example, the knowledge restriction option is enabled; otherwise, the language model would have used knowledge from its training dataset.
Xnapper-2024-01-31-21.28.21.png To rectify this, click the “improve” button (available only from the Inbox page). You will then be prompted to provide a correct answer for the question that stumped the AI Employee. Xnapper-2024-01-31-21.30.02.png This process automatically generates a new Q&A datasource within the linked datastore, which you can later edit or delete from the Datastore page. Xnapper-2024-01-31-21.30.51.png Following this procedure ensures that the AI Employee will correctly respond to similar questions in the future. Xnapper-2024-01-31-21.32.11.png This method is effective across various languages, offering a versatile solution to improve your AI Employee’s performance 😎 Xnapper-2024-01-31-21.42.35.png