Choose a model and response length

Model selection, response length and the fallback answer solve different problems. Choose a model for the task, allow enough room for the reply and give customers a useful next step when the knowledge base lacks enough information.

Select the correct workspace and agent. You need permission to change the agent’s settings. Available models depend on the workspace’s subscription. Prepare a few real customer questions and a question the knowledge base cannot answer.

1. Choose a model

   Open the agent’s Overview → Model. Choose a model available to your workspace. For the full settings, open Settings → AI and Show advanced model settings. Check advanced-model availability in this guide’s Feature availability table before switching models.

2. Choose an appropriate reply length

   In Maximum response length, choose a length preset or Custom value. The displayed word count is an estimate. Save this section’s changes and wait for confirmation.

3. Write a fallback answer

   Find Fallback answer in the same AI view. Explain that sufficient information was not found and give a contact method or another real next step. Save this section’s changes separately.

4. Test in a new conversation

   Test the same questions before and after the change. Check correctness, length and the fallback answer. Preview test messages consume message credits. Change the next setting only after comparing the results.

Response variability controls variation in the model’s wording. It does not control factual correctness. If the view says this setting has no effect on the selected model, compare results by changing the task instructions or model instead.

This is an editable example. Replace the contact method with your organization’s actual details.

I cannot find enough information to answer this. Please send your question to
[your support address] so our customer service team can check it.

A fallback answer does not itself create a support request or summon an operator. Use human support or lead collection to capture a request with an Aihio action.

The service assesses the information found before answering. The current service uses balanced handling: insufficient information can produce a fallback answer, while an uncertain reply may include a notice. This does not guarantee correctness or provide a customer-adjustable certainty percentage.

Check the answer against its source and the real situation. Analytics response quality helps choose what to fix; even a high score still needs human review.

Also check availability and any applicable add-on in your workspace. This table gives minimum tiers for these features; it is not a workspace usage limit or a list of every integration.