Understanding AI Behavior
Whisper's AI is powerful. However, it's important to understand how it learns and why it behaves the way it does in certain situations.
Updated: 3 June 2026
Whisper's AI is very powerful. To get the most out of it, it is important to understand how it learns and why it behaves the way it does in certain situations.
How Whisper Learns#
Whisper builds its knowledge base in several ways:
Onboarding Research
When you first create your organization, Whisper performs a deep analysis of your provided e-shop URLs. This helps it understand your catalog, policies, and brand tone.
Feedback Notes
You can manually add specific instructions in the Feedback & Training section of your WhisperBot settings.
File Uploads
You can upload reference documents (PDFs, text files, etc.) for the AI to learn from.
Conversation History
The AI continuously learns from resolved threads, adapting to how your operators handle different types of situations.
Why Responses May Be Inaccurate#
If the AI provides an inaccurate response or draft, it usually means it lacks the correct context or specific instructions.
Modifying Suggestions with Copilot#
If a drafted email response isn't quite right, you don't need to rewrite it manually. Use the Copilot prompt at the bottom of the open thread to simply instruct the AI on how to improve it (e.g., "Make this shorter and more polite").
Re-analyzing a Conversation#
If you've recently updated your integrations or customer data, the current AI suggestions might be based on outdated information. In this case, click the Re-analyze button in the context panel. This forces the AI to fetch the latest data and generate completely new suggestions.
