Ensure accurate answers from human agents with AI
Our AI-powered Quality Assurance feature just got even more powerful. You can now use it to ensure the answers provided by human agents were accurate. This is done by having the AI check the answers against your knowledge base, and then have the it rate their accuracy, and provide actionable feedback.
To use this feature, simply set up a QA criterion in the Pluno dashboard, like “Answer correctness.” The AI then checks, flags inaccuracies or missing info, and assigns a 1-5 score with a brief explanation for improvement.
Our AI-powered Quality Assurance feature just got even more powerful. You can now use it to ensure the answers provided by human agents were accurate. This is done by having the AI check the answers against your knowledge base, and then have the it rate their accuracy, and provide actionable feedback.
To use this feature, simply set up a QA criterion in the Pluno dashboard, like “Answer correctness.” The AI then checks, flags inaccuracies or missing info, and assigns a 1-5 score with a brief explanation for improvement.
Prevent end-user frustration with silent escalations
Sometimes, users are already frustrated when they contact support. If a deflection AI first tries to handle their issue and then says it’s escalating to a human agent, it can make them more annoyed, wondering why it wasn’t escalated immediately.
Now, you can create a deflection workflow that silently escalates specific ticket types to human agents without telling the user an escalation is happening. This is especially useful for high-urgency requests (e.g. billing disputes, security concerns, outages, VIP customers), where a fast human handoff is the best experience.
Sometimes, users are already frustrated when they contact support. If a deflection AI first tries to handle their issue and then says it’s escalating to a human agent, it can make them more annoyed, wondering why it wasn’t escalated immediately.
Now, you can create a deflection workflow that silently escalates specific ticket types to human agents without telling the user an escalation is happening. This is especially useful for high-urgency requests (e.g. billing disputes, security concerns, outages, VIP customers), where a fast human handoff is the best experience.
Other fixes and improvements
- Answer Copilot now runs automatically after agent notes are added to the ticket, and also if a ticket is escalated following a deflection attempt, ensuring it always provides relevant suggestions when context changes.
- The deflection workflow guide has been updated to clarify what workflows can see, when they run, what actions they can take, and what’s not supported.
- Workflow text areas didn’t expand with content while editing, making it harder to see long entries; now they automatically grow to fit the content.
- Call summaries sometimes generated incorrect information for empty recordings; now this issue is fixed.
- In the Pluno dashboard, the Support Agent role description wasn’t clear, and users could still see restricted pages in the navigation; now the description clearly explains what the role entails, and the navbar only shows pages a user can access.
- Before, the Members page on Pluno dashboard didn’t guide users; now it shows helpful messages when empty or when a search has no results.
- Added a tooltip to help new users quickly understand how to set limits on a knowledge base web link, such as restricting access to public pages only.
- All Zendesk fields were listed previously in the AI Field-Filling configuration page, which could be confusing; now only active ones are shown, with an updated description for clarity.
- Previously, onboarding didn’t allow switching Zendesk subdomains easily; now a small button lets users connect to a different subdomain during onboarding.
- The second onboarding step (API key) was incorrectly marked as completed if a wrong key was installed; now it correctly requires the user to complete the step.
Special thanks to our users PhantomBuster, Waste Vision, MaintainX and JCommerce for their feedback that inspired these updates.