Add “Possible Resolutions” section to AI Summary tab with AI-generated solution suggestions
- What is your original issue/pain point you want to solve?
Currently, the AI Summary tab only provides a summary or brief insights of the ticket content, but it doesn’t offer concrete, actionable solution suggestions. Agents still need to manually search for relevant solutions, even for common issues. The AI is not used to its full potential to proactively assist agents in solving tickets faster. - Which are one or two concrete situations where this problem hurts the most?
- When handling technical tickets with specific error messages where agents have to manually search the documentation or external sources for a solution.
- When onboarding new or less experienced agents who may not immediately know where to find answers, causing delays or inconsistent resolutions.
- Why is it not solvable with the Zammad standard?
The current Smart Assistant functionality in Zammad focuses on summarizing content rather than suggesting solutions. There is no feature that automatically proposes potential solutions or knowledge base articles based on the ticket’s content, such as extracted keywords or error messages. Zammad does not perform AI-driven searches or match resolutions proactively within the AI Summary tab. - What is your expectation/what do you want to achieve?
We would like the AI Summary tab to include a new section called “Possible Resolutions” where the AI:
- Proactively suggests one or more possible solutions based on the ticket content.
- Uses semantic analysis or keyword extraction to search the knowledge base, documentation, or even external sources (if configured) to find matching solutions.
- Links directly to relevant articles or predefined responses, giving agents immediate access to potential fixes.
- Optionally allows agents to rate or mark suggestions as useful to improve future AI recommendations.
This way, the AI not only summarizes but also provides prescriptive, actionable support to help agents resolve tickets more efficiently and consistently.
Your Zammad environment:
Average concurrent agent count: 10
- Average tickets a day: 50
- What roles/people are involved: Helpdesk agents, 2nd line technical support
Anything else which you think is useful to understand your use case:
We believe the AI could leverage error messages, keywords, or relevant phrases within the ticket to perform searches and propose solutions. This would save agents time and improve first-time resolution rates, especially for recurring or well-documented issues.
Thank you and have fun.