Feature Requests

Expanded Control and Deactivation Options for Reminder Agent
Reminder Agent currently restarts its sequence from Reminder 1 after completing the final configured reminder if the ticket status remains unchanged. This can lead to unintended message loops and excessive ticket activity. Additionally, the current setup only supports daily reminder intervals and always logs each reminder as a ticket entry, which may result in unnecessary clutter. The lack of configuration flexibility limits its usability for teams with existing ticket lifecycle workflows or custom follow-up strategies. Requested Features: Deactivation After Final Reminder: Add the ability for Reminder Agent to automatically deactivate after a specified number of reminders, without requiring a status change. This prevents looping behavior and avoids the need to create additional ticket statuses solely to exit the reminder sequence. Customizable Reminder Intervals: Allow users to define the interval between reminders, such as every 2 or 3 days, instead of the current daily default. Individual Reminder Scheduling: Support per-reminder scheduling so users can set different delays between each reminder or define longer gaps after a certain point. Optional Note Logging: Provide a setting to minimize or suppress reminder entries in the ticket note history, reducing clutter and maintaining ticket readability. Benefits: • Prevents reminder loops and client notification fatigue. • Enables alignment with existing follow-up policies and escalation timelines. • Reduces the need for excessive ticket statuses or complex mappings. • Helps maintain clean, readable tickets by limiting repetitive note entries. • Expands the utility of Reminder Agent beyond chat-based tickets, supporting broader adoption across all ticket types.
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Role-Aware Functionality for Magic AI (Ticket Routing & Snippets)
It would be incredibly useful if Magic AI could recognize a technician’s job role within the company and use that information in two areas: ticket routing decisions and snippet phrasing. Primary Use Case: Role-Aware Ticket Routing Right now, ticket routing decisions are typically based on things like category, priority, and keywords. If Magic AI could also factor in the job role of the person routing or escalating the ticket, it would help us enforce process standards, improve queue management, and maintain SLA integrity. A few examples where this would be valuable: • Escalations from managers could bypass Level 2 queues and go directly to Level 3. • AI could restrict certain routing actions for non-manager roles (like moving tickets to Projects, DevOps, or Leadership queues). • If a Service Desk Manager escalates a ticket, Magic AI could automatically increase priority or flag it for immediate review. • For routine misroutes, AI could warn Level 1 techs of improper routing but allow managers to bypass the warning. • Tickets requiring leadership approval could be auto-tagged ‘Pending Manager Review’ if routed by a technician. This would help clean up routing mistakes, prevent SLA risks, and make escalations run smoother while respecting team roles and responsibilities. Secondary Use Case: Role-Aware Snippet Phrasing Additionally, having Magic AI adjust phrasing in suggested snippets based on the sender’s role would improve client perception and communication clarity. Some examples: • Ticket closure confirmations sounding different if sent by a manager vs. a technician. • Escalation notices reflecting the sender’s authority. • Service restoration or outage notifications adjusting tone and phrasing depending on job role. • SLA warnings or fast-tracks coming from leadership carrying the appropriate urgency.
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