H1ST-SUP-TKT-001
Urgent tickets shouldn't wait behind routine ones
The issue that can't wait should reach the right person first, without depending on who opened the queue. The agent reads each incoming ticket, infers its priority from severity, impact, and study context, and routes it to the appropriate queue automatically, so urgent issues jump the line and specialized problems reach the right experts. Support leaders replace subjective manual triage with fast, uniform classification.
The grind you know
When triage is manual, a ticket's priority depends on who happens to read it, and when, so it's never quite consistent. The urgent, high-impact issues end up waiting behind routine ones, and misrouted tickets bounce from team to team. All that delay and rework stretches your resolution times and leaves users frustrated.
Part of the Study Support Desk family
AI-triaged help desk for every user.
The issue that can't wait should reach the right person first, without depending on who opened the queue. The agent reads each incoming ticket, infers its priority from severity, impact, and study context, and routes it to the appropriate queue automatically, so urgent issues jump the line and specialized problems reach the right experts. Support leaders replace subjective manual triage with fast, uniform classification.
Explore the Study Support Desk familyThe agent reads the ticket's content, severity signals, and study context on submission.
It assigns a priority level using consistent criteria and explains the rationale.
The ticket is directed to the appropriate team and re-evaluated if new information changes its urgency.
Capabilities
The agent infers urgency from ticket content, severity signals, impact, and study context.
Each ticket is directed to the queue or team best suited to resolve it, reducing hand-offs.
Classification applies uniform criteria so priority no longer depends on who triages.
Priority is re-evaluated as new information arrives so escalating issues are re-ranked.
In practice
Where the agent shows up in the day-to-day of a live trial — the moments the grind usually lives in.
A production-blocking EDC fault arrives amid routine requests. The agent infers high priority from severity, impact, and study context and routes it instantly, so it doesn't wait behind trivial tickets for someone to notice.
Two similar issues used to get different priorities depending on who opened the queue. Consistent triage rules apply uniform criteria to both, removing the subjectivity from manual triage.
A ticket first looked routine, then a follow-up reveals broader impact. Reprioritization on update re-ranks it as the new information arrives, so the escalating issue rises appropriately and drives its SLA target.
Proof
Figures shown are pre-launch targets based on internal benchmarks, not guaranteed outcomes.
Gemini / Anthropic LLM
LLM
Who it's for
A ticketing system for users to submit, track, and resolve platform issues across the study team.
Learn moreResponse and resolution time tracking with automatic escalation against defined service-level agreements.
Learn moreA self-service FAQ and troubleshooting library powered by retrieval-augmented (RAG) search.
Learn morePeace of mind
Every output is generated inside a validated, audit-ready platform, kept under human-in-the-loop control, and mapped to the regulatory and CDISC standards this agent supports.
Walk through it on your own workflow with a clinical-trials expert — no pressure, no obligation, and honest answers, including on the limits.
