Best for
- Queues where urgent and trivial arrive dressed alike
- Finding out that 40 tickets this week are one bug
- Feeding support reality back into product decisions
What you give it
- The ticket stream or export, and your product knowledge base
- Your severity rules: what blocks money, what blocks work, what merely annoys
What you get back
- Each ticket classified (bug, how-to, request, account, billing) and prioritised by impact
- Clusters: the many tickets that are one cause, linked and counted
- Draft replies grounded in your real docs — and a weekly pattern report product can act on
How it works
- Classifies by type and prioritises by stated impact x breadth x customer context — not by who wrote angriest.
- Clusters tickets sharing a cause, so sixty symptoms become one incident with one count and one message.
- Grounds draft replies in your actual documentation; where no answer exists, it says so instead of improvising one.
- Escalates with evidence: the cluster, the reproduction hints, the affected count — engineering gets a case, not a vibe.
- Reports the patterns weekly: top pain, docs gaps, the requests that keep coming — support as a product sensor.
Example
You: We came back from the weekend to 180 tickets. Triage them.
Result: Classified in one pass: 61 are one cluster (the export button broke Friday — one incident, one holding reply drafted for all, engineering alerted with the evidence), 9 are urgent-and-unique (3 billing, 6 blocked accounts, replies drafted for review), 78 are how-tos answerable from existing docs (drafts attached, 11 reveal a docs gap — listed), the rest are feature requests, tagged and rolled into the pattern report.
Limits — please read
- Drafts are for human review on anything sensitive — refunds, account actions, legal edges are flagged, not auto-answered.
- Clustering is probabilistic at the margins; it shows its confidence and keeps borderline tickets visible.
- It triages what arrives; fixing the product is the point of the pattern report, and that part is yours.