Similar tickets
Find tickets that look like the one you're working on.
When you're working on a ticket and want to know "have we seen this before?", the Similar Tickets feature pulls up the closest matches from your archive.
How it works
Click 🔍 Find similar tickets in the ticket sidebar.
- We run a MySQL full-text search on the current ticket's subject + description, scoped to the same workspace, to build a candidate set of up to 20 tickets.
- We send Claude the current ticket + the 20 candidates and ask it to score each candidate's similarity from 0 (unrelated) to 1 (basically the same issue).
- Claude returns the ranked list. We show the top 5 with their scores above 0.4.
The result renders as a list of clickable tickets in the sidebar with their reference, subject, status, and similarity score. Click a row to open that ticket in a new tab.
What "similar" means
The score weighs:
- Subject overlap — same topic words.
- Description overlap — same problem described in similar terms.
- Resolution pattern — already-resolved tickets that match get highlighted; you can see how the previous one was handled.
It's not just keyword matching — the LLM groups by semantic intent. "I can't log in" and "Password reset email never arrives" might score 0.7 even with no shared keywords.
When it's most useful
- Recurring issues — you want to find the canonical resolution.
- Outage detection — five tickets in an hour about the same thing means it's not just one customer.
- Onboarding new agents — they can see how veterans handled the same question.
When it's worst
- Brand-new workspaces with few resolved tickets to match against.
- Highly customer-specific issues (account #42's specific data) where similarity doesn't transfer.
Cost
The FTS candidate set is free. The LLM ranking is roughly 3000 input + 300 output tokens — about $0.005 per click.
Off-switch
Settings → AI → uncheck Similar tickets. The button returns "feature disabled".