Five tickets about damaged shipments from the same supplier. Three checkout failures tied to the same application. Two store locations reporting the same issue two weeks apart. Individually, they look like isolated problems. Together, they're a pattern — and patterns are where the real operational risk lives. The problem is that most teams never see them.

Why Patterns Stay Hidden

It's not a people problem. Your team is doing exactly what they're supposed to do — logging tickets, resolving issues, closing them out. But when you're managing dozens of incidents a week, nobody has the bandwidth to cross-reference tickets manually and ask "wait, have we seen this before?"

Tags help, but only if everyone uses them consistently. Filters help, but only if you know what to look for. Most of the time, the pattern only becomes visible in hindsight — after the third supplier failure, after the fifth checkout error, after someone finally says "this keeps happening."

By then, the damage is already done.

Introducing Recurrences

Resolve now automatically analyzes your incidents and groups them into similarity clusters — no manual tagging, no configuration, no dashboard to maintain. Using AI, Resolve identifies not just that incidents are similar, but how they're similar. That distinction matters more than it sounds.

A cluster of incidents sharing the same root cause calls for a technical fix. A cluster tied to the same vendor calls for a conversation with your supplier — or a new one. A cluster concentrated in the same store location points to something environmental or procedural that no amount of engineering will solve.

Resolve surfaces all of this automatically, so your team spends less time connecting dots and more time acting on what they find.

Recurrences that actually mean something

When Resolve groups incidents, it tells you exactly why they belong together — and the type of similarity determines what you should do about it.

• Similar Impact — incidents that affect operations in the same way, even if the surface cause looks different. Useful for understanding the business cost of a recurring pattern before it escalates.
• Same Application — multiple failures traced back to the same system or integration. A signal that something deeper needs attention beyond individual fixes.
• Same Vendor — incidents linked to the same supplier or external provider. The kind of pattern that turns a support conversation into a procurement decision.
• Same Root Cause — different symptoms, same underlying problem. Often the most actionable cluster — fix it once, close multiple failure modes.
• Same Store Location — for distributed operations, incidents concentrated in a specific location often reveal process, staffing, or infrastructure issues that won't show up any other way.

These are just a few examples. Resolve detects similarity patterns across a wide range of categories tailored to your industry — from equipment and infrastructure to processes and external dependencies. Each cluster comes with an AI-generated description explaining what the incidents have in common and a list of the most recent cases — so you always have the context you need to act.

From Data to Decisions

Knowing you have a pattern is only valuable if it changes what you do next.

When a manager sees that six incidents share the same vendor and the same type of impact, that's not just an operational insight — it's evidence. Evidence to escalate a supplier relationship, renegotiate contract terms, or make the case internally for switching vendors. Evidence that's objective, timestamped, and built from your own operational data.

That's the shift Incident Similarity enables — from reactive firefighting to informed decision-making. Your team was already generating the data. Resolve just makes it visible.

Incident Similarity is available now for all Resolve Business plan users. Open your dashboard and see what your incidents have been trying to tell you.