Exception handling and escalations

Exception handling and escalations is a layer that sits across your processes and deals with the cases that break the normal path. As work moves through a process, it watches for the edge cases: a mismatch, a missing or malformed field, a value outside the usual range, an unusual request, a failed step. When one appears, it catches it, works out what kind of exception it is and who owns that kind, and routes it to the right person with the context to resolve it. Then it tracks each one until a human closes it, and logs the pattern so recurring exceptions can be fixed at the source. A person resolves every case. The software makes sure none get lost.

Alerting fires a notification and moves on. Logging writes a line to a file someone might read later. Both leave the actual work to whoever happens to see it, which is how exceptions end up in a channel nobody watches or a log nobody opens. This is different. It classifies each exception, decides who owns that specific kind, routes it to that person in the tool they already work in with the context attached, escalates if it sits too long, and tracks it until it is resolved rather than just announced. A raw alert tells you something broke. This gets the right thing to the right person and makes sure it actually gets closed out.

No, and that is deliberate. The software catches, classifies, routes, chases, and logs. A human resolves every case. The reason is simple: an exception is by definition the situation the normal rules did not cover, so it is exactly the kind of case where letting software guess an answer causes real damage. Having the AI silently resolve a case it does not actually understand is the failure mode this is built to prevent. What it does instead is remove the part that wastes time, the noticing, the hunting, the working out who should handle it, and put a well-packaged decision in front of the person best placed to make it.

Together with you, against your real cases, during setup. The first days go to naming your actual exception types, who owns each one, how urgent each is, and how long is too long before it escalates. This is the judgment-heavy part, because rules that cry wolf train people to ignore the alerts, and rules that are too quiet let real problems sit. So the rules get tuned against real examples before anything goes live, and the log surfaces the ones that fire too often or route to the wrong place so they can be corrected. A misrouted exception is worse than a visible backlog, which is why this window is where most of the work goes.

It plugs into the tools your processes already run through. CRMs such as Attio, Salesforce, and HubSpot; team chat like Slack and Microsoft Teams; email such as Gmail and Outlook; accounting systems like QuickBooks and Xero; project and ticket tools such as Jira and Asana; and automation platforms like Zapier and Make. It reads exceptions out of wherever they occur and routes them to wherever the owner works. Most tools with an API can be added. The audit maps your exact stack and picks the processes where stalled edge cases are costing you the most.

Usually two to three weeks. The first days go to mapping your real processes, listing the exception types that actually occur, and naming who owns each one and how fast it needs to move. Then the catching, classification, routing, and escalation get built and run against your real cases, so the rules are tuned before anything routes on its own. You are live on a first process quickly, and the testing window is what keeps the system from crying wolf or misrouting once it is handling real exceptions.

Two parts. Tooling runs as a monthly cost for the model usage and the routing, typically a range that scales with how many exceptions you process. Implementation is a fixed scope, quoted once the audit maps your processes, exception types, owners, and escalation rules, so you are pricing a defined build rather than an open-ended retainer. The audit itself is where the scope and price get set against every other opportunity in your business, so you are not guessing at effort up front.