Granted, neural networks were not generally applicable to this problem at the time, but this whole idea seems like the same problem being solved again.
Telecoms and IT used to supervise their networks using Alarms, in either a Network Management System (NMS) or something more ad-hoc like Nagios. There, you got structured alarms over a network, like SNMP traps, that got stored as records in a database. It’s fairly easy to program filters using simple counting or more complex heuristics against a database.
Now, for some reason, alerting has shifted to Slack. Naturally since the data is now unstructured text, the solution involves an LLM! You build complexity into the filtering solution because you have an alarm infrastructure that’s too simple.