I previously worked on a project where we have a table of cases and we predict the group it goes into based on the case description through Python. We were able to do this successfully but now we are trying to assign some people to work on each case based on the prediction.
I have thought about separating the groups first using rule-based row filter, and then using a simple rule engine (if group=a, then input agent A) but there are many agents within one group. The caveat is to be able to assign cases to each agent more or less equally, looping through each case within that group.
Case table
Agents table
Expected outcome should be the case table with an appended column that loops through each agent.
I tried to look up other posts but there seems to be no topic opened for this yet.
I tried to create a sample workflow on this but the table outcome isn’t quite right. The agents aren’t being looped after the first iteration and thus creating blanks in the table.
this waas interesting! Although loop is a what first might come to mind here is a way without it. Idea is to bring list of agents on project and then pick one by one from the list using mod function for which you need rank inside project and count of agents on project.
