Been working on a workflow where we pull daily attendance logs from Vertex HCM into our payroll processor automatically. The idea was simple enough on paper but the actual implementation threw a few things at us I wasn’t expecting.
The main issue is that Vertex HCM exports attendance data in batches at the end of each shift cycle. Getting UiPath to watch for that export, validate the records, flag exceptions like missed punches or overtime breaches, and then push clean data into payroll without manual intervention took more back and forth than I expected.
Currently using a combination of file system trigger and a scheduled bot but wondering if anyone has handled something similar with an API integration instead. Curious whether that approach ends up being more reliable or just trades one set of headaches for another.
Has anyone built something similar with an employee attendance management system and run into issues around exception handling for incomplete records?
With use case detail you mentioned, using APIs would not have much difference since the shift cycle update is key here. You can leverage APIs to reduce UI operations which can make your code more modular and reliable. Apart from that I don’t see much difference.
Would love to know more, if other members have any solution.
Your current approach using file trigger and scheduler is actually standard and works well for batch-based systems like Vertex HCM, but the issues with incomplete records are expected. Using an API can be more reliable and real-time if the system provides proper status flags (like finalized or approved data), but it won’t completely eliminate exception handling.
The optimal strategy is to add a validation and retry layer process only complete records, hold or recheck incomplete ones, and handle exceptions separately. In short, API can improve control, but strong validation logic is the key either way.
In the case of handling incomplete records, depending on the turnaround time that you require you can always add all of the incomplete records to a data table and at the end of the process send those out to a human for manual validation. This would allow the “valid” data to go through in a timely manner, but it would still require human involvement. that would also give you the option to have that user resend the data table back into the automation with the valid information and it would fill in the gaps.
For the API integration aspect, I think API adds more robustness to the automation however that would be more up to you and your specific use case
Exception handling as a separate queue workflow rather than embedding it in the main sync process solved this pattern for us. attendance tracking software data from Vertex HCM into legacy payroll worked cleanly once partial day leave adjustments were processed as a pre-calculation step before overtime rules applied rather than simultaneously in the same transformation logic. Documenting edge cases exhaustively before building saved more development cycles than any technical approach. What is your current exception rate on the validation step?