Aito predictive database runs machine learning on relational datasets using queries. Like ML, but easier and faster. Like a database, but predicts unknowns. Truly mind-blowing.[…]
Machine learning so clever it needs no training, now in UiPath.
RPA practitioners often face situations where they need to work with imperfect data. As a result, we see less than optimal automation rates or sometimes even abandoning the desired workflow as the estimated value creation does not justify the development cost.
We see these examples all the time. Here are some recent ones.
Document extraction was not able to get the VAT category per line item reliably, so automation performance was low.
Purchase invoice processing automation was not able to complete workflows, as it did not know the cost center to assign invoices to. Humans still need to be involved all the time.
Sales lead assignment could not be automated in fear of losing valuable deals. Finding the most suitable sales rep for the lead requires non-deterministic judgment.
Do you have a similar example?