With 100 concurrent projects, checking actuals against forecasts meant opening every time card manually. Clutch described their rules in plain English, and the agent enforced them from day one. First rule took three minutes to set up and test. Now exceptions flag themselves, wrong entries get blocked at submission, and the team only sees what actually needs them.
Video transcript
We're a fintech startup, managing about a hundred projects concurrently. If you wanted to see whose time significantly exceeded what they were forecasted for a given project, you had to dig into somebody's individual time card. You had to also, you know, manually look at what their forecast was, and reconcile that. So, you know, being able to have these, these AI time sheet policies, really just allows us to save a whole bunch of manual work and do a whole bunch of new things that we just simply weren't able to do before.
Three minutes to create a rule, test it, it worked the first time, you know, let a whole team, you know, submit, you know, thirty time cards for the previous week, see flags on a handful of them, spot check those flags, they're all accurate. Honestly, the process couldn't couldn't have been smoother. It just worked exactly as advertised. I spent thirteen hours this week getting them live.
I worked a total of fifty four hours. Is anybody even going to see that? And you're seeing flags pop up, and you know that your manager is going to see that flag. Hopefully, that makes them feel seen and lets them know that, like, their workload and their potential burnout is is really important to us as a leadership team.
There's more important work to be done than, like, manually shifting through time card entries every week.