Short answer: Emanuele Melis says separate agents check transactional databases, documents and monitoring logs, turning what used to be a week of investigation into a report within a couple of hours so a person can reply to the customer.
Watch this answer from Episode 46 (starts at 12:05) · Episode 46 notes and transcript
From Episode 46: We Tested Claude 4 Fable and Deployed Enterprise Agents Without a Single Data Migration, starting at 12:05.
Jordan Metzner [12:04]: Okay. So Emanuele, like walk me through a use case like obviously like, you don't have to tell me the company like Coca Cola per se, but just walk me through kind of a pharmaceutical company or kind of, what kind of enterprise was coming in here and what kind of tools are they popping out that have really impressed you guys.
Emanuele Melis [12:17]: I'll tell you my favorite project because I never thought that was I've never I never thought in my mind I would see that type of project being deployed in a regulated environment. I just never thought in my lifetime we will see AI doing that or a version of AI, Gen AI, however you want to call it, which was effectively user request comes in. So somebody receives an email. Now usually that email means a person has to spend a week investigating something that happened on the back end. And usually the email is about money so people are very nervous and you know whomever sent the email, they want to have a response right away, they wanna make sure that doesn't happen again And the person investigating, they have somebody on their shoulder that drives them to go fast, get response, let's go back to the client, find the root cause, who needs to fix it, what happened, when, why, all those things.
Emanuele Melis [13:13]: And so what I'm really seeing is when you have when you can build a sort of agency and scenes to help the person do that. Now what used to be a two days investigation now compresses to one day. And you have an agent that goes on the bucket system transactional database and get all the transaction. You have another agent that goes in and checks the documents. Is there an edge case that should have been taken into account or was it? And then you have another agent that goes into the logs and says, is there a failure in the monitoring system that was supposed to be caught or was missed because of x y z reasons? And now you end up after a couple hours of what used to be a week of work, you end up with a report that tells you exactly all the data points that a person needs to then draft an email to the customer. The agent could draft the email. Sure. But the idea is that you don't need a person going into and keying at the keyboard onto that system.
Emanuele Melis [14:12]: What happened for customer one two three on that day, at that time? And the agent will be much quicker because they also can effectively brute force their way into the systems and just run multiple hypotheses at a much higher speed than a person. Right? So that is the one use case that I never thought I would see happen really, especially in highly regulated environment, but I'm seeing a lot of traction because it actually make a diff it does actually make a difference to Baba to the everyday life of people.
