Multi-agentic architecture is needed when a large, complex goal must be broken down into discrete steps, with each step handled by a specific agent tasked with executing that narrow task before handing off to the next.

3:59our GenAI presence and now an agentic presence in the past 2 years. Talk a little bit about um kind of the the motivation for multi-agentic systems. Where does the the need for multi come in? So, um so here here is here is the philosophy behind it, right? We moved from a classic ML world to a world where we have LLMs generating responses and now we want to

4:29move on to a world where actions need to be taken. Specific goal-oriented actions need to be taken. And when the problem that we are working on is a complex one uh with the multifaceted uh aspects associated with it, that's where multi-agentic comes into place. So, basically, we have a large complex goal which we have to break down into specific steps. And each step is basically narrowed to a

4:57specific agent. And that agent is tasked with the goal of executing that specific task. And then you move on to the next agent. So, a multi-agentic system or architecture orchestrated system comes into play when you have a large complex goal which can be broken into steps and you can take this entire system to fruition of that one complex goal that you have. So, that is that has been the founding

5:24principle behind uh our our backing of multi-agentic architectures. Let's maybe make this more concrete by talking about a specific system that you developed and deployed. It's called Chat Concierge. Uh tell us about Chat Concierge. What is it and why does it exist? So, Chat Concierge for us was our beachhead initiative around deploying multi-agentic deploying a multi-agentic solution. So, uh Chat Concierge is essentially auto dealership uh project or application that was