knowledge graph. Once you have the knowledge graph, then we wanted let the agent to navigate the knowledge graph. So, the knowledge graph is not just something the agent looks up for data. It is a control plane for the agent. So, what do you mean by that? So, the knowledge graphs dictates what the agent can look into, what path it can take, what investigation hypothesis uh it can evaluate. So, for example, if you when you do this analysis, the root of the problem, say something like your TRX is declining at a national level. This could be when you do source localization. So, that's our uh contact for how to find the where. It might happen within a region. It could be concentrated in a territory. It would be concentrated in a combination of a territory or a pair or an account. So, there are whole lot of dimensions which the agent needs to evaluate. Now, it's a lot of permission permutation combination. So, the knowledge graph guides the agent on how to find where this is concentrated. Then the why why part of it. Why it is happening? When you figure out that okay, something is concentrated at let's say the decline is concentrated at a particular region. Now, you need to figure out the why. This is where where the KPIs and the relations come comes in. Once the agent is able to narrow down the where, then it's able to go and figure out the uh figure out the why part of it. Which KPIs is driving what? Graph access the control surface. So, agent every edge is a hypothesis. So, the agent can go and evaluate that hypothe- hypothesis. Uh it doesn't go outside of this. So, that gives a more bounded surface for the agent to investigate.