Great. Thank you for the introduction. Good afternoon, everyone. Hope the event is going well for everybody here.
So today, we're going to talk about something that is driven by what we're seeing in the industry, and it's something that is going to be impacting everybody who is doing anything with IAM irrespective of what tool, and what framework, and what technology you're using. Fundamentally, what is happening is that we are really seeing that there are three dimensions that is actually impacted by IAM when it comes to the IAM economics.
First and foremost is everybody's talking about AI agents, what it can do as your digital worker, and what it can do in terms of your transformation as part of your solution, and all the things that it helps in minimizing the effort by the humans and so on. The second piece is around things that we do as an IAM practitioner. We design a configuration. We design workflows. We do application onboarding. We do configure access policies, authentication policies, and so on. All of these are going to be simplified by IAM in terms of how you do things.
That's where I'm going to spend a lot more time talking about today, addressing a unique and important segment of the IAM community, which is around designing your IAM piece and how does AI help in that. And the third, of course, is something that all of us who are in the vendors community, what we do there is the AI capabilities themselves are helping us reduce the effort involved in building new features and new capabilities. So what does it mean when you have the runtime side, the design time side, and the software side of things helping in our activities?
It just means that there is going to be a trend where the cost of IAM for an organization is going to come down. And we are going to see that over a period of time and kind of stabilizing.
Today, there is significant cost involved when you talk about anybody running an IAM program in terms of how they do things. So AI is going to have an impact where the vendor cost is going to come down, implementation cost should come down, and even the operational side of things should come down. So overall, the TCO for an enterprise which is running an IAM program should come down, and you'll see trends related to that. So the driver for this was to see how we are going to bring AI into a mechanism where the TCO can be reduced.
So the reality is that you'll find that we never almost see that you just configure something and go away. There is always so much activity that really happens with IAM, and it's not at all repetitive for us, and it is very custom. Every organization has something that is specific to them, and there is a lot of activities surrounding their own set of doing things, and deployments tend to be very customer-specific. And then every vendor, every SI, every organization have their own set of tools in bringing in the IAM program into reality, and you'll find that it's not uniform, not consistent.
It's fairly fragmented, and every SI would also build something that is custom-made for their deployments. There is no standardization. Standardization for them, and even if you're a large SI, you'll probably have half a dozen or a dozen different mechanisms in which you do some things, right? So a fair amount of tribal knowledge that happens within this enterprise when you try to do your deployment, and it is kind of spread out. Nothing is central. The net effect is that your IAM program has the risk of being slow, and it's expensive.
I don't know of anybody who has seen any IAM program that they call it as it hasn't been expensive. It hasn't been over-budgeted, right? So given this, what we're trying to do here is we're really looking at the fact that the IAM itself is both a design kind of a problem and also an execution problem. This is where I'm talking about the runtime side of things, and most efforts, people are looking at one side. Everybody's talking about AI agents, what it can do, and how do you make it part of your solution, right?
But how many are actually looking at how can you use AI for your IAM design, right? This is what we are going to see in this presentation. So the model is that people can choose one versus the other, or people choose both as they deem fit, and they'll see value both on the design side as well as on the runtime side. So essentially, we are looking at two planes, right?
One is completely surrounding an environment where you are designing your artifacts, you're managing your integrations, your policies, your governance controls, and all of that, and then the second part is truly the agents which are performing your scheduled activities, your policy executions, and your risk computations, and analyzing your risk, and so on and so forth. So two planes in which we operate. One is the design plane and the runtime plane. So think of it as the fact we are referring to is the agent studio itself is something that will help you design and build your various artifacts.
So what does that mean? So think of this exercise as something you do in software development, right? So you gather requirements, you then transform those requirements into use cases, and then you get a technical specification, you build code, and it gets deployed. So we want to look at IAM as a software program, right? Not just some arbitrary thing that you just go configure in some UI and say, yeah, I deployed this, right? So there is no reason for us to look at IAM configuration deployments like people were looking at before.
So you can truly go through this whole process wherein you can do exactly what you do in software development programs with IAM programs as well. And how do you do all of this? This is all completely facilitated and supported through a chat interaction. So what does this studio actually do, right? It'll help you create your policies, workflows, schemas, and it helps you do it with best practices. So the studio is smart enough to know what are the right ways in which you can implement something.
You know, there are multiple ways to look at it. There could be best practices, you know, what the industry uses, there could be best practices based on a vendor offering. There could be something that your own organization comes up with, right? And all of these artifacts can be validated through a validation phase. And you can manage this like any other software that you manage today, right?
You know, when you do development of software, you have a source control repository where, you know, you go through reviews and it gets pushed into production and all the good stuff. And then traceability. So where is the traceability of any IAM deployment? It's probably maintained in spreadsheet, if at all, maybe somewhere in SharePoint, maybe it's in some PowerPoint somewhere. Nobody knows where those things are, right? And then reusability. This is another big piece. Everybody has, you know, artifacts that get developed.
If you are an SI or if you're an organization, where are you storing and sharing and managing all your, you know, design artifacts? Where are they? Where are the reusable components? The systems are not facilitating, you know, a mechanism to do this. So what we are trying to do here is, we are trying to deliver something. Think of it as, to put it simply, think of it as cursor for IAM or a cloud for IAM. That's what we are talking about. So I wanted to get to a point where you understand where you can come interact with this platform and it will help you design those artifacts.
And you can take those artifacts and push it into any environment. It could be a Nokta, it could be a Microsoft, it could be a SailPoint, it could be Tubera, it could be anything. So you can push your design artifacts into those systems through this interface. So what can an IAM designer do? Think of it as a platform where a designer would come and say, I want to do a POC and here are the applications. And the system would come back and work with you on how to go about building the POC. And it'll say, here are the things you want to do.
For those of you are familiar with, you know, cursor and cloud and those tools, they actually give you those step-wide instructions on, hey, here is what you want to do. Here's what we know about your environment. Here are my recommendations to go about doing these things. So there are multiple different use cases, again, for a designer. It could be a set of things that you got in a rod and structure format. You get requirements in an XLSP, a Word doc, could be some nodes. You feed all of that and say, can you make sense out of this and help me run through this particular flow that we want?
And it's independent. Like I said, it's vendor agnostic.
You know, you should be able to do anything with any particular environment that you have. So the system is fairly well aware of certain set of vendors with whom integration has been done. And then it'll allow you to refine your design as well. So you might have done something with some workflows a year ago. You can come back and say, here are the changes I want to make. You can literally say that, here are the changes I want to make, as opposed to going into 25 screens and trying to figure out, I need to do these changes in 25 screens.
It has got the knowledge of what has happened with regard to the deployment itself. So if you take another persona and what that persona will do, just put up something for a program manager. So if somebody can want to come and ask, tell me what has happened in this deployment. I really want to know what has happened in this deployment. And you might say, we did this design. What exactly did get pushed into production? So it'll answer those questions for you as well, any gaps that you want to assess.
And it'll also help you do things that are consistent between your different systems and how you want to operate. Essentially, you can get real-time assessment. You can do migration to modern systems. You can do things that will help you analyze how your current deployment has been set up as well. So a whole bunch of use cases that you can imagine that could be done through this platform. So the idea is that, if you have migration, if you have situations for reuse, you have a redesign, this kind of environment helps you build these.
And it serves as a system of record or a system of truth to manage your environment in an effective way. So the idea is that the dependency on SMEs or specialists is going to come down through this model, where you can really leverage what systems you have and take things forward.
Similarly, on the runtime side, so far I talked about the design time, designing your artifacts as you're going through building out stuff. Then you also have things on the execution side that will allow you to complement or to take your design into any of the specifics around runtime activities. So the platform allows you to do both design side of things and runtime. As you can imagine, it could be a whole bunch of things, running workflows, running your scheduled operations, and things that help you in bringing in the right visibility and intelligence into the platform itself.
So there are a whole bunch of agentic use cases. I won't go through each one of those, but you can understand that it's about taking all your governance processes and being able to automate and run them in a scheduled manner, including some auditability and reporting that you would want on a regular basis. So the real question is, you can do with this automation both on the design side and on the runtime side. So the idea is, it will help you reduce your overarching burden that you have in your deployment itself. So the platform also allows you to build your own agent.
So the same way I was telling you design your IAM artifacts, you can actually talk to it and say, I want an agent to perform these activities. And it'll actually build you an agent, and you can set policies on those agents and then run it against any platform that you have. This is not tied to any one particular platform. It is tied to a process. So you tell it what process you want, and it knows how to take your requirement from that process into a specific underlying vendor solution out there.
So as you can imagine, this is certainly something that significantly helps organizations in faster IAM delivery. Just like what Cursor is doing for software development, this platform will help people do faster delivery and reducing the implementation types as well as the cost. And more importantly, the operational overhead that people will have in dependency on specific individuals and requiring their involvement is reduced.
Overall, the system and the platform is continuously audit-ready, because at any point in time, you can come and say, give me a snapshot of what's happening, and it'll be able to give you that piece of information. Things that your underlying IAM solution might not be able to do, it can build these things. So you think of it as a layer on top of whatever you have underneath. Everybody has their own platform underneath. This helps you smoothen the execution and the operational side of things.
And the key takeaways for us in this would be, first and foremost, the idea of bringing AI from design as well as execution. There is dual capabilities there. And then it allows you to pick one versus the other. And the fact that it is vendor agnostic kind of helps people do a comprehensive offering for their situation. And it brings immediate value. So you can quickly come and see what's going on. Let's say you have a particular vendor deployment, and you can launch this tool and quickly ask, tell me what's happening in this environment. What are the things that I need to pay attention to?
How can I improve this? Just like pointing cursor or clock to a code base and say, help me understand what is happening in this code base. Or help me build something unique or improvise on something. And then you can always take this model to build new capabilities on top of what you have. Because IAM is a phased approach, and incrementally, you need to improve on things. This will actually give you a more consistent uniform model in helping you understand what that transformation is going to be.
And even if people come and leave, you have the knowledge base, and you have the system that will fully understand and support in that journey. So the fact that people are leaving, everybody worries, oh, that person knew how this integration worked. What do I do? That information is lost. That's not true anymore in this model. And last but not least, the customer has a good handle on what's happening. They don't really need to go reach out to an SME or the partner who actually did the deployment. They can actually ask the system to say, where exactly are we in our journey?
What are the things that we need to pay attention to? Because the system is smart enough to understand and give insights into where those improvements should be made. So that's what I wanted to cover today. It's something that we have launched, and people can actually take a look at this and sign up for a demo. Or even if you are interested in doing early access and try it out, we're happy to work with you on that. Thank you so much. Thank you. Thank you. Thank you.
