What's Up with Tech?
Tech Transformation with Evan Kirstel: A podcast exploring the latest trends and innovations in the tech industry, and how businesses can leverage them for growth, diving into the world of B2B, discussing strategies, trends, and sharing insights from industry leaders!
With over three decades in telecom and IT, I've mastered the art of transforming social media into a dynamic platform for audience engagement, community building, and establishing thought leadership. My approach isn't about personal brand promotion but about delivering educational and informative content to cultivate a sustainable, long-term business presence. I am the leading content creator in areas like Enterprise AI, UCaaS, CPaaS, CCaaS, Cloud, Telecom, 5G and more!
What's Up with Tech?
AI-Ready Enterprise: Your Journey to Making AI Work For You, Not the Other Way Around
Interested in being a guest? Email us at admin@evankirstel.com
The digital transformation journey has evolved dramatically over the past two decades, and now generative AI stands as the latest force reshaping how enterprises operate. But what does it truly mean to be "AI-ready" in today's landscape?
According to ManageEngine, the answer lies not in chasing AI for its own sake, but in understanding how it enhances your existing digital foundation. True AI readiness means "AI is doing the work for you, and you're not doing all the hard work to make AI work." This distinction forms the core philosophy behind their approach to artificial intelligence.
Drawing inspiration from SpaceX's methodical approach to innovation, ManageEngine emphasizes that breakthrough technologies require absolute clarity about your end goal, an optimistic yet balanced mindset, awareness of all possibilities, and no compromise on fundamentals. These principles apply equally to AI implementation as they do to rocket science.
The company's AI journey began long before the current generative AI boom, with machine learning capabilities incorporated into their products since 2012. What's changed now is the integration of large language models and the development of their own proprietary LLM technology, designed with privacy and data sovereignty as core principles.
Most exciting is their vision for "digital employees" - agentic AI systems that work alongside human teams. These AI agents operate within a controlled identity framework, respecting the same security constraints as human employees while tackling challenges like employee experience improvement, security alert fatigue, and cloud cost optimization.
Despite these advancements, ManageEngine remains committed to solving business problems first, with AI serving as a powerful enhancement rather than a replacement for their core capabilities. They'll continue offering both cloud and on-premises deployment options, recognizing that organizations have diverse needs when it comes to infrastructure.
Want to see how these capabilities could transform your enterprise IT operations? Reach out to the ManageEngine team to learn more about their AI initiatives and explore how they might help you navigate the digital transformation landscape with confidence.
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Everyone for always super exciting to be among customers. I always start with this message the idea of running an event like this, a user conference across the world. We do it across the world 2025. If I'm not wrong, we are doing 18 such user conferences, in addition to all the workshops and other events that we do. The reason I say ManageEngine we are in the 23rd year of running our business and it could absolutely have not been possible without all of you in this room. So thank you so much for being here. Appreciate you all taking the time, giving us all the feedback, giving us the encouragement and being here. So last evening we had wonderful conversations with a few of our friends, customers, this morning, nonstop. We absolutely treasure this experience. And a special note of welcome to Mike Happy to have you here among us, so looking forward to hearing you all the lessons. So thank you so much again.
Speaker 1:The next 35-40 minutes or so I'll talk about. I said we are a customer-focused, customer-driven company. I'll give you our perspective, manage Engine's perspective, on what are the things that are changing in the technology landscape. How is it affecting our customers? What are the problems that you are dealing with on your day-to-day basis today? What are your priorities? How do you want it solved? Right? That is on one side. On the other side, you also have pressing questions for yourself, right? So I am in this technology industry. Every few weeks, I'm seeing something disruptive happening. How am I supposed to navigate? And on the other side, you're also getting a lot of pressure from your management, right? So where are we on this race? So, in all the conversations that we have, we are not alone. We have the same question in our minds, inside manager, inside Vohkar, right? So this is what I would like to break it down, give our perspective how do we see what is happening in the technology world? Which is why I always talk about digital transformation journey as a series In the last four years, if you have followed us, we talk about how are we commuting in this journey?
Speaker 1:Because, like any other life journey, this idea, this digital transformation journey we have been all in this together for the last 20 years at least. It has had its ups and downs. We have seen a lot of bumps come along the way. We have had to take a lot of folks. It's never been easy. So this is what we keep telling ourselves at State Manager how do we understand. How do we navigate? How do we stay relevant with all that is happening around? How do we stay relevant with all that is happening around and since 2022, the biggest question on top of all our minds is this idea of generative AI. This is coming to us as a force. We want to know how to navigate. So this is exactly what I am talking about. A lot of our customers ask I understand what is happening. I have a roadmap. Show me your roadmap. What is your understanding of what's happening? What are you going to do? I want to map it. This is what we will do today and tomorrow, in addition to all the other capabilities that Manage Engine builds for you. So, talking about that question, so are we ready for the AI force that is hitting us right? So that's the top of the question.
Speaker 1:The analogy, coincidentally, that I have is from this place, right. So this happened October 2024. So if you are a space enthusiast, you could have followed it. This was the first launch of the SpaceX booster that they caught safely back, returning to the Earth, right? This, I thought, was an exciting moment. So, in terms of if you talk about any breakthrough in the technology world, this is like throwing a 40-story building to the space. Do some action, catch it back safely so that you could reuse it many, many times. Think about it.
Speaker 1:By itself, it is a major breakthrough, but if you think deeper, if this is really the end goal this is the objective that's not the case. So why would a company like SpaceX even attempt something like this? It's a monumental occasion. The real objective is someday we want to make humans a multi-planetary organization. That is the real end goal. That's the real end game. Towards that journey, you are going to see a lot of breakthroughs happening, and this was one Making rockets boosters reusable.
Speaker 1:Important thing is such aspirational transformation requires a lot of risk appetite. It's going to be taking a lot of time, like we talk about it all the time. Most of you know Shri Dharwimu. He talks about deep R&D is not cost intensive, it is time intensive. We have to give it a lot of time. That's what we believe in our company. Give problems the time Go deeper and deeper. That's how we achieve breakthroughs, right? So it calls for a lot of these things and to be able to. We talk about making humans multi-planetary. So this whole exercise needs to be efficient, needs to be effective, needs to be optimal for it to be run in a very reliably repeatable fashion.
Speaker 1:So these are important things, what it takes to achieve such a breakthrough towards your end goal, right? So SpaceX is a company I follow. Elon Musk is a person I follow. You may like him, not like him, you may agree with him, disagree with him on a lot of things, but people who push things, people who push boundaries, people who chase dreams and achieve breakthroughs are good to follow, right? So these are some of the lessons I picked from this exercise, right? So the first one is absolute clarity and conviction about the end goal. It's never about chasing breakthroughs, it's never about announcing something tomorrow. It's about the end goal, the absolute clarity and conviction. The second, the end trait is to have this optimistic, yet balanced mindset. You want to have lofty dreams, but when things fail, you have the mindset to accept, correct and move on. So that is extremely important as well.
Speaker 1:The third thing this is the conversation we had with a few customers last night and even today Awareness of all the possibilities. You really understand AI as a technology to clearly know what are the possibilities and what is not possible. So what you are attempting as an end goal, what is the percentage of possibility. Right, this is very important. And see, manish, here we were talking about doing this AI literacy course for your leadership, right? So is very important. And see, manish, you were talking about doing this AI literacy course for your leadership, right? So that was a brilliant idea, right? You cannot just have superficial knowledge and assume you know about all the possibilities. You have to do the hard yards, right? So awareness of possibilities is important. Your ability to blend data along with instincts this is, again, a leadership trait. We all learn the hard way. Data is important. Instincts are equally important.
Speaker 1:The next lesson absolutely no compromise on basics. This is something I again read a lot about basics. The first principle thinking, understanding, to be able to even think about something like making humans multi-planetary right, so these are important. Finally, resilience as an understanding Anything that you try as a lofty goal, you're bound to fail many, many times. Celebrate, learn, move on right? So very basic lessons. We just have to keep reminding ourselves of all of this again and again, because each such breakthrough fuels us ahead towards our ultimate end goal. Right?
Speaker 1:And you all who are all driving owning technology for your organizations, because today, let's face it, every business is a digital business. Every enterprise is a digital enterprise, so you all have the mandate to drive your enterprise forward. You know the end goals of the business, right? So this is the reality today, and one of the goals is to make your enterprise future-proof. With all the disruptive technology that you have at your disposal and aid that you have today generatively, conversationally, agentically, whatever it is it is a major breakthrough, a tool, a new power that you have in your hands. How effectively you handle that is going to determine how you meet your end goals, right, and the other conviction that we have today is the generative AI, or even agentic AI, for that matter.
Speaker 1:We believe it has gone beyond just being some hyper vaporware right, it is already starting to demonstrate value. We use it inside Manage Engine. We generate a lot of code today using the AI tools. We use AI to improve a lot of content that we write. We use AI to automate our level one support. All of that is happening.
Speaker 1:I'm sure that is the case with most of you. Right, it's already useful, but does that mean we completely replace everything? No, so these are some stories from earlier this year where companies, enterprises are able to demonstrate great value adopting AI. Right. So I'm sure we're all in the same boat, but we have to stop for a bit, pause for a bit and see for ourselves if we are applying the same traits, same lessons that we could get from a company like SpaceX.
Speaker 1:Right, you know your end goal, so you know your business objectives. You want to be future-proof. Do you do this exercise? Do you have absolute clarity and conviction about what your end goal is? It's very important. Do you have an optimistic mindset? At the same time, very pragmatic, also, balanced? Also, it's a question we ask ourselves right. Awareness of possibilities? Right, so this is something we are going to follow. So, this literacy course for our, for our leaders, right? So things like that, are you trying that already, which is, again, very important? Your ability to blend data with your instincts? This is again a question. These are all questions you ask.
Speaker 1:Do an assessment? This is how you come into a situation where you are able to confidently answer if you are AI ready. That's the whole point. Absolutely no compromise on basics. You want to leverage the power of AI, but you cannot take cyber security or privacy or your compliance to regulations very easily, right? That's what it means by no compromise on basics. Again, resilience as an adult.
Speaker 1:Any new disruptive technology that you take and adopt, you are going to have a lot of speed bumps along the way, right? So how you fall and how fast you get up really really matters. So, with all this in place, you have your end goal, right. So you do an assessment if you are ready. What it truly means to be AI ready today for digital enterprises like us, right so we used to have the same question we think about all the time. This is a simple definition. Being AI ready means AI is doing the work for you and you are not doing all the hard work to make AI work right. So this is very deep what we realized two years ago. We, as a company, forget about all the R&D we do, about artificial intelligence and machine learning. It is we, as a company adopting AI. We suddenly realized we have to do much more work to make AI work. Right. So this was the case.
Speaker 1:So an AA-ready enterprise is where AA just works in the background, right? Always give this example. If you're a healthy person, you're burning calories when you're sleeping, right? Not by just counting calories. It doesn't work that way. And if you're a wealthy person, your money should multiply when you're sleeping, not counting the number of hours you work. It's the same philosophy, so expanding further, of how you really become A-ready.
Speaker 1:This is where the idea of digital transformation journey comes in. A-ready is you're just being one particular face. If you see this as the evolution of digital transformation, you should have started at some point 20 years ago, 15 years ago, 10 years ago. The first thing you should have done really well is build your system of insights, or system of records. How did you digitalize all the manual things you had, the paperwork that you had, how effectively you did really determines if you were ready to even go to the next step. Once you had that ready, you went to the next phase, which is building the system of automation, a system of workflows. Right, you had to have these two working really, really well to even move to the next phase, which was the systems of experience. Regardless of where your road force is, regardless of the device they were using, the form factor, the application, they're getting great experience in doing business transactions.
Speaker 1:This is what is meant by building a system of experiences. Only if you had built these three systems, only if you had crossed these three phases well, you are even in a position of thinking about being a Reiki. That's what it means, right? So most of us want to be AI ready. Again, you have to ask the question where you exactly are? Any lapse in the previous systems or in the previous phases it's going to come back to bite you.
Speaker 1:So this is how we can visualize System of insights driven by records, system of automation, system of experiences will lead you to build your systems of intelligence. What this actually means, right? This just means you continue to hold the mandate for making it happen for your enterprises. It is your responsibility, your accountability, to build the system of intelligence, also in your enterprises, right? So that's what it means. So, if you are the CIO, if you are a technology leader inside your enterprises, right, so that's what it means.
Speaker 1:So if you are the CAO, if you are a technology leader inside your organization, how does things change? Right? Your mandates don't typically change big time, right? They continue to be the same. You have to run your day-to-day operations. You have to worry about security and compliance. You have to worry about risk management for your business, digital risk management, your workforce experience, your customer experience all of that, except you now have a lot of powerful capabilities provided by AI, right? So this is what I tell our customers. We don't want to claim ManageEnginecom is suddenly Manage manageengineai. There is no magic there. Right, we will continue to build what we are building. We'll continue to understand business problems of our customers. We will build solutions. At the same time, put AI as an important piece in our stack to help you Visualizing this in a completely different way I spoke about.
Speaker 1:You still have to run operations. This is one way to visualize your digital enterprise, which starts from your three W's. Any digital enterprise comprises of your workforce and I say workforce, not just employees. Any person that takes part in a business class could be a partner, could be a contract worker, gig worker, very, very temporary transaction. All of them are workstops Anyone doing any transaction on behalf of the business. A workplace is any place from where the business transaction happens. Need not be inside a building, right? So that's the idea. Workload is any technology component that comes in the way of a transaction getting executed. Need not just be a server of an application. Could be a browser tab, could be a kiosk. That's what we need to understand. So you still have to do your asset management well. You still have to do your patch management well, worry about the uptime and health of all the workloads that you have. So you have your operations layer built really well. It's when you can do your strategy layer better. How can I do better service management, how can I do better security information management, how can I build a security operations center? Or how can I run an observability program? These are all strategy levers.
Speaker 1:Operations and strategy help you to achieve outcomes. Outcomes like how effective, efficient, optimal you are to respond to incidents. So when incidents happen, you are not blinking, you are not reacting, you are responding. How quickly can you respond? This is an outcome, right? Or your ability to recover from a disaster, complete disaster, or your ability to immediately give evidence about your security posture. These are all the outcomes we are talking about.
Speaker 1:So what's happening? Insight, managed Engine. Our objective, our transient end goal, is to give a massive AI boost to each of these layers. So this is how we approach artificial intelligence today Not completely change everything to AI, keep doing what we are doing, but give the Managed Engine platform, give the Managed Engine stack, a very powerful, massive AI boost. So how are we doing this? This is something I wanted to talk about for five minutes, right. So anyone who wants more information, reach out to me, reach out to our team. We'll be happy to help. So this is not something we have been doing only in the last four years, after generative AI became a thing. I remember we started our AI initiatives in 2012. That is when we got started.
Speaker 1:By 2014, most of our products had machine learning capabilities. If you went to service management product, it had the ability to predict things. It had the ability to find the right technician who could work on a ticket. You go to our products on IT operations management, it was able to predict downtimes, things like that. We had machine learning models. That still continues.
Speaker 1:What happened after 2022? We had the power of large language models, right. So that is when GPT became a breakthrough in our industry. What we did an immediate short-term goal was to take available large language models. We made all of our products work with the available LLs, right. So this was the second step that we did, and now what we are doing is so service display works with one LLL. Endpoint central works with its own LLL.
Speaker 1:Now what we are building inside Managed Engine or, broader, zoho combination, we are building a massive central data platform, or call it data lake. All these products, their data, will go into this data platform. Once we have this ready, we will be able to leverage the power of intelligent, autonomous automation, in other words, the agent API model. So we are there. Anyone who wants to do a test run? So reach out to us. We'll be able to show what we are building there. So ZI agents are already there. The agents could be built by managers, by our partners or by you, right? So we'll give you a studio where you can build all these agents. I'll talk more about that later. In addition, we will also have the equivalent of chat GPT, right? We call it ASKZia. Zia is the technology inside Managed Engine, ai technology, so we'll have both agentic AI and conversational AI part of Managed Engine, natively part of Managed Engine. So some of you followed. Two weeks ago, we launched general availability of AskZia in service and this works with our own large language model, zia's own large language model.
Speaker 1:Because what is really the need for Managed Retail to build our own LLM? This is very important for us. We always want to be in a position where we can give this commitment, promise to our customers that privacy comes first. Data sovereignty comes first If you want your data to never leave management and go to a third party. You can choose to run with our own LLR. So that is why we are making all the investment. We have our own full stack with absolutely no external dependency For retrieval-based augmentation. We are making all the investment. We have our own full stack with absolutely no external dependency For retrieval-based augmentation. We are building the centralized data platform. We have our own identity and access management system with which, even for agentic AI, you will be able to do full identity lifecycle management. So we think intimate, we think deep is how we are building our AI capabilities into ManageIt. So this is very, very important for you also to understand.
Speaker 1:So I'm giving you the bigger picture. Anyone who wants to dive deep, please attend the roadmap sessions today, especially the service management roadmap, where we will demonstrate a lot of things in action. So this is our approach to managing. So, with this revisit, the same approach, managing it will continue to invest in all these layers because the businesses need to achieve their outcomes In the process, we will give a massive A-moves. This is managing its approach To every piece of operation you do, every piece of a massive AI boost. This is management's approach To every piece of operation you do, every piece of strategy that you do. Right, we are not putting AI as the most important thing and everything follows. No, that's not the approach. The business problems remain the most priority, right. How do we solve? Comes after, how do we leverage AI to solve those problems better comes number three. This is our approach to building AI inside manager chip. So, once we have this across the stack, you see, right, so you will have conversational intelligence and vertically, you see, you will have the ability to intelligently automate, autonomously automate a lot of these players. This is how we envision AI coming into managed engine. So this is revisiting. So I always talk about this.
Speaker 1:When we started in 2002, managed engine, we had two products, two tools, as we call. 10 years after 2012, 2013,. We have a set of products that talk to each other. It's two tools as we call 10 years after 2012, 2013,. 9th frame we have a set of products that copy each other, right, so, suite of integrated products Until 2025.
Speaker 1:Today, manageengine is a full-blown, seamless platform. It's like seen as one platform, even though we have 16 plus products. The idea is it behaves like one platform Flexible, seamless. You start with one platform, even though we have 60 plus products. The idea is it behaves like one platform Flexible, seamless. You start with one product. The second, third, fourth would come in seamlessly, talking to them. That is the mission that we are working on, and now we are giving it, this platform, a massive AI boost. We are not calling it as an AI platform. That is the big distinction. So a massive AI boost, we are not calling it as an AI platform. That is the big decision. Right? So the platform will go on the same way.
Speaker 1:Our focus on operational layer will continue, how we have built a tool for managing your active directory. Infrastructure. Patch management, network monitoring will continue. You can see the way we see digital enterprises the three Ws, the devices, the identities, the three Ws, the devices, the identities, the applications. We'll continue to see them that way. Build tools on the operational layer. On the functional or strategic layer, we'll continue to have these product speeds right. We'll have service displays giving you a unified experience. So it was an IT ticketing tool. It became an IT service management system, it became enterprise service management. Now we are calling it the unified service management system. So that is how our products are evolving into platforms. This focus will continue.
Speaker 1:In addition, we will also build a services layer, not just AI. We will have search capabilities working across the products, analytics working across the products. Analytics working across the products, workflows cutting across and executing across the products. You go into Service Desk Plus, create a workflow. The same workflow instance should be visible from endpoint central, should be visible from inside your lock list. So that is the vision that we are pursuing. In addition, there will be a lot of focus on AA and ML. We have the management labs division inside the company that is doing some deep research. As they make breakthroughs, they find their way into the management stack. So this is how we are operating.
Speaker 1:Once we have the operational, functional and services layer built is when we will be able to deliver solutions for you right, solutions for specific needs. You are building a network operation center or a security operation center. You are building a compliance center. You are building a competency center so you can put the managed platform capabilities together to build solutions right. This is the vision. This is the evolution of managed, helping you drive specific outcomes. I'll spend a few minutes giving you specific examples of what we mean by outcomes. Improving increasing employee experiences or workforce experiences is an outcome Improving your security portion or your resilience levels is an outcome, or your levels of efficiency, right. So these are all outcomes that you are thinking about. Your business leadership is thinking about how do we achieve that?
Speaker 1:I spoke about how we are building the agentic AI systems inside management. We build all these products. These products collect a lot of wealth of data across your infrastructure. Push it into the central Zoho data platform. That gives you the power of agentic AI. It doesn't stop there. We have our own identity and access management system where the model is, along with the human employees, part of your workforce. We will create the equivalent of digital employees. So you have to provision them in that central system. You have to have entitlements defined, access control defined so the agents operate under a controlled environment. So they will respect your access control laws. They will respect your privacy constraints all of that right.
Speaker 1:So take an example like this you run a survey about your employee experience inside your company. The survey comes out badly right. So what would you have done before we all had agent TKA? You have to do a lot of manual things, including going through the survey response tool, doing the planning, executing those actions. Now, with the advent of intelligence autonomous agent, you create equal digital employees which will look into the survey results, right, so? Send to all the answers, find what are the top points. Right, so you have a special agent for that, right.
Speaker 1:The problems could be something like slow resolution or application performance issues. So this is how an AI agent could. You could build agents like this subject matter expert, right so? Or an onboarding agent. These will work with the power of LLMs in the background, automate intelligently, automate autonomously, automate a lot of these actions. They understand all these problems. These digital employees, these digital agents, will act like anyone that has India's experience operating your infrastructure. So this is the model that we are moving on. So this is what I wanted to convey. You could also have an orchestrated agent orchestrating all of this happening, at the same time giving control back to you. These agents will be able to explain why they are doing a particular action, why they even chose to do an action in a particular way, and give you the option to override right. So this is the model we are moving towards. With this, you see the business impact that it can make. What could take weeks or months could be solved on a daily basis. So this is the model we are moving. We are piloting this in SIG Managed Engine, so we hope to have this coming into our products pretty quickly. So this is one example of how agents could be used for improving employee experience. The other case is cyber resilience right, so you could be a big multinational bank or airline right, so serving millions of customers.
Speaker 1:The big problem always is when you're running your security operations center. Is this alert safety, primarily caused by the number of false alarms? You have Big volume of false alarms combined and multiplied with your lack of ability to properly triage incident. You don't know, your team doesn't know, what is a real incident, what is a real alarm, and they have many of them. They don't know to triage. What is the first problem? I should be working, so this is not a problem. Humans should be working on Best. Left to agents. This is what we are doing, right? We are creating digital equivalence, digital agents that would act like analysts L1, l2, l3 analysts. We could also build strategy agents right, so we could also build decision-making agents all of them with which you will be able to crack both your number of false alarms multiplied by the alert fatigue right. So, because these digital employees don't have the idea of getting fatigued. That's the idea. So this is the business impact that we can hope to have with such a system. Again, going back to how effective the central data network is, that is where all the effort inside managed engineering is going. Same goes for efficiency and cost optimization.
Speaker 1:Most of us run our infrastructure in a hybrid model. You have a lot of infrastructure on-premises, many sitting on the cloud, multi-cloud, multi-hyperscale infrastructure. Oftentimes you do not even know how much you are paying or what you are paying is really worth it. Are you getting the right returns? This is a huge challenge, right Again, this is not a problem. Humans should be spending all their time on this is is, again, the cio's big problem. Right? So now you have the ability to create multiple different autonomous intelligent agents.
Speaker 1:You could build a research agent, analysis agent. What is the research agent? Right? So this agent? On a daily basis, hourly basis, like following the stock market, go look into publicly available information in Asia, if you are paying the right price for the infrastructure you are operating. And then you need to have an analysis agent that looks at all the spending that you are doing, your credit card expenses, your invoices, all of that right, and match it against what you should actually be spending, right? So this is what we mean by building on these agents Directly delivering you business impacts right. Much reduced operational costs, faster incident revolutions all of that, right.
Speaker 1:So if you're interested, please reach out to us. We'd be happy to discuss a lot more, because these are things that need a out to us. We'd be happy to discuss a lot more Because these are things that need a lot of validation. These are business problems. Like I keep emphasizing, we want to start from the business problem. We want to understand this is really a problem for you. We want to understand how you want to approach solving this. So, do you want to trust something like an AI agent? Would you trust a digital employee? How do you want permissions to be run? So, what is your feedback? Because most of you could already be using such systems, right? So we use this event to have this opportunity to also take your feedback, navigate our ideas.
Speaker 1:But this is the path, this is the approach we are taking in Manage Engine as we evolve, like I said, from set of products to a suite of integrated products, to a platform which now gets massive boost, both conversational intelligence as well as autonomous automation intelligence. So, in addition to that, our progress, our investments, our efforts building tools will never, ever go down. It will only increase. We will continue to build specific tools for all the operations you do Like. You see, it was four domains some time ago. Now we have added the low-code platform into the mix of managed engine. We have a solid analytics platform coming into the mix. Each of these domains, as we speak, is getting very strong. The service management, our log management, identity management, endpoint management and security All of this is getting strengthened and these strong platforms will come together with the power of AI to deliver you an AI-powered managed agent platform.
Speaker 1:The other important point we started managed agent delivering on-premises products. I understand most of you still need at least for some of you, a critical strategic need an on-premises option as well as cloud option. As we speak, our investment in both the models will continue. We will continue to offer both on-premises and cloud. Even that effort will not go down, but you will see AI coming in cloud a lot more earlier. This is another question a lot of customers ask why do you put all your AAs in cloud? We are not ignoring on-premises, except bringing AI into on-premises is not as straightforward as just for cloud, but other endeavors to have them on-premises and cloud.
Speaker 1:The AI boost that I talked about will be very similar. So this is a commitment, assurance from our side how managed it will evolve, because I spoke to a few of you in the morning how managed it is helping you make your life very simple. Right? This is exactly what we want to hear. The products need to be useful. We'll just bring the right dose of AI to make your life a lot more simple. That is the promise, because we all live with a lot of challenges. I like to call challenges as possibilities. We are living in a universe of many, many possibilities that you want to pursue. The commitment, the promise from Manage Ingenious In that journey of yours, dealing with these challenges and possibilities, we will be with you together. Right With that, I wish you may you all live long and prosper. Thank you so much. Thank you. I'm not taking questions now, but we are going to have an exclusive Q&A session.