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What's Up with Tech?
Autonomous Enterprise: The Future of AI-Driven Operations
Interested in being a guest? Email us at admin@evankirstel.com
The dream of an autonomous enterprise has been theoretical for decades, but Digitate is making it a tangible reality. Rajiv Nayan Vice President and General Manager reveals how their Ignio platform is transforming how global organizations operate by eliminating the 80-90% of repetitive tasks that consume valuable human potential.
What makes Digitate's approach revolutionary is their unified layer of intelligence that shifts enterprise operations from reactive to proactive. The Ignio platform combines three powerful capabilities: unified observability that understands horizontal data flows across systems, AI-driven insights that predict problems weeks before they occur, and closed-loop automation that resolves issues without human intervention. With 107 patents supporting these innovations, Digitate has created a solution that fundamentally reimagines how enterprise systems function.
The results speak for themselves. Companies like Tapestry (parent of Coach) have recovered millions in previously blocked orders, while other customers report 50% reductions in incidents requiring human attention. Measuring success across revenue assurance, IT toil reduction, tool consolidation, and accelerated SRE adoption, Digitate demonstrates ROI within nine months for most customers. Their partnerships with global players like TCS, Azure, AWS, and Rocket Software extend their reach across industries.
Looking toward the future, Digitate envisions the "ticketless enterprise" – an operational environment where problems are prevented or resolved automatically before they generate support tickets. This represents a fundamental shift in how IT operations are measured and managed. With AI adoption accelerating faster than previously projected, Digitate is positioned at the forefront of a transformation that's happening years ahead of schedule.
Ready to free your team from repetitive tasks and build an autonomous enterprise? Discover how Ignio can transform your operations and redirect your workforce toward innovation rather than maintenance.
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Hey everyone, Fascinating topic today with a really interesting guest and company on the rise of the autonomous enterprise and the evolution of AI and automation. Rajiv, how are you?
Speaker 2:Great.
Speaker 1:How are?
Speaker 2:you, everyone.
Speaker 1:I'm doing great. Thanks so much for joining, really intrigued for this chat. For this chat, maybe you could introduce yourself and for those who aren't familiar, who is Digitate and talk about your journey since your inception in the 2000s.
Speaker 2:Sure, so you know pleasure to be with you and Digitate.
Speaker 2:We started almost 10 years ago, in 2015, with a clear vision to go on the journey of autonomous enterprise and it was rooted in the whole philosophy that if you look at the enterprise today, globally the large enterprise almost 80 to 90% of operational work is repetitive tasks. It takes away a lot of human ingenuity out of the equation, where people are just doing that work day in, day out and if we can build software and the technology was available those days when we started in 2015, to free those human minds to go and do some higher work, and that's the journey which continues. We have been privileged to be part of this exercise. There's a lot of customers which we are working with today and we can talk about in detail during the course of this discussion working with today and we can talk about in detail during the course of this discussion.
Speaker 1:Yeah, talk about your flagship platform and how it's maybe differentiated. Given the vast number of choices enterprises have for automation and RPA and do-it-yourself these days in the marketplace, what's the driver for your platform or your product?
Speaker 2:Sure. So look, you know what we're trying to do is completely differentiated. If you look back in the industry for the last 30 years, pretty much automation has been there, monitoring has been there. If you take a typical enterprise, even today also, they might have 10 to 12 different monitoring tools. They might be doing some script-based automation or some kind of automation which they've been doing for the last 20, 30 years.
Speaker 2:I think where the challenge has been for the industry that, first of all, it's not sustainable and scalable. Secondly, it doesn't give you a proactive insight. It's always reactive, it's siloed, there's a lot of toil and at the end, it impacts the overall business outcome, what the business wants to achieve out of those systems and processes which runs within any large enterprise, or small enterprise, for that matter. Now, from that perspective, when we looked at and when we started building this platform, which is the flagship Igneo, which is branded as Igneo, we look from the lens of how we build something as a single layer of intelligence and autonomous operations where all these tasks can be made proactive, predictive, rather than being reactive. Of course, there will be always some level of reactive situation which will arise in enterprise. But even if the reactive situation arises. How can you recover much faster from those situations when typically a siloed human team goes and tries to resolve those situations? And that's where we have built a differentiated platform which has three key, I would say, elements of it. One is what we call the unified objectivity, and that's a little bit different than what you see in the industry today. From our perspective, unified objectivity is all about understanding the horizontal data flow within the enterprise across different systems and processes and practically understand what can potentially go wrong and trying to recover from those situations before the problem has taken place. And then the whole vertical stack, full stack observability what the industry is talking today. We have combined these two within the platform, along with adaptive nature to understand the context of the enterprise to behave in a certain situations. For example, a peak season for a retailer, the behavior will be very different for those systems than what it is non-peak season. So that's one big part of the enterprise within the platform how we can help the enterprise to understand what's going on proactively.
Speaker 2:The second big piece is we ingest a lot of data and do machine learning and AI reasoning to understand what's going on in the enterprise, to eliminate a lot of problems. For example, a situation could be that this particular process is our system in last month has created 32 situations which has taken a toll on the system and a revenue process has been stopped. And that's where Igneo can understand those and create a problem ticket for the teams to understand that. How can we avoid and eliminate the situation from happening the following month? Or, for example, a particular system the way it's performing today, in six weeks from now, it will start degrading. These are early warning signs which the system can tell you upfront to the team, so that they can go and take action to eliminate the problem from happening.
Speaker 2:This big piece is what we call AI-driven insight. It also elements to the cloud today, because there's a lot of cloud issues which is happening today, and the conjunction to the cloud today, because there's a lot of cloud usage which is happening today, and you know the consumption of the cloud is a big issue for any enterprise, though the cloud has given a lot of agility to the enterprise. But the cost consumption is a big issue and the product can tell you what is the optimal usage of your environment so that your cost can come down. And the third part is the closed loop automation no-transcript those problems. It will triage those problems and close the loop, what we call close the system. So it's a zero human touch situation where, if something has taken place, igneo can end to end solve the problem, and that's what we call the closed loop automation.
Speaker 2:All these three the unified observability, the AI driven insight and closed loop automation big capabilities I would say we have deployed across cloud application infrastructure, bad jobs, sap systems and edge devices, and that's pretty much covers your 80 to 90% of operations in any enterprise. So that's where we have tried to build this whole intelligence and autonomous action within a single platform. And that is what the customers see as a very differentiated view how they're using it today.
Speaker 1:Brilliant. And so how do you measure success on a new approach like this? What are the key KPIs or measurements to show the benefits or value when deploying Igneo? What sort of ROI do you pitch to your customers?
Speaker 2:Sure. So typically it's in four dimensions. One dimension which we typically look at is typically the revenue impact or revenue assurance, where how much we have been able to recover from a situation where a potential revenue was getting lost or impacted in an environment where Igneo has been able to help. So I'll take an example Tapestry, which is a brand which you know, sells coach and other and they have stores also in online e-commerce. Typically their problem was that orders would come on an e-commerce site. It will go to the order management system, it will go for some shipping. In the process, something will fail. We have deployed the horizontal objectivity which I talked about from the unified objectivity perspective and that is helping them to have an uplift of $1.8 million worth of orders because that wasa blockage in their whole process flow. Also another example to the same organization we have been able to help them to put the promotion and pricing to almost more than 1,000 stores in time, because sometimes in the past the data was not available real-time into the store systems on the POS systems. Again, that's a big impact on the Indians because they are high-end brand retailers. Those informations are critical for them to serve their customers and the brand protection has to be protected at any cost. These are just example on the revenue assurance side and customer experience side.
Speaker 2:The other dimension is the typical IT toy. For example, let's say you have a 100 incidents being reported today in last one month. Typically we have seen with Ignew I can go and reduce 50% of those instance If only 50% will go to HumanCube. We can deploy our because this comes as pre-built a lot of technology within the platform. Typically in six to eight months 50% of those tickets can be onboarded to Ignew. Only 50% will go to Human. That's a lot of free time and free ability of resources for the enterprise to go and do something new and higher stuff. The other could be noise reduction at the command center. You know we could typically reduce noise up to 100 percent because those are the, you know, needle in the haystack problem which Igneo, through AI reasoning at the highest level of model based reasoning, igneo can find and fix those problems.
Speaker 2:The third dimension which we are seeing now lately in last I would say last two years, is we have been able to replace some of the traditional monitoring tools with our unified regulatory platforms at the infrastructure layer or APM layer, and that has become an interesting part of the discussion with customers. We have replaced ITOMs, we have replaced typical monitoring tools in the infrastructure and APM layer, because that helps customer to synergize their architecturally, simplify their environment and also it makes a commercial sense for them. And the fourth dimension is industry. We are going through the process of if you have heard the word SRE, service reliability engineering. There are certain elements and facets of that behavior and process within the enterprise. If you deploy our product, like Igneo, you can fast track and leapfrog into the journey much faster because there are elements within the platform which can help you to achieve some of those objectives much faster. So typically we measure across these four dimensions and it also depends on how customers want to take on this journey.
Speaker 2:Some customers start purely on the IT operations space of did I remove some hours? Did I remove some tickets? That could happen. Tapestry started in a complete revenue assurance side of the world where they had a problem. They deployed unified ability. In fact they had a BrightTalk seminar yesterday, a webinar yesterday, the customer from Terrestri. They talked about Agnew and how it has helped them. Very interesting data which came from that discussion.
Speaker 1:Brilliant, so clear opportunity benefits. How do you overcome a lot of the adoption challenges you see with especially large organizations lots of technical debt and lots of silos and some data challenges. How do you address those for the global enterprises?
Speaker 2:It's an interesting question, ivan, because I don't think there is an easy answer to this. Because of the nature of how businesses are structured and the functions within the business are structured just within the IT itself, how different IT teams are structured and platform like this, you have to create a centralized view of intelligence and a central, autonomous platform which can give you a sustainable automation automation for future. I think we have learned through, you know, deploying across 200 plus customers today, large because we only deal with enterprise grade customers. I think the learning has been, first of all, it's not more about a technological debt, which is, I would say, a minuscule part of the problem, because you can find some solution to that. I think the bigger problem is the mindset change and the culture change, because the whole team, typically we have come across, is siloed. They have their own logical view. So first of all, you have to get an executive sponsor at the right level who can own and has a vision to go in this journey, and that's very critical. Of course, budget is one part, because every budget is through a business case that is given. That's a table stake. But when you go and deploy, we have created a Igneo way methodology to kind of take through the journey of customer and we do that in a very agile format that every month you deploy a few things with a very clear outcome stated upfront as a business outcome and start measuring them in the process of deployment. And, as typical to any environment, there will be some naysayer, there will be a lot of people who will try to test this idea and the moment you start a few things early on in first couple of months, you start people start seeing the results and they start rooting for it.
Speaker 2:Now you know, one part which I'll always talk about is it's not easy as the way we are talking it's an intense exercise. It's a true transformation because a lot of time customers which have been using in a certain way and suddenly this software comes and it solves the problem in three minutes which they have always seen, that that problem was solved in two hours. It's hard to believe because it's something new. And then sometimes we have built also a lot of explainable AI features within the platform where people can see through what's happening, because that was also a black box early on. That has also helped the customer to adopt faster.
Speaker 2:I think more and more, I would say as an industry, when customers are seeing the behavior of Gen AI, what is in the platform, how the industry is evolving and how fast people are getting accustomed to the ecosystem of this whole Gen AI and AI concepts.
Speaker 2:Now I think it's becoming much easier. Now People are receptive to the idea and with the advent of Gen AI now in the last few months I would say the AI application has become a little bit more mainstream and, for example, we have done a Forrester study with a couple of our customers and it's very clear, evident from that data production data that we have 185% ROI within nine months payback period. Now some of those elements help those customers at the executive level to go through and sell this idea to their teams, because at the end you can't change the culture overnight. You have to slowly, slowly glue it together and that's how you cross that through the hump. So it's an interesting journey. We have a lot of knowledge how to take it through the large enterprise. It's complex, we have a few scars also, but certainly it's a very fruitful journey and there are a lot of customers who are enjoying the fruits of what we have been able to deploy for them.
Speaker 1:Brilliant. Well, talk about your partnership ecosystem as well, with companies like Arrow Electronics really an amazing global blue chip player, and also TCS a very close collaboration with the tech IT giant TCS. What does that look like?
Speaker 2:So I know as true to any software business. We have a partner ecosystem. You know we partner with the hyperscalers where you know, our district SaaS platform is both. You know Azure and AWS are our partners. We have a lot of ISVs which helps in our journey to, you know, go and co-sell and sometimes, you know, place the software in the customer environment. We have TCS is one of our big SI as an implementation partner also. A lot of business we do along with TCS because we are part of that ecosystem and it always helps to get that contextual knowledge from TCS.
Speaker 2:So overall we have almost 50 different partnerships, a different layer within the ecosystem. We have almost 50 different partnerships, a different layer within the ecosystem. We have some technology partnership with something like ITSM tool in the market. In fact, very recently as of two weeks ago, I was in Florida and one of the customers has asked us to replace a very known platform in the industry completely with Hikni. That's a challenge they've given to us. Another request which I'm seeing in the industry and I'm just talking to you, you know, as I see it, in the last two weeks another customer in Canada has come up and asked for the same question that can you just replace completely one of the leading platforms they're using for the last almost 10 years now. So a lot of those partner ecosystems helps us to play that.
Speaker 2:We are also OEM with Rocket Software, which has Zeek and Xena as a platform, primarily on the mainframe back job side of the business, and a lot of banks and other large institutions globally. We are OEM to them. In fact, that was noted by Gartner in one of the reports last, I think September 2024, on service orchestration and automation, and they have mentioned that how the state has helped Rocket Software to leaf-frog into their quadrant. So yes, we will always continue to explore and find the right partner in the market because it's a classical software business where you just cannot do everything yourself. You have to work with the ecosystem. It's a classical cooperation and competition, both, which happens, and we are Journey and we are always on lookout for the next right partner in the business.
Speaker 1:Brilliant. So a lot of eyes are focused on the RSA conference coming up I'll be there in a few weeks and security and trust, ethical use, transparency lots of issues there, including, of course, helping employees manage the security experience and manage all these new endpoints that are coming on stream. How do you think about your role in the security ecosystem?
Speaker 2:So you know I think there are two parts to it. One is you know the platform itself. Because we are in SaaS, there's a lot of scrutiny to the security itself because of the data privacy. We have done some, I would say, table stakes, for example, gdpr compliance for the European Union. You know we are compliant to those standards. You know SOC 2, Type 2 compliance. You know from that perspective the platform is compliant. We are GXP compliant for the pharma industry. We have deployed a lot of pharma industry customers where the platform is GXP compliant I would call that as a table state and we have built action firewalls within the platform itself to ensure that Ignio doesn't take any action which is not it's authorized to do, because at that it takes certain action the way human takes today an administrator of a enterprise would do, and we have to be very, very clear and prescriptive what Ignio does, so that we are built in, built in the platform, and a lot of reasoning and AI is placed behind the product. I didn't tell you there are 107 patents on this platform till date, so that's again a lot of innovation in that area.
Speaker 2:I think if you look from the lens of on the security side, we honestly, have not dealt a lot on the SIEM side of the world, on the security side of the world. There are a few use cases within the platform we have done. Having said that, we have built a complete compliance module within the platform. Today Any customer who has to understand, for example, because it kind of intertwined in some way a patching has not been done and that's why there is a security hole or a vulnerability is there in the environment and that's where somebody got access to the system. So a lot of compliance and hardening use cases are pre-built based on NIST standards. Clients and hardening use cases are pre-built based on NIST standards and that is helping customers to secure their environment and their parameters. And that's where Ignore is helping a lot. But classical, I would say, security management and areas. We do deploy a few of these cases, but I won't say we are actively. Actively, you know we have built something out there completely to that environment.
Speaker 1:That's good to know. So let's talk about your strategic priorities over the next year or two. Obviously, agentic AI is all the rage and discussion and you're sort of living that world almost today. But what's your direction and where are you headed?
Speaker 2:So what you're glad to know, ignew is agentic AI today, so Ignew can take actions, you know. So you would be glad to know Igneo is as NTKI today, so Igneo can take actions. You know. If you just do you know a question to Grok or chat GPT and say, is Igneo as NTKI, you will get a very interesting answer it is. And look, this has been being talked about in the last few months. We have been building this for the last 10 years and nobody was putting that word to it. So is it as NTIKI, as a platform which takes and understands and take certain actions based on the situation, based on its own understanding? I think the interesting part I was what we are going forward is that we are going into something called ticketless.
Speaker 2:If you look at the industry for the last 20, 30 years, ticket was a primary reason a customer would look to something and tell to their business or an SI which is serving the customers. Today, because of the outsourcing and different nature of that industry, they would say, look, I'm my SI to you. I have sold 100,000 tickets this month or this year. I have done so much work for you, pay me so much. If you look from a very abstract lens why ticket happens. It's a problem which is taking place somewhere. Somebody is reporting it. It's a record and report. If Igneo, like a platform, can understand proactively and resolve those situations, you don't need a ticket. Ticket becomes just an exception. So we are going very big into that area. On a ticketless enterprise, it's a journey. It's not that something you will get it done in a year or so, but certainly it's a big, big area where we are focused on because of the ability of the platform to proactively understand the environment, contextualize this problem, what's happening on, you know, and then go and take certain action to avoid those situations from happening in the first place. So certainly ticketless is a big ticket item.
Speaker 2:Of course, business as usual, you have to grow the rate of AI which is coming in today. I was reading something in the flight yesterday that in 2019-20, the expectation was that AI will become full-blown by 2036. There is an error rate in that projection by 69% and if that error rate is true, they're saying by 2026, ai will become full blown across different layers of the industry. If that is true, we are very well placed and we are deploying a lot more areas into that space.
Speaker 2:From the AI perspective and the larger piece of puzzle which I told you early on in this discussion is we are looking at a wide lens platform which can help the enterprise to become autonomous. I have not come across any software in the industry today to the level of sophistication from the AI perspective and to the wide lens which we are talking about from the operational lens of benefit, what it can give to a customer, because most of the softwares are designed purposefully for a very deep understanding and a deep area, a very small area to solve a problem. And we are looking at a very wide lens from the operational perspective. And that is giving us a leeway to work in that direction going forward in 25 and 26.
Speaker 1:Brilliant, well, very exciting. Congratulations on that, and you've been traveling everywhere. Any other travel plans coming up? Any other events? Maybe you'll get a breather for a few weeks.
Speaker 2:Yes, there is for sure, and travel is. I think it comes with the role which I'm playing for the business and I'm passionate, if you can imagine. I'm passionate about this business because in some way, we are changing the world in a small way. I think. Yes, I will be in New York in the next few weeks and I will be in New York in the next few weeks and I will be in India. I travel a fair amount of time to India and European countries because of the customer base and I might be in Australia Sydney in the next few months. So these are a few of the locations, I think Helsinki, stockholm, india, a few cities, new York and maybe Calgary. So a few things are lined up in the next few months.
Speaker 1:All right, Well, get your passport. Congratulations on all the success you and the team are doing and look forward to keeping in touch and watching the journey.
Speaker 2:Thank you, man. Thank you very much for your time.
Speaker 1:Thank you and thanks everyone for listening, watching and sharing.