In this engaging session at the Kong API Summit 2025, Paul Nashawaty of theCUBE Research meets with Prashant Gaonkar of Cognizant. The discussion centers on Cognizant's strategic initiatives and their partnership with Kong, highlighting advancements in API management and AI-led transformations.
Prashant Gaonkar brings a wealth of experience in enterprise integration and process orchestration, leading Cognizant's efforts to drive AI-driven transformations across industries. With insights from their collaboration with Kong, Gaonkar explains how businesses can enhance their capacity to navigate modernization. This video details the strengths of Cognizant's approach in integrating various technological ecosystems to optimize operations.
The discussion provides valuable insights on how businesses can leverage existing systems amidst AI advancements, ensuring compliance across sectors, especially in regulatory-heavy industries such as finance and aerospace. Gaonkar underscores significant opportunities in AI and process orchestration, emphasizing the importance of effective integration strategies to unify different systems seamlessly according to industry needs and maturity levels.
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Prashant Gaonkar, Cognizant
In this engaging session at the Kong API Summit 2025, Paul Nashawaty of theCUBE Research meets with Prashant Gaonkar of Cognizant. The discussion centers on Cognizant's strategic initiatives and their partnership with Kong, highlighting advancements in API management and AI-led transformations.
Prashant Gaonkar brings a wealth of experience in enterprise integration and process orchestration, leading Cognizant's efforts to drive AI-driven transformations across industries. With insights from their collaboration with Kong, Gaonkar explains how businesses can enhance their capacity to navigate modernization. This video details the strengths of Cognizant's approach in integrating various technological ecosystems to optimize operations.
The discussion provides valuable insights on how businesses can leverage existing systems amidst AI advancements, ensuring compliance across sectors, especially in regulatory-heavy industries such as finance and aerospace. Gaonkar underscores significant opportunities in AI and process orchestration, emphasizing the importance of effective integration strategies to unify different systems seamlessly according to industry needs and maturity levels.
At Kong API Summit 2025, theCUBE Research’s Paul Nashawaty sits down with Prashant Gaonkar, who leads Cognizant’s global practice for enterprise orchestration, integration and supply chain. Gaonkar breaks down why process orchestration is the “glue” across 400–500 systems inside large enterprises – and how an integration “string engine” underpins end-to-end workflows for customer and internal processes. He reacts to Kong’s latest moves – expanding governance and observability with MCP and embracing hybrid AI, on-prem and multi-cloud neutrality – and explains ...Read more
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What are some recent developments regarding the Kong Konnect Foundation and its support for customer AI transformation?add
What significant developments occurred between Kong and Cognizant regarding their approach to AI over the past few years?add
>> Welcome back to Kong API Summit 2025. My name is Paul Nashawaty and I am the practice lead and principal analyst at theCUBE Research for the app dev practice, and I'm joined today by Prashant. How you doing, Prashant?
Prashant Gaonkar
>> Very good. Thank you you for having me here.
Paul Nashawaty
>> Yeah, great to have you here live on the show floor. It's pretty exciting, the keynotes. The sessions have been great. Why don't you tell the audience a little bit about yourself and a little bit about Cognizant?
Prashant Gaonkar
>> Excellent. Excellent. So, first of all, thank you for having me.
Paul Nashawaty
>> Of course.
Prashant Gaonkar
>> A great day. At Cognizant, I manage our enterprise orchestration, enterprise integration and supply chain practice globally. And Cognizant has been in this field for a while, helping our customers on transformation and most recently, AI-led transformation, which is the topic of the day nowadays.
Paul Nashawaty
>> Yeah. No, it's exciting times. I mean, it really is. My practice, as I said, I'm in app dev and app monetization. I deal with past, present, and future. So, it's right up your alley, it's what you do. But let's start with the event that's going on here at Kong API Summit. You're a partner of the year, which is pretty exciting, right? Cognizant's building that trust around Kong and Kong Konnect and Kong Gateway. Anything to share around that?
Prashant Gaonkar
>> Yeah, I was very pleasantly surprised when Auggie and Marcos spoke about how they are leveraging their Kong Konnect Foundation and take it to the next level to support our customer's AI transformation. For example, they are bringing up this MCP control governance and observability to the full board, which has been a pain point for many architecture groups within our customers to decide about how to go about it. And second, very pleasant surprise is Kong is becoming very agnostic. They're saying, "Bring your hybrid AI workloads. Bring your on-prem workloads. Bring your own cloud workloads. We'll manage it all." So, those are very good things for the customers nowadays who are struggling with the multitude of options across the board.
Paul Nashawaty
>> Yeah, absolutely. So, I agree with you. I think that when we look at organizations environments, they're not typically built in one aspect, right? They're built across the ecosystem. All right. Let's talk a little bit about you though. Let's talk about you. You're in charge of process orchestration in your practice. So, what does that mean?
Prashant Gaonkar
>> So, if you look at any large enterprise and when they buy platforms or products that have their own systems, any organization of significant size has at least 400 to 500 different systems. Maybe 30%, 40% of that is SaaS and some of them are homegrown. Now, when you look at those platforms and when you want to serve your end customer, you have to bring some of those system functions and aspects together, so process orchestration does that across the enterprise. Now, underlying that, what I call a string engine, which is enterprise integration, which takes care of the systems, services and data to integrate them with the services. Then, process orchestration sits on top of it to manage and navigate those process and workflows across the board. It can be end customer processes or it can be internal human capital management processes or anything like that.
Paul Nashawaty
>> So, you're the glue that makes it stick together?
Prashant Gaonkar
>> Yeah.
Paul Nashawaty
>> That's awesome. That's awesome. And I like that because when I think of modernization, I think the theme that I hear, and that's been pretty aware at the show, is bridging the gap between heritage environments to new environments. And organizations, they need to run, but they also want to modernize. What are your thoughts around that?
Prashant Gaonkar
>> See, the ecosystem is such that customers have migrated to cloud in the last 10 years and they have done significant investments in that as well as in SaaS. So, with this new AI wave, I don't think they have an opportunity to, again, re-spend the capital to rewire, re-engineer everything. They have to leverage the assets they have, whether it is system functionality, the SaaS platforms, or the data, or even the underlying governance structures. They have to leverage that to get the benefit of the AI. So, to do that, I think Kong Gateways and those things will help because you're literally exploring the options of leveraging those existing assets and then bringing them together, gluing them together to give the end result, which can be business acceleration or cost reduction or productivity gain.
Paul Nashawaty
>> Yeah, I like the way you put that, because in my mind, everything becomes an LLM or an SLM. Organizations are not going to throw out their data lakes and their data pools that they've been using. Their big data solutions that they've had in the past now become those data sources for these new AI initiatives. So, whether you're using MCP or you're using your agents or whatever you're building, you need some way to harmonize and the connectivity about that. Well, all right. So, let's talk a little bit about you work with enterprises across multiple industries, whether it's financial services and aerospace, those are not easy industries to work in. What kind of transformation challenges are you helping these organizations overcome?
Prashant Gaonkar
>> Yeah. So, through our leadership, Cognizant has redefined the strategy of helping customers on the three vectors. The first vector is automation and acceleration, gaining the low-end productivity, which then feeds into the next level of AI journey, which is hyper-automation, hyper-acceleration. And if you really see that is when most of the initiatives begin to take shape when it comes to foundational work, whether it's deploying Kong or deploying Cognizant's own neuro-platform and those things. The last one is taking customer to the completely agentic world, which requires, in fact, organizational change on the customer side. So, the transformation that we see in any customer can fall into any of these three vectors and different customers are at different maturity levels in that path itself. And because of that, Cognizant tries to meet them at that point, rather than describing, "Hey, this is how you do it," because everybody's not mature, not everybody's starting today. So, we have to meet them where they are.
Paul Nashawaty
>> Oh, I totally agree with you. When I built out my research that I just put out, I built a five-stage maturity model, and I was talking exactly about that. Customers can enter in at any one of those stages, but even on top of that, applications within customer environments can enter in any one of those stages. So, it's very much along that. But when we look at financial services and aerospace, is there anything that's unique that ties... I know there's requirements in governance-
Prashant Gaonkar
>> So, Paul, I will take I think financial solutions as a domain, aerospace as a domain, and in each of those there are regulatory burdens as well. When I say a burden, not in the negative sense, but in the sense of doing more work.
Paul Nashawaty
>> Compliance, right?
Prashant Gaonkar
>> Compliance. So, especially when it comes to AI, financial industry has to think a lot. I will give you a classic example, Paul, where in one of the cases the project ended with a good use case of deploying an agent inside the underwriting system, but the quality team rejected that output because the product could not explain why the decision is made. Now, for example, you're a property and casualty customer. If the company denied your claim, they have to be able to explain why they denied you. In this project, that was not explained. So, the traceability, the explainability, the audit trails, all those things, the financial industry and even aerospace need to incorporate. So, it's not just deploying a technical project, leveraging LLMs and RAG models and then building your own data fabric to deliver end solution. There are a lot of other pieces, especially in these industries, which they have to take care. And then, on top of it, especially in the financial industry, there is a huge monetization effort going on and APIs have to monetize. That's what Marco spoke about today.
Paul Nashawaty
>> Absolutely. Yeah. Yeah.
Prashant Gaonkar
>> So, that is an all new angle to this capturing the growth side of it.
Paul Nashawaty
>> Yeah. No, that makes a lot of sense. I think that there's also a huge impact, and you alluded to this already, is the huge impact of adding AI into it. In my mind, we're not quite ready to have a complete autonomous, completely automated. We still need a little bit of that human in the loop and to make sure that things are going right, because at the end of the day, organizations are accountable for their business actions. And I was talking to one organization, they said, "Well, it wasn't our fault. The AI put it out." It's like, but you did it and it's your business. So, it's the same thing here. When you have compliance governance and regulations, you need to have the ability to have a human in the loop and make sure that's watching. But I want to come back to the monetization comment. That is a big factor. That's one of the big announcements here, right?
Prashant Gaonkar
>> Uh-huh. It is.
Paul Nashawaty
>> We're talking about monetization of the API chargeback models, understanding where the amount of flow is happening. Can you touch a little bit more on that?
Prashant Gaonkar
>> Yeah. Yeah. So, again, maturity of the monetization will take some time because the parties which are involved in those transactions are still figuring out. You might've seen one of the big banks recently announcing that will cut off all the APIs because only one small company was taking 80% of the transaction workload and pulling all the information and pinging every so often, and they had to cut it off because it was hurting another 20% of the customers who are really in need of those APIs to respond to credit answers or availability of funds or transactions. So, this is a path that everybody wants to take, but a business model for monetization is still evolving and it'll come to fore once the other infrastructure and foundations are set in place. And on top of it, just think about it, an agent, you can take me out of the equation if you don't like me or . Similar thing needs to happen with the agent. So, there has to be a so-called kill switch. So, to your point about human in the loop autonomous, if that agent is switched off, which is probably handling tens of thousand transactions, who's going to do that? There is no other second agent. There is no other Paul or Prashant. So, I think all those things will matter because monetization will also come with certain penalties, certain performance guarantees, certain KPIs.
Paul Nashawaty
>> Yeah. No, I think it makes sense. And we had some of those larger banks on earlier today on the show here, so for the audience, look back at those events as well. But I think there's a lot there to unpack when you look at compliance, human in the loop and automation. We touched a little bit about hybrid environments. We touched a little bit about on-prem and working with the cloud, and I want to talk a little bit about some of the announcements. We talked about Kong Konnect and Kong Gateway across hybrid environments. What does that mean from a technology stack and when it comes to scaling securely, but also how do you prepare for the agentic AI era with regards to this whole movement, right?
Prashant Gaonkar
>> Yeah, it is, I would say a little bit counterintuitive. Nowadays, many technologies like Kong offer what you want to do, but most of the mistakes will happen in how you deploy them. You talked about the agents across the different . So, multi-agent orchestration can be handled through Kong platform, but the question is how you implement it? If you, as a human, missed it and then if that leads into some other aspects of business loss or transaction issues, how do you handle it? So, it's not just the technology being ready to be used, it's about how you are consuming it as a human being to deploy within your organization.
Paul Nashawaty
>> Yeah. I mean we could talk all day on this, but that also opens up the skill gap issues, that opens up the citizen developer part and everything that goes along with this. But I think that aligns to where I want to go next, which is what has been the key successes between the partnership with Kong and Cognizant?
Prashant Gaonkar
>> Yeah, so one biggest thing that happened to Kong and Cognizant about two, three years back is our CEO came in, Neil. He was talking AI. He was one of the early champions of AI and we all caught onto it in the company. At the same time, Kong also changed their mindset, even though they're much smaller, nimble organization on the AI journey. So, we started to discuss about how to go to market. Kong API Gateway is there and then Kong Konnect. And we saw that the path is converging in terms of how we both want to do things. So, that's where I think the idea of the help to customer came into similar path. And most importantly, it's a trust and transparency we both have with each other. And that's where the partnership is, so I think, ready to take onto the next level.
Paul Nashawaty
>> Very cool. So, Prashant, we're sitting here in 2026, a year from now at Kong's API Summit a year from now, we're doing the same conversation, we're talking about this. Looking ahead, how do you see Cognizant in the Kong partnership really expanding or what's the need for enterprises to take that next wave of digital and AI transformation?
Prashant Gaonkar
>> I was thinking you're going to ask me to have a crystal ball to talk about AI. Glad that you did not do it. So, you threw a very simple question.
Paul Nashawaty
>> I did.
Prashant Gaonkar
>> Because we are investing both heavily in solutions and platforms and products, both of us. So, I would say if we can help some customers, to your point about automation change and getting through the complexities of AI transformation, I think we would succeed. My way of seeing the success is fast-forward next Kong Summit, if we both are on stage, Auggie and I, and talk about couple of customer case studies, this is our take on that, that will be a success.
Paul Nashawaty
>> That'll be great. Well, Prashant, thank you for your time and your insights.
Prashant Gaonkar
>> Thank you.
Paul Nashawaty
>> This has been really great. I really appreciate you being on theCUBE with us today. It's really been awesome and this event's been really great.
Prashant Gaonkar
>> Thank you, Paul.
Paul Nashawaty
>> Thank you.
Prashant Gaonkar
>> Thank you very much.
Paul Nashawaty
>> And thank you to the audience. My name is Paul Nashawaty and I'm coming to you live from the show floor at Kong API Summit at 2025 on theCUBE, your leading source of tech news.
Paul Nashawaty