theCUBE + NYSE Wired: Marketing Leaders | Jyoti Bansal, Harness & Sanjay Nagaraj, Traceable

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Jyoti Bansal

Co-Founder & CEO

Harness

Sanjay Nagaraj

Co-Founder & CTO

Traceable AI

play_circle_outline Maximizing Efficiency: The Convergence of DevOps and Application Security with Harness and Traceable AI

play_circle_outline Unlocking Competitive Advantage: Enterprise AI Integration Influencing Merger Decision-Making in Data-Driven Companies

play_circle_outline Customer impact and benefits

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Jyoti Bansal, Harness & Sanjay Nagaraj, Traceable

Jyoti Bansal

Co-Founder & CEO Harness

Sanjay Nagaraj

Co-Founder & CTO Traceable AI

Jyoti Bansal, CEO of Harness and Traceable AI, joins theCUBE to discuss the merger of the two companies. The interview, conducted by theCUBE Research analysts, covers the motivations behind the merger and Jyoti’s vision for a unified DevSecOps platform. Jyoti and Traceable CTO Sanjay Nagaraj explore how the convergence of DevOps and application security aims to address the velocity and security demands in software delivery.

The discussion underscores significant insights such as the imperative of integrating software development and application securit... Read more

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technology and software development for many years now. Can you tell us about how Harness and Traceable are leading the way in modern DevOps and application security, and how they are converging to create a unified platform? add

What is the reason behind the decision to merge two companies and how does AI play a role in solving problems related to DevOps, deployments, builds, FinOps, and application security? add

What are customers excited about in terms of security integration in the software delivery process? add

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Jyoti Bansal, Harness & Sanjay Nagaraj, Traceable

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>> Hello, welcome back to theCUBE. I'm John Furrier, your host here in the Palo Alto Studios. We're going to break into our CUBE NYSE Wired coverage of the CMO Leaders Summit to bring some breaking news at Harness and Traceable AI are merging together. Jyoti is the CEO of both companies, and we have the CTO, Sanjay here from Traceable. First of all, congratulations Jyoti, on bringing everything back together. Unusual ventures funded both of you guys, and again, great kind of mission. So let's get into the news real quick. Why the transaction? What's the purpose behind the deal? Give us a quick hard news update.

>> Sure. So Harness is the leader in modern DevOps. How do you bring software delivery in a fully automated lifecycle from builds and deployments and how the software is released and Traceable has very rapidly become leader in modern application security. Starting at the core of it is API security securing your APIs. So what we realized over years is that it's starting to converge very, very rapidly the two markets of how developers want to ship software and how the software need to be secure. So the velocity and security has to come hand in hand together for it. The two companies are growing really well. Both companies have been on a very successful path to become a platform, and we think it's a good time to bring DevOps and application security together and to create this kind of a unified DevSecOps platform for the market.

>> Jyoti you've been a student of and actually a practitioner entrepreneur in the enterprise. It's well documented, your successes, but also you have an opinion on how to go to market in the enterprise. Enterprise AI is surging in demand, yet everything seems to be stuck on POC purgatory, right? Because AI software is changing and the platform engineering work is ramping up super fast. It sounds like this is kind of in that vector of kind of put aside the fashion, let's just get the steady state platform DevSecOps so we can get the AppSec reviews and clear the resilience hurdles needed for the enterprise. Is that something going on here? Is that part of this? Can you share your thoughts?

>> Definitely. AI is a big driver for why we decided to merge the two companies, both companies. When we look at the future of how we solve these problems on DevOps, on how do you do deployments, how do you do builds, how do you do your FinOps, how do you do application security? The interface and how people deal with it is now AI like AI. And we have been at the forefront of it. So we have some of the best agents for DevOps, for FinOps, for application security, for release agents. But what we realized was the data is in two different silos. In Harness, we have some of the best data on how people are building their apps, how people are designing their apps. In Traceable, we have some of the best data on how people are consuming these through the APIs. And we think now if they bring the two data pieces of data together, we can build some of the next level of agentic AI possible on that. So that's definitely one dimension. Of course, the second dimension is the enterprise is building AI apps on their own. As you're building AI apps for your businesses, for your consumers, a big challenge is how do you secure them? How do you make sure the data governance is right? How do you make sure the toil around building those apps, deploying them, all of that is taken care of. And the tool chain that Harness and Recibel now can bring together is to speed up the adoption of these AI apps. At the practical level

>> Sanjay, I want to get your thoughts on this because I talked to a lot of enterprise customers, CISOs, CSOs, CIOs, pretty much technical decision makers and recommenders. They all say the same thing when I say, "How do you guys view frontier models?" And they all say, "It's just another application." And I'm like, "Oh, okay." So you're starting to see them look at the path to production. How does this fit into that? Because they want to get the apps on board fast. You've either got cost reductions, okay, check productivity gains check, that increases potentially revenue, but you have all that sandboxing going on and they kind of get stuck there and the enterprise wants to get these into production, these workloads and get these apps in there. What are you seeing in that piece of it? How does this play into that?

>> Yeah, that's an excellent question. So if you think about AI that is getting used to develop these applications, you don't have to always think about velocity and compromise and security. How do you think about them together? Because if AI is moving everything at a greater speed to make sure that the businesses can actually act on the customer requests and everything else in a much quicker way where software gets deployed a lot more quicker, securing those also should be a priority. Not just the AI technologies, but remember that everyone is using from a development perspective today, AI to write the code as well, right? So how do you actually secure that through the life cycle but also secure that at runtime and production is where a DevSecOps platform . And that's what we are bringing it to the market together.

>> What was the motivation, guys, on this? Were you're sitting around saying, Hey, we should put this together. What was the catalyst? What drove the change?

>> It's an interesting thing, an interesting situation. As in I'm CEO of both companies. I started both companies and there's my co-founder in Traceable. And people always ask me, why did you start them as two companies if you're going to merge them together now? And the reason we started as two companies was the developer and engineering personas and the jobs that they want to do has been a bit siloed from the security personas and the jobs that the security teams are trying to do. But what we've started to see over the last, I would say, especially in the last year or two, a much more convergence of that, especially because the speed of engineering is so high, speed of development is getting so high, the security teams cannot keep up with it without coming together. And so we started to see more and more of that. The customers for Harness, which are mostly using Harness for engineering and DevOps will say, "Hey, can we talk about Traceable? Can we bring application security more deeper and closer into it?" Customers of Traceable will ask the same thing, "Can we integrate more deeply with the CIACD, more deeply with our DevOps, practices and bring engineering and security together?" And as we started hearing more and more of that, we realized it's time to bring them together and we can bring this offering to both the security and engineering teams in an integrated fashion.

>> Go ahead Sanjay. You have something?

>> Yeah. So one thing I'll add to what Jyoti is saying is that in most of these customers, if you look at two separate products, Harness knows everything about software delivery. That means that they know exactly how software is getting built. So they have all of the development data. Traceable has all of the data about how these applications are getting used in production through the life cycle as well as in production. So it's like two great companies have this data, and what we wanted to do was bring that together so that we can serve the customers with both of the data, with the AI, melding the data together, and AI, as you know, is as good as the data. And that's where we felt that it's a powerful combination to come together.

>> I love the better together story. It makes total sense. I want to get you guys thoughts on security because you're seeing security, heavy data. The common thread here is data. How is data being leveraged? Obviously there's some great advantages on the software side. Data engineering or knowledge engineer, whatever word you want to call it, data is key to the agentic builders out there. These builders are coming, the apps will build services in software. How do you guys see that? Is that part of the intersection? I mean security is kind of a tell sign anyway. What's going on with data? It's got velocity, more data. Is there a thread there?

>> Yeah, definitely. If you look at it, there is no doubt that agentic AI and just AI-based solutions are going to the norm for everything. And the underlying piece is data. The challenge of data is data is what the bad guys are after. They want to steal the data, they want to manipulate the data they want to... So all kind of stuff that is happening, you have to protect it. You have to protect your data. We also look at what is the interface to come into these modern applications is really APIs. If you look at it in let's say the DeepSeq distillation conversations or allegations, they're all about that maybe they use the OpenAI APIs in a way they should not have used more than they use it and distilled the models to train that beyond what they were supposed to do. So APIs have become core of all of this, how the applications interact with each other, how you're accessing the data, how you're accessing the models. And so where we look at in how it all comes together, if you're building AI applications, it'll be all API driven applications. The data will be behind APIs, addressable. We are the leader in API security, protecting the APIs, understanding the usage of APIs, harness. We are leader in building and deploying apps and modern applications. So it's kind of the synergy is very strong on if you're building all these apps, you got to protect the APIs are the windows and the doors and these APIs and in these apps, and that's the only way you secure all this.

>> APIs are a critical infrastructure. Obviously 80 plus percent of the web is API based. Everyone knows that. But now with AI, as you mentioned, some of the distillation conversations, what's behind the API? Is it a black box? What's going on? How's the usage? So I have to ask, what's the customer impact? People watching might want to know, "Okay, better together. What's in it for me? I'm the customer."

>> Yeah. So I think if you think about it from a customer perspective, it's important to understand that on the development side of it, the developer, when they wrote the piece of code, they had an intent behind what that code was written. Which Harness has a complete understanding as they look through the STLC, right? Then when it actually runs in production, that is when actually the attackers are actually seeing what that data is supposed to be, what that API is supposed to do. That means that if you have a common understanding of the code, what it was written to actually what was deployed and the way it was running, then actually you can protect them a lot better. You can be compliant a lot better through the entire life cycle without compromising the velocity of software delivery itself. So yeah, it's a win-win for our customers

>> And our customers are very excited on both sides. Harness customers are very excited that security could be even more deeply embedded into the software delivery process. There's not an afterthought. It's just more get closer and closer to the development process, deployment process. And that's a trend that's been happening with over the few years. But we become the strongest platform to deliver this in this kind of a better together way. Traceable customers, they want to make sure, like the API security and securing the apps, the CISO buyers, they want to make sure the developers are operating in a more secure way. They are using secure development practices. So it's a good convergence and with customers are very excited about. So we only gotten really positive feedback today after this announcement.

>> Yeah, it makes a lot of sense. And the developer tsunami is coming. You start to see open source, thrive, the deep seek style innovations are here. Entrepreneurship's changing. Jyoti, your thoughts. You guys have both entrepreneurs, you've been there, done that. You've seen the movie before. Now we're in the modern era, born in the cloud, generate a lot of new brands. Born in AI is a whole nother thing happening now. Born in AI means you're dealing with all the AI benefits. What's your take on that entrepreneurial opportunities from this new era?

>> AI does open a new set of entrepreneurial opportunity every time we have this massive shift. Mobile was one, and before that, internet was one and then cloud, and now you have AI. These are massive technology shifts and that creates a lot of opportunity for innovation, a lot of opportunity for disruption. That means a lot of opportunity for entrepreneurship. What is different this time is the velocity of it. It's like internet took 8, 10 years to be mainstream and you had a bit lesser than that and Cloud took quite a long time. AI is just rapid. The adoption is rapid. The impact is rapid. So you see the companies, the next set of entrepreneurship, the next set of companies that are built to leverage the AI shift would grow fast. You see the numbers. We are very excited for B, the infrastructure foundation for a lot of these AI applications, both from software engineering, DevOps, software delivery, and also from the security side of things. And we are seeing massive success in our business. We are projecting our business, the combined business to be north of $250 million of revenue, which is a pretty sizable business for us now. And it's still growing more than 50% year over year. So we will be in the very small number of companies. That size is growing at that kind of scale. And a lot of it is the momentum that's coming from AI and how people are building these AI driven apps and the amount of software engineering that's going behind it and the tool chain and the infrastructure people need to make that happen.

>> Yeah, speed is a competitive advantage. It's also a mode. If you can scale it again, velocity is the market. That's the fit. Gentlemen, congratulations on the announcement again. Just bring it together what was already there under one roof. Jyoti, congratulations on your continued success. Been following Harness and traceable for a while now. And again, better together. Thanks for coming on theCUBE, appreciate your time.

>> Thanks for inviting us.

>> Cheers.

>> Thanks for having us.

>> My pleasure. I'm John Furrier here, theCUBE. Breaking into our AI programs with CMOs, part of the NYC Wired and Brian Bowman's new network, the Wired Network and open community where people are gathering, sharing news. And of course this is another data point that speed, velocity and value is accelerated in very short timetables. People are moving fast, making decisions. Here's a great example. Thanks for watching.