theCUBEd Awards | Tray Universal Automation Cloud by Tray.ai (Most Innovative Automation Product)

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Rich Waldron

Co-founder & CEO

Tray.ai

Alistair Russell

Co-Founder/CTO

Tray.ai

play_circle_outline Benefits of automation and AI for technical teams and business transformation

play_circle_outline Adoption of AI in automation, success stories with customers highlighted

play_circle_outline Challenges and solutions in handling scale and platform architecture for success

play_circle_outline Distinct aspects of Tray.ai's approach enabling success and pushing boundaries

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Tray Universal Automation Cloud by Tray.ai (Most Innovative Automation Product)

Rich Waldron

Co-founder & CEO Tray.ai

Alistair Russell

Co-Founder/CTO Tray.ai

Rich Waldron, Co-Founder and CEO, and Alistair Russell, Co-Founder and CTO, both of Tray.ai, join us in this engaging episode of theCUBE Tech Innovation Awards. Hosted by John Furrier, this discussion delves into Tray.ai's innovative journey and recognition at the inaugural CUBEd Awards. Waldron and Russell share their insights into the evolution of automation and the pivotal role of Artificial Intelligence in transforming traditional Integration Platform as a Service solutions and beyond.

Throughout the conversation, key takeaways emerge, such as the ... Read more

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What was the speaker's experience with AI machine learning and how did it impact their work in automation technologies? add

What are some examples of successes achieved by organizations using Tray agents and other sources? add

What is the reaction of most technical people to modern technology such as the use of automation and AI, specifically in terms of enhancing productivity and helping fast-growing businesses adapt quickly and efficiently? add

What approach did the organization take in deploying automation and building their architecture that has allowed them to be perfectly set up to handle prompt engineering and adaptable to market changes? add

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Tray Universal Automation Cloud by Tray.ai (Most Innovative Automation Product)

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>> Hello, welcome to theCUBE here in our Palo Alto Studios. I'm John Furrier, host of theCUBE. We are here celebrating the Tech Innovation CUBEd Awards, an inaugural awards program. We're celebrating the winners and the competition was fierce. We got a lot of entries, a lot of high caliber companies showcasing their innovation across the tech landscape. Today we're joined by Rich Waldron, Co-Founder and CEO of Tray.ai, and Alistair Russell, also Co-Founder and CTO of Tray.ai to discuss their award-winning entry and the innovation behind it and how they're driving the innovation forward. Guys, we got the founders here, and you took the most innovative automation product, which by the way is huge honors because everyone's automating. It's the top kind of gen AI, pre-gen AI, pre-agentic, and soon to be very key as part of the platform engineering and agentic system so congratulations to both of you guys and the entire team.

Rich Waldron

>> Thank you very much. Yeah, huge pleasure for us to be here and receive this award today so thank you very much for having us.

>> We had 43 judges, and I think we'll have more next year in the community who loved it. Again, we're going to do another one. We're always worried about inaugural events, will it be the last? So congratulate, but there will be another one, and you guys are in the first class of winners so let's just jump in guys. Innovation has been central to this awards. Can you share how you guys approached the challenges in the market in the innovative way and just give us an impact example, quickly set the table?

Rich Waldron

>> Yeah, for sure. I think that the key point here is automation, as you already alluded to at the start of this conversation, has basically had to completely rethink itself. As you think about traditional iPaaS and deploying integrations in automations within organizations, AI has come and completely rewritten the book for everybody and really every process is up for grabs. A huge effort for us and a massive shift this year and my own personal belief is that iPaaS has evolved. It's already happened. It's already changed, and so we've made a huge effort in making AI central to our automation experience from an agent perspective as well as AI infused or driven workflows.

>> Alistair, any point from the CTO perspective, obviously you guys both co-founders, love the founder action. What's the perspective on the key innovation and impact?

>> I mean, Rich mentioned it. Yeah, AI has had a big impact and I mean personally I've been interested in AI machine learning for a number of years and we were thinking about how we could use it and utilize it within automation. And then I think a couple of years ago we launched Merlin, our intelligent agent, the first version of it. That was unique in the iPaaS market and it really revolutionized how our customers were building automations and also thinking about how the future was going to evolve and how it was going to change the way that automations even themselves were running. Yeah, it's definitely key.

>> Rich, you mentioned iPaaS, obviously we've been covering that market for a long time. You mentioned the modern era. Looking back at the journey and the product and the company, what was the key turning point and decisions that helped you guys get that product out there and get that recognition today?

Rich Waldron

>> Yeah, there were two key turning points from my perspective. The first one is early on, it was obvious that not only was cloud going to continue to be the dominant force from an application and data layer, but the types of people within each organization, within each department were becoming inherently more technical. iPaaS is something that historically always relied on very heavy set engineers and Java programmers to create very complex solutions. We took the approach of can we take all of the scalability and all of the complexity that you need to build a great integration, and package it in a way that meant you could harness this within an organization much faster, take advantage of all these cloud solutions and really position ourself on that wave. That set us off in the right direction and saw us accelerate through. I think the second order that's occurred is that we made a sharp turn into AI as soon as possible. What we've heard from our customers and what we've been seeing is that demand for their integrations and that the ones that they want to build going forward are considering AI first. From an iPaaS perspective, it's not good enough just to be an iPaaS anymore. You've got to be an iPaaS that can handle AI workloads that supports AI capabilities and provides these things natively out the box. It's changed the way that CIOs are operating and thinking about the platforms that they have within their own organizations.

>> I always use the music analogy a lot when I talk about some of the cool things going on with runtime, anything that's runtime, certainly gen AI fits the category. Orchestrator and composer, those are key people in music, and we're playing a lot of AI music right now. You look at say Kubernetes, big orchestration role that plays there. You mentioned integrations because I love that you guys have that whole composition positioning of integration because composable apps, I've always loved that term because it's always been hard to integrate, but can you guys share some of the things you're doing with the integration? Because we're seeing enterprise AI adoption in areas where there's domain-specific knowledge, end-to-end workflow, process knowledge, and then integrating it all together always has been hard. And if you guys can also comment on what the customers are doing, because remember, they bought a lot of tools, they've had a lot of platforms and sometimes they don't want to let go. So now they might change a process, but our research shows that, hey, you know what? Process management and changing process is better than swapping out tools. I mean, nobody wants to change tools if they don't have to. These are market forces, can you guys comment on and share your reaction to that and do you believe that or what?

Rich Waldron

>> Yeah, I think you touched on a really important point there, which is the best performing organizations that we see and the most forward-thinking CIOs that we work with, they think about creating their own experience layer within their organization. The tools can change, the services can change, even the underlying data can change, but if you construct these things in a composable manner where you figure out what the process is, it becomes really easy to swap in and swap out solutions. We've seen a big drive from customers in consolidating the tools that they already had in their stack and trying to reduce down the number of applications that they have. And on the flip side, because they've structured and built their organizations in a composable way, it means that they're the ones that can innovate and use agents the quickest. As I'll ask Ali to comment on in just a second, what that enables is once you've got the data in the right place, once you've got that composition set up, then you can actually go and harness these agents to act across the entire organizations rather than being single threaded. That's the key component that we've seen with customers. Ali, I know that a lot of the work you've been doing in setting up some of the tooling and things like adding vector data support to the product has meant that customers are set up to go and continue to take advantage of AI thanks to composition. Maybe you could comment on that.

>> Yeah, absolutely. I mean you've mentioned orchestration and composing and those two terms, but I also like to think of creators and consumers when it comes to composability. We have people within the business that are way more technical that can create composable assets that others within the business can consume. That's even more important in the agentic space where we're starting to have companies build agents. The tools that the agents use, they are composable building blocks, they are connected to different systems. They have a single purpose. Non-technical people can come in and start building agents that by picking and choosing the composable building blocks off the shelf so composability is a hugely important part of both the automation space and the future of agents as well.

>> Yeah, everyone uses the Lego blocks example. I love that kind of having, just putting the package together. Rich, you mentioned single threaded. Can you just share for the folks watching what single threaded means and then obviously what multithreaded means? Now my processor brain goes off, but putting that aside, is that a process issue, workflow, people, what is single threaded versus what?

Rich Waldron

>> Yeah, I mean it's applicable to everything. In the way that I was describing it, I think of this as the solutions that you purchase, right? If you think you're a CIO or a senior person within an organization, you're looking at your technology strategy, your options today are we have to go and take advantage of AI, we have to get the movement going within ourselves as an organization because it's pertinent to innovation. In order to do that, do we go and buy lots of individual AI solutions that we deploy across an organization? And then do you become the de facto AI referee who has to manage and handle the governance and the capability of all these different solutions? Or do I go and turn on the AI for every application I've already got and still play that same role? This idea coming back to composition is if you set things up correctly and you structure them in such a manner, you can go and build these multithreaded agents that can go and take action across the entire stack without requiring independent governance on a per application basis. It gives you a centralized way to go and operate. The companies that move quickest, the ones that we are seeing who have adopted that mindset, they're flying right now. It's exciting to see the speed that really large enterprise organizations are actually operating at with this new technology.

>> Awesome. Yeah, and I think that's one of the things people are looking for. They want low-hanging fruit, they want wins out of the gate with AI. Can you guys share any wins you're seeing with your customers with the product? Obviously automation drives a lot of free time or value shifts. Can you share a little bit of some of the successes?

Rich Waldron

>> Yeah. I was actually just on a call with the CIO of Zura last week. He shared that using Tray agents and a combination of other sources, they reduced the number of tickets their IT team processed or the IT agent processed by 3X in less than six months. So if you think about that just from a volume perspective and just from a gained productivity perspective, there's a direct measurable outcome to harnessing knowledge across an entire stack, being able to take action across multiple applications, and then applying it to a business problem that every organization has. In the same vein, we see lots of organizations doing things like auto-generating the first pass at marketing content using voice and using pre-existing content and ingesting knowledge to go and do that all the way through to sales processes, handling things like RFPs, or carrying up on next steps based on outcomes. All of these things are data points that we have that were impossible to reason over historically, and now that's moving organizations in the right direction very fast.

>> Alistair, weigh in on this because every company has a team that evaluates, how are the tech guys loving this? How are the tech teams? Obviously, you take the Jira tickets, that's an easy win. Boom, knock that out right away. When they start getting into, wow, I got more time to drink beer, which I've heard on theCUBE before, which is basically a code word for I'm going to work on cooler things, what's the reaction on the tech side on the adoption? Is there any objection? How does it roll out? Take us through a day in the life of the teams that evaluate Tray.ai.

>> I mean, it's modern technology. There's always that initial rollout and the reaction is different depending on different people. But to be honest, I think the reaction we've seen for most technical people is this is incredibly powerful. They're seeing the value of it. Even from a Copilot perspective, the ability to enhance your day-to-day productivity with AI. Even our engineers at Tray, they use Copilots to help code. It's not replacing their creativity, it's not replacing the stuff they do, it's enhancing. It is making them that mythical 10X engineers, and we're seeing the same across our customer base that people are getting more done. And that's key. That's key for fast-growing businesses. They need to be as fast and adapt to changes as quickly as possible. And technology like automation and especially combined with AI is really helping that happen, and the best companies are adapting and embracing them basically.

>> Yeah, you get more engineering, the 10Xs here, but also the business transformation is the 10X business input too. We're seeing a lot of the examples. Guys, I want to just focus in on one thing. While you got both of you here, every successful company has their own secret sauce. What would you say is the most distinct aspect of your approach has enabled you to push the boundaries and achieve this award and just a success?

Rich Waldron

>> I think the key for us is we are a extremely product driven organization. We've got the classic founding story, and there are three founders. I was the bad engineer and you're lucky to have the good engineer on this call as well. I think we took an approach at the time that was very different to the ways that you would go and deploy automation. It was far more experience driven, it tried to abstract away a lot of the challenges. We built our architecture in a completely different way so that every execution was handled individually rather than the classic container model. And all of those things together have meant that as AI has come tour de force, we're perfectly set up to handle prompt engineering. We're perfectly adaptable to all of the changes that have occurred in the market. We kept this ever evolving approach to the way that we develop product and stayed right on the pulse of it that I think really underpinned the difference that our customers feel when they use us as a AI-ready iPaaS versus maybe some of the more legacy vendors that are out there.

>> Alistair, you want to weigh in on this too?

>> No, I mean, I agree with what Rich said. I think that as founders and as part of our story, we were open to change. We were open to adapt as well. We spent a number of years really focusing on both the user experience of the product and also the scalability. We knew we needed to build an enterprise ready platform that could handle the scale of billions of transactions a month. We've really focused on that balance, and I think that's really put us in a good position. Adopting standards, making sure that there's the composable architecture has allowed us to really move fast ourselves as we've innovated in the last couple of years, especially with the AI revolution.

>> Well, great to have you guys across the pond, all the way to California here in Palo Alto. We've got our New York City studio in the NYSE, we'll certainly have you over there soon. Final question, what's the origination story? You got three founders, Rich, you've got the short straw to be CEO. Tell us what's happened. I'm only kidding by the way, it's just a joke.

Rich Waldron

>> No, I mean, it-

>> Tell us the story.

Rich Waldron

>> It's a classic founding story in that we were working on solving slightly different problems within different organizations, and I was writing these scripts that would carry out the functions for people that we weren't able to hire or didn't have. And like many of the scripts that I wrote 12 years ago, whilst they were very valuable, they often failed. APIs were more brittle, the solutions were much harder to use. And so Ali coming in and cleaning up that mess and saying, "Look, there's a better way to do this. There's so much power trapped in these applications that is almost hindered by the UI. What if we could create a better way to go and compose and create these experiences?" We approached it from that perspective, which is how do you unlock an amazing capability and set a power within an organization without all of the burden that comes with deploying applications and trying to scale things and all the challenges that any engineer will tell you about, which isn't the construction, it's the ongoing maintenance. As we were driven to solve that problem, it led us just to approach it in a different manner and I think it's a product that we dearly love and a challenge that we continue to enjoy solving.

>> Alistair, you mentioned APIs are brittle, I can almost see the scripts crashing in my mind's eye there, but even now, APIs are critical infrastructure. 80% of the interactions are through APIs. Now you've got gen AI, things are behind the API, so this is critical infrastructure. You mentioned scale. I mean, pre-agentic mode we're in, agents are happening, starting to see them roll out, but they're going to have sub-agents. We cover that deeply at SiliconANGLE and theCUBE. How important is platform engineering and having that foundation to bring in the army of agents that are coming?

>> It's absolutely critical. I mean, it is key that one of the first customers we ever had while we were building the platform was throwing billions of events at us every month. I think they would spike at the end of the month, and I think they did a load of financial reconciliation or something along those lines, and we had to be ready for it. I think we learned out in the trenches in many ways. We learned from the beginning that we needed to handle this sort of scale, and the platform was built. As Rich mentioned, we didn't take a typical architecture route. We didn't try and bundle things up. We came about or matured at the time of containerization, Kubernetes, things like that. But we built essentially a distributed messaging system to ensure that we could handle that sort of scale as the platform was adopted more widely. It really has helped us, especially with the agent and AI future.

>> Rich also, thanks for coming on. Congratulations for winning the most innovative automation product. Congratulations, and welcome to the inaugural first class of the CUBEd Awards. You've been CUBEd, thanks for coming on.

Rich Waldron

>> Thank you very much, John.

>> Thank you.

>> All right, take care guys. I'm John Furrier here in the Palo Alto Studios for theCUBE Tech Innovation Awards, the CUBEd Awards. We're celebrating the winners, thanks for watching.