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Intelligent Automation: A Conversation with Tray.io – Futurum Tech Webcast

Intelligent Transformation: A Conversation with Tray.io - Futurum Tech Webcast

On this episode of the Futurum Tech Webcast – Interview Series, host Daniel Newman welcomes Rich Waldron, CEO and Co-Founder of Tray.io for a conversation on the company’s mission to deliver the intelligent autonomous enterprise, enabling organizations to composedly, collaboratively, and continuously transform every business process using AI to achieve breakthrough agility and unlock hyper efficient growth.

Their discussion covers:

  • An inside look at Tray.io’s mission and the challenges that enterprises face when deploying new technologies and integrating them into their current and legacy systems that they depend on every day to run their business
  • What Tray.io sees as the key to successful AI implementation
  • How Tray.io is approaching intelligent transformation for enterprises, enabling developers, technologists, and teams to collaboratively compose and deliver using AI

To learn more about Tray’s perspective on AI and to download The Futurum Group’s research report on composable development, click here.

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Disclaimer: The Futurum Tech Webcast is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded, and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors, and we ask that you do not treat us as such.

Transcript:

Daniel Newman: Hey, everyone, welcome back to another episode of the Futurum Tech Podcast. I’m Daniel Newman, your host, founder and CEO of The Futurum Group. Excited for this interview series. Conversation today, we’re going to be talking about iPaaS, but we’re going to be talking about digital transformation, artificial intelligence, the challenges that enterprises face when deploying new technologies and integrating them into their current and legacy systems that they depend on every day to run their business. I’m going to be joined today by Rich Waldron, CEO of Tray.io. Rich, welcome to the podcast. How are you?

Rich Waldron: Hey, Daniel. Great to be here. Thank you.

Daniel Newman: Hey, it’s been good to spend some time, and over the last year I’ve been paying a lot of attention to what you’re doing over at Tray and also to the entire industry. For nearly a decade, I’ve written about digital transformation, the challenges that companies have, the mix of people and technology, and of course, they always say people process technology that is required to be successful in driving transformation across the business. But you have been busy solving a really hard problem, and that problem really has to do with how companies are able to continually optimize and implement next generation applications and technology, maximize the utilization of their data, and do it in a way that is as frictionless as possible. And I’ve been really impressed with what you’re doing. So let’s talk about that today, but let’s start out just doing a little bit of the background stuff. Well, I’ve seen the rise of Tray across the industry, and I’ve seen your name more and more. We want everyone out there to know a little bit more about the company. So why don’t you give us a little bit of the background?

Rich Waldron: Yeah, sure thing. And you touched on so many interesting points there that really play into the arena that Tray’s focused on. We started the company really out of frustration with trying to automate so many processes across our own business. And what we found is it took so long to build this stuff, only for the process to then change overnight. We bought a new service, we’d connected a new source of data, we changed something in the business or the market that we were going after, and you kind of get back to square one. You have to go and rebuild the whole thing all over again. And so we set out to build Tray to be the quickest possible way to build enterprise grade integrations and automations. And as we’ve all been watching from the sidelines over the past 18 months or so, as AI has exploded on the scene, we’ve really been able to embrace that and become the AI-powered multi-experience iPaas, the place where you can build out your business process, you can build it dependent on whether you want to write code or build it in a low-code way or now just type out what you want and have it appear. And for us, it’s all about making the CIO’s life easier. How do you govern this stuff? How do you run it at scale, and how do you deal with a framework and a business environment that is changing so fast all the time?

Daniel Newman: Yeah, and I think that’s the key. You and I straight away are coming to this conclusion that the pace of change in innovation is so fast. And if you look even just week to week… A little backstory, Rich, at the beginning of 2023, we were all sort of seeing the explosion of generative AI. And it really happened late in ’22, but kind of coming out of the gates in ’23, I think everybody knew this was going to be the talk of the town if you’re an enterprise. And we saw in the beginning it was the have and have-nots. If you had GPU power, did you have data scientists? Did you have coders? Did you have the ability to basically do the buildout from a hardware at the IaaS level, buildout with the platforms, and then, of course, develop applications for your business that could enable you to do more with your data and use these generative tools. Within just a matter of a few months, you saw companies including OpenAI, Microsoft, you saw Google, we saw Meta with Llama, of course, NVIDIA with what it’s done with certain abstraction layers. But you started to see this stuff be built into every application.

And so we went from this like, “Oh, my gosh, you need all these capabilities, resources and hardware at your disposal in order to be successful with generative AI,” to, “You really just need to be able to connect all your data sources to these tools that are being built, these low-code, in some cases, no-code tools that are being built to basically enable you to very rapidly implement and benefit from AI technology.” And that’s something that, again, it sounds easy, but this is where I’ve been so interested in what you’re doing is because the one thing that isn’t always solved for in any of these applications is the complexity of the data landscape, the data state that most companies have. It’s like, yeah, you can do something generative with the data in your Salesforce implementation, or you can do something generative with the data in Oracle, but what if you want to use the Salesforce data, the Oracle data, and also maybe take something out of a different data, a different SQL database? Maybe it’s your data lake or maybe it’s different operational data from your supply chain software. Anyways, so you guys really talk about iPaaS because in order to do everything I just talked about, you do need to be able to connect all those data sources. You need to be able to do it quickly and an ongoing basis. Talk about this kind of assertion. It seems to me to be really the principle in which you’re building this company upon.

Rich Waldron: And the way I think about this is, and in many conversations I’ve had with CIOs lately, this has fast become the CIOs’ biggest nightmare because if you sort of take yourself back to the start of the pandemic, most companies, and as you talked about, you’ve been writing about digital transformation for 10 years. Well, for a lot of companies that acceleration occurred overnight, right? Your entire workforce suddenly got stuck at home. How do you give them access? How do you provision applications? How do you enable everything in the cloud to happen really quickly? The speed that you decided to embrace the cloud opportunity at was kind of taken out of your hands. So for many IT orgs and large enterprises, they were having to use these legacy iPaaS tools that were built for a different era. They were built to take on-premise data, push it up to the cloud, they were built for a different type of architecture. They weren’t built to connect to so many sources and to support so many sources at scale. So the first problem that you had to deal with was, “Oh, hang on a minute. We’ve bought way more applications than we need. There’s data spread all over the place, and we now need to start automating it and get it to kind of sing together in the right orchestra for us to be able to move quickly as a business. Our competition is moving faster than us.”

So the first state was user service like Tray, a kind of modern iPaaS, that would give you that capability instantly. You could build that in low-code, you could write that in code, and we would take care of all of the stuff behind the scenes that creates problems here, all the queuing, all the transactions, all the resiliency. Everything that is an issue in maintaining and supporting robust cloud-based automations, Tray took that pain away, versus the old model of use a legacy service bus, stand this thing up using multiple code environments and have to figure out the scaling of your own machine. That doesn’t make sense in this new world. So that digital transformation challenge kind of appeared overnight for many companies and they got to serving it using modern iPaaSes like Tray. Well, you wake up at the start of this year and there’s this talk generative AI and it slowly becomes that this is going to be an important part of your strategy. You’ve just spent so long trying to figure out how to get everything kind of connected together. What the hell do you do now? How do you solve for every single one of these applications kind of rolling out its own AI and its own model that’s going to overwrite each other, that’s going to create an entirely new headache for the organization? And I think the role that the iPaaS player plays in this world has also changed really drastically. If you go back historically, iPaaS meant a very specific type of service architecture. It meant a very specific type of integration. And over time, that then brought in things like ETL and data integration and business process management.

And I think now going forward, it’s the foundation or the place where AI is going to be orchestrated, because when you bring AI to business process, that’s the thing that speeds up a business the fastest. That’s where you can use things like sentiment. That’s where your quote-to-cash workflow can change, or your lead lifecycle workflow can improve based on what’s happening within the market or what context you’re able to get from other applications. If you let loose every application within your stack with its own homegrown AI, you lose your role in IT as being chief joining officer. You have to become an AI referee, and you don’t stand a chance. So for us, it’s all about how do we first enable you to deploy automation at scale in a way that’s resilient, governed, and controllable. The second order is all about, well, how do you harness AI across your organization? How do you take advantage of all these amazing gains? Because when you apply them to process, that’s really the thing that is unique to your business. Market changes, your product changes, everything else moves around. Even the tooling and the data changes, as you point out, right? How do you deal with all these different datasets and all these data structures? Well, the process is kind of the thing that stays the same, and that’s what you maneuver everything else around. So being able to evolve that, being able to grow that with your business and being able to infuse AI into those processes as you develop them becomes a critical weapon as you go to market in this world. And really, I think we’re all worried about getting left behind. How do I stay on top of this stuff and build these things out in such a way that it doesn’t create risk, but does allow us to benefit from the amazing innovation that’s happening everywhere.

Daniel Newman: Yeah, you definitely want to minimize risk. I like that AI referee, Rich. I think there’s a lot of that going on. Put on the zebra stripes, and you get the whistle.

Rich Waldron: That’s it.

Daniel Newman: But it is a little bit of a turf war. Every company is kind of like, “We’ve got the AI solution for you.” And I think you’ve got this kind of battle between monolithic AI experiences being created by big or mega tech companies, and then you’re competing with these sort of point solutions that are maybe going to do one particular thing really, really well. And then, of course, you’ve got this constant barrage of the data source conundrum. You have all these data sources; are you able to tap into all the data sources? And then you kind of put that all together, and this is why you started the conversation where you did with the CIOs having a bigger headache than ever before. And the thing that I’ve learned, and I’m sure you could probably agree to this is over the last decade plus of digital transformation is the time from disruption to disruption is only going to get shorter, meaning the next wave of innovation, you’re like, “Oh, well, look at what happened between November and middle of this year.” What do you think is going to happen between the middle of this year, end of this year, the next year? It’s just going to keep getting faster. More companies are going to have more solutions. They’re going to want you to tap into all of them. They’re going to make you feel like you have to use it in order to be successful. You’ll hear things like, “The best feature sets are only going to be delivered if you buy our cloud solution.”

And the whole idea of iPaaS is optionality, right? It’s focusing at one layer in terms of how you’re going to connect all these data sources, and then also being able to have a bit more control over which applications you’re going to benefit from. And just to go a little bit further, I’ve talked to some of your peers, some of the CEOs across the industry, and I do think there will be less total front end applications, meaning the goal is to minimize the front end, but it’s not going to remove the back end applications. You still need these applications to run. So you need systems to bring all this together, and that’s what I’m hearing from you is really the problem you are trying to solve. Now, I’m going to ask you the question. This is either the hard question or the layup question, depending on how you want to approach it, Rich. But effectively, Tray is the modern iPaaS. So you know there’s other companies out there that say, “We do this,” and there’s others that’ll say, “We do what you do.” So what is different and what have you done different in the approach, specifically when it comes to your iPaaS with Tray, that is making it the modern solution that’s going to allow for the key joining, chief joining, chief orchestration of AI that companies are looking for?

Rich Waldron: Yeah, I think we’ve done a number of things. So firstly, we are built for a cloud era, right? We’re built for a world where everything’s on all the time, everything happens in realtime, everything’s connected via API. We have the luxury of not starting in a world that was thinking about embracing that and not having seen what those standards look like, not having had to figure out what that orchestration or process looks like. So that’s kind of your first order.

The second piece is, from an infrastructure perspective, we benefited from a significant shift in backend technology during our development. So we were able to take advantage of technologies like Serverless and containers and Kubernetes and tooling that effectively meant that we can handle high throughput extremely quickly. But more important than that, we’re able to bring together the different facets of creating an automation, so being able to view your logs within the place that you build the workflow, being able to debug live within the product, being able to handle the deployment end-to-end all within the same browser-based approach. So it means that across the board, everything’s happening within one unit. Secondly, everything that we built, we built with an API-first mentality, and we’ve opened up those APIs over time. So as an integration engineer within an enterprise, I can tap into the Tray infrastructure and I can effectively build the solution in the way that I want. And so comparative to a legacy approach, which was far more restrictive, required far more verbose programming or a very specific language set, didn’t have the connectors that exist out of the gate to enable you to connect to all these different sources and wasn’t built with this consideration in mind, you end up with a drastically faster and better experience. Our automations are being stood up in hours and days rather than months and years. And in a world that’s moving as quickly as ours, that makes a significant difference.

I think the second piece of that puzzle is when you then start thinking about something like deploying AI or taking advantage of it, I think AI ultimately accentuates the platforms that were built from an infrastructure perspective. So if you think about Tray, we’re built with all these different connectors. We’re built to handle this process at scale. We’re built with governance in mind so that when you use AI against that model, it allows everything to move much faster. And as we’ve kind of seen the explosion of SaaS, and now, I think, the consolidation of SaaS, that’s very much the theme. Every IT org is looking at all these applications and saying, “Do we need them all? Can we shrink down the footprint? What are the core services that we should buy?” Well, they’re the ones that ultimately get to take advantage of AI the best because they’re the areas that have the biggest impact on your business. And if you don’t have that footprint, if your tooling is built to purely support something or sit on top of a singular other service, that’s as far as your AI effort can go, whereas using a platform like Tray, we can connect to every part of your business. We can automate every process and every step that you have. We can help support the way that data moves across your organization and take action on it. And so when you are able to control the governance of that, that provides that security and removes that risk that we’re also so worried about.

And I think over time, we’ll see more and more of that kind of embraced approach to AI whereby you’re not going to want to allow independent AI agents to build and deploy code in random places across your architecture and kind of create the second order of the problem that digital transformation created, which is lots of applications everywhere. Well, if you’ve got to support lots of agents everywhere and ultimately build some sort of AI to maintain those as well, you end up kind of back on the hamster wheel. So I think as we look ahead, really, the face of iPaaS is changing. I think the requirements that are going to be placed on this industry are going to change significantly as well because suddenly it’s not just about connecting the pieces, it’s about building on top of them and using them as a core to go and speed up the way in which your business performs.

Daniel Newman: Yeah, you said a lot there, and there’s quite a bit to unpack. A couple of quick double clicks from my end is, one is the experience that enables… I think you’ve measured it at about 10x faster value coming out of AI. And of course, as an analyst, I’d love to read a bit more on how that’s being calculated, but that has to be monumental in terms of business value, Rich. The second thing is I really like what you’re doing, kind of living the AI within the platform, adding natural language capabilities. Not everyone’s a coder. Not everyone can develop code. Not everyone’s even a low-coder. But oftentimes, inside of the business where a lot of these applications need flow is someone can explain what they need to have happen. And if the ability to explain what needs to happen is an enabler for developing a process, implementing and deploying, you’re talking about real business value that can be abstracted quickly by providing this level of capability to the users. So those are a couple of things that really did stand out to me there. And of course, there’s quite a bit more, and I hope everybody’s going to digest this a bit. As we kind of close down this conversation, Rich, I’d love to just get your feedback on the process you typically see your customers go through. We spent some time even at The Futurum Group evaluating, and we’ve been impressed by what we’ve seen with Tray, as a company like ours that runs in a different ERP and a different sales, and just seeing how you can quickly tie these things together. And we’re a small but growing company. Who are the customer profiles? What is the typical process of them identifying and then coming over to Tray? And then give us a little bit about how they can learn more if they’re interested in discovering how iPaaS from Tray could solve their business problems.

Rich Waldron: Yeah, and I think you hit the nail on the head, which is it starts with recognizing value and figuring out how quickly you can get to that value. I think you’ve undersold yourself a little bit there. The Futurum Group is growing at a rate of knots and acquiring companies all over the place. And actually, that’s kind of a great example of the entry point for a service like Tray, right? So you’ve got many applications that are used to run your core business. Your processes, I imagine, are changing pretty regularly. You’ve got maybe different methods of going to market, different companies that you’re looking to keep up with. As you have bought other organizations within your own, that means adopting their processes and their datasets and kind of bringing them together, and each of those creates an entry point for an iPaaS, because you’re then recognizing and looking at your system and saying, “Well, hang on a minute. There’s got to be a way that these things can work in tune. There’s got to be a way in which… We need to stop doing this manually. That doesn’t make any sense.” And so you go out and look in the market, you find your way into an iPaaS conversation, and we should be able to demonstrate, either via you getting into the product or over a short call, how quickly you can get something stood up that recognizes that value. The typical organization that we sell to is an enterprise organization whereby we’re selling into the departments themselves that are trying to solve lead lifecycle issues in marketing, quote-to-cash issues in finance, and really many other process speed improvements across the organization.

We’re also really oriented towards selling toward IT. That’s in supporting the back office process itself, but also being a great collaborator and partner to the rest of the org, right? Everybody knows they create a ticket for IT when they want to get something done, and IT is then burdened by all of these tickets that come in. They can’t move quickly enough on the legacy provider they bought 10 years ago; they need something that’s going to allow them to move faster. And then lastly, we sell directly into product orgs that want to be able to expand their integration footprint and bring data in from other services on behalf of their customers. And so they use us to effectively white label their own integrations and make those accessible to their end customers. By bringing this experience together, we call it the Universal Automation Cloud. It’s the one platform that you go to build out your automations, manage them at scale, manage the governance, manage the permissioning model, and effectively enable you to go faster as an organization. And so every single one of those touchpoints creates a way in which we’ll engage with a customer, and in many cases, that means them getting stood up in a trial, building out this thing to close to final deployment during that initial engagement, and then us being off, ready to hit the ground running as soon as they become a customer.

Daniel Newman: And there, Rich, is a great place to end. What I’d love to do is make sure that everybody out there knows that in the show notes, there’s some links. If you want to learn more about how to get started or how to connect with Rich and his team over at Tray, I would love for you to check it out. I can tell you, like I said, from having looked at it, we definitely see the value, the use case, and we are continuing to monitor this situation, which does mean companies need to evolve the way they think about connecting their services across very complex and fast-changing landscapes. Rich, I’m excited. Always love hanging with CEOs that are doing things to disrupt the industry, and I’m really excited to continue to follow your success, so thanks for joining. Hope to have you back on the Futurum Tech Podcast – Interview Series in the near future.

Rich Waldron: Thank you, Daniel. Been a pleasure to be here.

Daniel Newman: All right, everybody, hit that subscribe button. Join us here for all the Futurum Tech Podcasts in the Interview Series with other great CEOs and leaders across the business landscape just like Rich Waldron here from Tray. For this episode, though, time to say goodbye. We’ll see you all really soon.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.

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