ONEiO CEO Juha Berghäll on Evolving Integration Platforms in the Age of AI Agents

Hey guys. Thanks Withrow. We're here with Haw Ol, who's CEO of one io, and we're talking about how integration needs to evolve, especially in the age of AI because, well, it's getting a little complex out there.

Ha, welcome to the show. Thank you. So one of the issues that we seem to see out there is, well, it's getting a lot more complex as we noted, but historically we had a bunch of APIs and then we got a bunch of connectors built on top of those, and we managed them through some sort of centralized platform if we were lucky.

But chances are we just kind of manage them in some sort of bespoke way that was not very efficient. You are. How does the way we think about integration need to change as we start to deploy all these AI agents out there?

It seems to be coming together at a level of scale that is mind boggling at the moment. Yeah, well, I think first thing they're all saying that goes in it, that if you build it, you have to run it. So I think that's the first principle which leads into this, um, more like a holistic thinking of managing innovations as more like a product rather than just ad hoc project that somebody, some hero puts together.

And then we hope, fingers crossed that they work. Um, so that's, that's the fundamental fundamentals not kind of a mindset change that we need As part of that. Therefore, do we need to kind of build the integration platform first and figure out how to manage it before we go build all the connectors?

Well, of course, integration use cases are like various, there are different kind of indications that you, the sim simple, simple from simple, um, um, integrations that can be kind of connector driven. Let's say that you need to hook up your active directory and stuff like that, which is really like simple all the way to this, uh, cross platform workflow automation that involves several parties. So of course you have to weigh, uh, the requirements against the investment investments that you do, but overall, the innovation platform is a kind of a good starting point, but it's only set of tools.

So you really need to have some operations model. You have, you need to have governance, all those things on top so that technology is not, um, enough. Mm-hmm.

We have had integration platforms for years and they're usually managed by some internal IT team. Um, but it seems to me at least that it's not like we're integrating things every day. We do integrate a lot of things, but is this really, you know, a capability that the internal IT team should have?

Or should it just be something that feels more like a service that I just in vogue as needed? Mm-hmm. Of course.

Depends what is your business. If you feel like that innovations are your core business, then of course you invest into your own capabilities. Um, at the end of the day, there's no, no sort of a way of outsourcing responsibility.

So regardless of internal IT team doing them these things themselves or, uh, getting them as a service or something in between, there should be somebody who's responsible of this. So, um, that said, um, majority of the companies, enterprises, they have their internal team to support their business. So things that are not directly creating, um, business value should be somehow put aside or buy both not to invest into.

Yeah. Um, will this whole equation get a little more complicated? We talked about early on in the intro with the rise of AI agents, but are these not gonna be, I don't know, hundreds of thousands of endpoints that need to be integrated, not just with legacy systems, but each other?

And how is that gonna all play out in your mind? Yeah. Well, um, I, I would, I guess that the ai, um, helps us to build faster, first of all.

And then AI agents are as, as, as we see them at the moment, they are mimicking human beings. So it means that they, they still need, um, real time reliable correct data in order to operate. That means that you need the integrations more than ever.

And then the demand is becoming so, so, so much higher because of the AI agents will be deployed, systems will be, uh, and they require more and more data. So you need to build more and more integrations, which means that you have to find ways to scale, which means that, uh, the manual way of, uh, and approach based approach that you bring in bunch of people and start building from the stretch on top of the platform is not suitable anymore. Will we also maybe, I don't know, create AI agents for the integration platforms themselves to help integrate AI agents with legacy applications and the AI agent will talk to one other AI agent, which will then manage the process for them?

Is that possible? Well, they need something in between. And uh, like what you just described is it's sort of considered as a kind of API driven approach that you have APIs and interfaces.

Putting AI on top of the APIs might make them little bit more, uh, you know, intelligent. But the problem is that how, what is the communication? What, where is the communication happening then and how do you do the translations and mappings and all these things with different data models and how do you run the business logic on the integration?

So point to point, yes, that I can see that happening, but then you need to have this, um, multi-point integration use cases. Um, it's unlikely that ai, um, agents can replace it. They can, they can be super efficient when they get the data and can process it and send it over, but how they send it over there needs to be something in between mm-hmm.

Some kind of fabric. Right. And to your point, how that gets accomplished matters, especially from a governance and security and compliance perspective.

So I can't help but wonder if the cart's before the horse a little bit and we're all excited about AI agents without thinking through exactly how these things are gonna get managed. Yeah. Well, I think we, thankfully we have one, one really good example in the, in the sort of past of it, which is DevOps.

I think same fundamentals can be applied, uh, when it comes to managing innovations, taking the DevOps culture, taking the automation, taking the monitoring, having the lifecycle approach, and that leads into better governance, clear responsibilities, accountability, um, SLAs, SLOs, all these things that are making integrations look like more at the products that have some, some, you know, clear reason to exist and they're not to add some, some ad hoc stuff. So I think that DevOps principle would nicely limit it into this picture When it comes to integration. What's that one thing you currently see organizations doing that just makes you shake your head a little bit and go, folks, we should be a little bit smarter than that?

Well, we, we still try to fix, fix this scalability issue with the sort of the old way of doing things, which is, uh, today I think was today Gartner just released the latest magic quadrants for IPAs. And you'll see the same folks there year after year integration platform as a service that's considered as a kind of a, some kind of a silver bullet for this. And nobody's talking about the actual requirements for these integrations.

So we are taking, um, we are enhancing the tools for developers to develop integrations. Uh, but you still need to developer, so I, what you said mentioned about the AI being on the, on the IPAs platform and helping, helping them to develop faster, make more integrations without any management model. And we all remember what happened happened when the shadow it was introduced back in the day, like suddenly you have different things outside within the organization because it's so easy.

But at the end of the day, security, governance, all those things that are super important nowadays, um, they, you need, you just need a model for them, operational model that covers them, the whole thing. From your perspective, um, how will the current platforms need to evolve, therefore, I mean, a lot of people will say, I already have an integration platform. So what becomes the impetus for them to change that out or swap that out and, and, and what's the ROI on that?

Well, I don't think it, it goes down to not only on the platform, what technologies it comes down to the understanding that innovations are, are, are sort of important part of the whole IT delivery as they, uh, are in the supply chain is a good example. Supply chain management innovation have been, have been fundamental for, for that kind of, uh, uh, concept for, for decades. And now within it, we have to wake up that we should have a similar principles, even regardless of the technology we need to invest into competencies, the model, how we run it, uh, the whole approach of, uh, really investing into important things and consider integrations product.

So it takes a, also, I think there's a kind of a skill, skill gap in that sense that companies are not really getting there. And it's not about ai, it's about really having the competencies and understanding what it really takes to run integrations as a, as a kind of a, um, organic part of your it, it ecosystem. Mm-hmm.

So as you look forward to this new AI slash API driven world, you know, how many APIs will organizations be managing, do you think? And then, you know, are we gonna see some level of scale here that people aren't quite prepared for? Well, I think it was, um, what it, MuleSoft or Salesforce, um, study about this app, number of applications that we add, uh, every year in the larger enterprise, it's hundreds of new applications will be kind of added, especially like terms of ai.

So there will be a lot of interfaces, APIs, and now the question is that how do you make sure that they are, uh, they match into your security re requirements, all these things. So it, it's, the scale will be, will be just like we, I think we just, we, we have just scratched the surface when it comes to a number of APIs and interfaces. And that being said, you need a governance model, you need operational model, otherwise you're gonna be like, you're, you're sailing your ship without knowing if all the, all the hatches are electric, are closed.

True that. So what's your best advice ultimately for IT folks out there as they kind of think this through and they start to, I guess, recognize the level of scale? What should they be thinking about?

Mm. Quite often we think when we discuss with the customers, the biggest pain is that they, they say that they have technology, they have integration capabilities when it comes to team, uh, competencies and, and things like that. But they still have a backlog of six months to getting there, which means, of course, simple answers you have to prioritize.

But how do you prioritize if you don't really know what is the most business critical, um, uh, for instance, for what, what is the most bus business critical innovation for you? How do you do it? So, um, my advice is that you really step back from technology perspective and start thinking that how do we actually deliver integration in integration at scale, which means that the operational model, how do we, how do we ensure that we are credible deli in delivery on time?

All these things that are like basic stuff to any, any IT operation, but integration are integrations. Integrations are not often considered as, as a product. So people don't think them like that.

So I will start with that type kind of a thinking that should be turn our thinking into more productized, standardized approach and what, what kind of investments we are willing to, to take in order to get there, which means then you have to prioritize, All right, folks, well, you heard it here. Hey, when it comes to integration, we're gonna be looking at things at a level of scale that might be mind boggling, but at the end of the day, it all comes down to the fundamentals. But if you don't start with integration, you're gonna treat it as an afterthought.

It's probably gonna go wrong. You ha, thanks for being on the chair. Thank you.

All right. And back to you guys in the studio.