Boomi World 2026 | Ken Schmitt, TechStone

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Ken Schmitt

Managing Partner

TechStone

play_circle_outline Techstone at Boomi World 2026: Houston Platinum Partner Accelerating AI Infrastructure for Data Transformation, Mastering, Integration, Intelligence, Visualization

play_circle_outline From Plumbing to Power: How Data and the Super‑CIO Are Reshaping the C‑Suite

play_circle_outline Two-Week Fixed-Fee AI/Data Readiness Assessment: Scorecard, Source-to-Target Traceability, Data Quality, Governance, Roadmap

play_circle_outline Boomi enables fast M&A integrations; Claude/AI can reduce weeks-long projects to days

play_circle_outline Use case: Select Water — Boomi master data, treasury DSO improvements, AI workshops

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Ken Schmitt, TechStone

Ken Schmitt

Managing Partner TechStone

In this interview from Boomi World 2026, Ken Schmitt, managing partner at TechStone Technology Partners, joins theCUBE's John Furrier to discuss how data management has evolved from back-office plumbing into the strategic foundation for enterprise AI. Schmitt draws on 22 years of data consulting experience and a decade-long Boomi platinum partnership to explain why fragmented, siloed and low-quality data remains the primary blocker for AI initiatives. He outlines how organizations are elevating data leadership to the C-suite — with roles like chief data and a... Read more

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What is Techstone and what does the company do? add

How is the convergence of analytics and generative AI transforming businesses and IT (including roles like data officers and the C‑suite), how are customers approaching and implementing these changes, and what practical ways exist for organizations to get started? add

What does your two-week, fixed-fee AI/data readiness assessment (as part of Techstone MD) entail, who performs it, and what deliverables and outcomes can clients expect? add

How do companies handle data and systems integration during mergers and acquisitions, and how can platforms like Boomi (with AI) accelerate that process? add

What is an example of a client use case where Boomi was used to help a company's treasury or finance team reduce days sales outstanding and resolve receivables/customer data issues? add

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John Furrier

>> Welcome back, everyone, to theCUBE's live coverage of Boomi World 2026. I'm John Furrier, host of theCUBE, with Gemma Allen here. She's out getting the stories out here, and the innovation of AI is happening. The AI infrastructure is really crushing it, moving along. It's booming, and in the spirit of booming, of course, it's causing a lot of enablement. You've seen coding, you're starting to see agentic infrastructure, agentic engineering, of course. It's all about the data. Our next guest is going to break that down for us. Ken Schmitt, managing partner at Techstone. Ken, thanks for coming on theCUBE. Day two of our coverage.

Ken Schmitt

>> Yeah, I appreciate it. Glad to be here.

John Furrier

>> We've been following data, Boomi, I should say, and the data piece of it for about 15 years. You've been covering it with them for a long time. Data's the key. This is what you do for a living. Explain Techstone and what you do.

Ken Schmitt

>> Sure. So we're a data management consulting company, headquartered in Houston, been around for 22 years, working with Boomi for 10 years. So we are now a platinum partner with Boomi, and what we do is everything with data when it comes to data transformation, mastering data, data management, data integration, data intelligence, data analytics, data visualization. And we work with best of breed partners, of course, Boomi being our number one partner that we work with, and we do the majority of our revenue for consulting with Boomi actually.

John Furrier

>> And you guys are hosting the party tonight.

Ken Schmitt

>> We are. It's our second year. So last year, we did Dallas Cowboys Stadium. So we had to do it big, being out of Texas, right?

John Furrier

>> Yeah.

Ken Schmitt

>> So we did the stadium, we had our signage everywhere, we had a band and we had huge screens on the stadium. And this year, we're doing the museum, so instead of screens, we're going to have banners, a little bit different with the architecture and everything. But yeah, we like to do the party. That's the way we like to do it.

John Furrier

>> Yeah. It's a good vibe. I really appreciate that. But you're also in the hottest area. I mean, if you go back, when we started theCUBE 17 years ago, it was a database, data center business and the cloud came on the scene, and data management was like, it was plumbing and then the analytics wave came in.

Ken Schmitt

>> Sure.

John Furrier

>> When big data started to come into the scene, analytics, you saw core competencies there. But now you got that analytics culture, and there's a lot of businesses like Procter & Gamble Consumer, you got energy companies that you talk to, but analytics is converging with this gen AI world, and it's moving up the stack. It's hitting the C-suite, so a lot of this deep tech, databases, cloud scale, pipelining data. And the systems, as Steve Lucas pointed out in his keynote, like ERP systems, weren't built for the kind of interaction and velocity.

Ken Schmitt

>> Yeah, which is where things evolve from, right?

John Furrier

>> And this is the challenge, so okay, the people who figure this out really get a transformational edge.

Ken Schmitt

>> Right.

John Furrier

>> Can you explain how you see this playing out and how your experiences are with your customers? How are they framing it? How are they attacking this opportunity, and what are some of the easy ways to get into this?

Ken Schmitt

>> Well, the evolution we've seen has been multifold. So you've had data being looked at as part of what IT did, and they managed, and it was a nice to have type of thing, and then you had little silos in IT that did it, but they really didn't have a lot of operational visibility. They were working in silos. And then what you've seen is businesses have gravitated towards bringing data and the people that manage data within IT to the forefront of their business, and so you start seeing new personas like directors of data management, data management officers, those type of things, even C-suite type of titles for data. And now, data's being looked at as a key part of how companies do their business on a daily basis. And so we work with solutions where we build out dashboards, they've got real-time analytics, using Boomi for real-time integration, and they're basically managing their day-to-day operations through all this. And now IT in that area has taken a leadership, a strategic role, which they haven't had, a CDAT, for a long time. So we're starting to see that as an evolution, and then now of course with AI at the forefront in terms of, okay, well, how do we do that now? Now we've been doing all this data stuff for the last few years. Now there's the AI part to tackle. Well, the data part of it really lends itself to making that AI challenge a reality, right?

John Furrier

>> And the data is the key. It's funny, the old days was run the business, grow the business, IT was involved, then it became just run things, then cloud came in. And you're right, it pivoted to, okay, now we got multiple data roles, but what's interesting is, as you said, is the C-suite is getting involved, and specifically the line of business managers are coming in. So what's happening is that it used to be, "Hey, can IT, can you help me?" Now it's, no, no, no. We are collaborating, so they're now more domain specific coming into IT. So IT is coming in, my friend calls this role the super CIO, where you got to bridge an actively engaged line of business or C-suite stakeholders-

Ken Schmitt

>> And that's not every CIO, because traditionally, I mean, back in the early part of the 2000s, CIOs had a seat at the table, and they were part of the table. Generally, they were underneath the CEO, but then you had the crisis in the early 2000s and all the implosions there, which we were right in the middle of the dot com stuff with another firm, and they suddenly started putting the CIOs and the IT guys under HR or under a CFO. So you saw a lot of CIOs actually came from accounting, and now they're being forced, if you think about it. Guys who are accountants and IT, two most reclusive people, personas, are now having to face the business and help them with those decisions. It's not going to be a fit for everybody, but they're being forced into that.

John Furrier

>> And I think it's good to unshackle. In fact, I've seen that happen at scale. Also, CFOs that are realizing that I can't be a CFO. I got to be operational, so this is all going on. So I want you to share what you guys are doing, because I think you guys have an interesting approach, the readiness score assessment, you've got a technique. Because a lot of people are trying to figure out, "Okay, I got a lot of stuff, got a lot of legacy, but also with Boomi integration, I can automate and integrate," but now they've got to build capability. So with GenAI, the AI builders aren't just developers or IT. They're business analytics trained data people.

Ken Schmitt

>> Right, which means it'll proliferate and you'll have more people using it, and then you're going to have to have more governance and all that. But like you said, it's all up to data right now. And so the blockers that Steve Lucas and everybody talks about at Boomi are the same ones that we see and that's there's silos of data, there's fragmented data, there's bad quality of data, there's bad context in data, and our job as a consulting company is, yes, we'll build agents and those things because we need to, but we've got to focus on data, and we've got to focus on getting companies to have harmonized, curated, golden standard of data that they can trust, that they can go execute a heavy data project or an AI project and be successful. So that's really where we focus on. And because AI is new and you still have a lot of skeptics out there, you've got to establish early wins, and if you fall flat on your face because you have bad data, you can jeopardize the momentum, the success of any type of AI initiative you're going to have, so it makes it even more important to have your data locked down. So what we've done is we've put together a special assessment that is an augmentation, a part of what we've been doing for 22 years, which is around what we call Techstone MD, which is our health check. And so we've been doing that for Oracle partners before Boomi came around. We did it for IBM, now we're doing it for Boomi, and it's for those customers that we come in and we do an assessment on what they've built out. We have an infrastructure architect and we have an integration architect, and we do a fit gap analysis and we provide recommendations and we tweak things for performance, and we get them to a point to where they've got a solid foundation and they go out and scale. Well, our AI readiness, data readiness assessment is a part of that, and rather than have an integration architect, we have a data architect or data engineer that performs a two-week fixed fee assessment, and in that two weeks the company gets, the client gets a ton of ROI, just like they do with our Techstone MD. And what we do is our architect will go out there and spend time with them, first with their stakeholders that they identify, and identify their AI objectives and really understand what their success metrics are going to be. Then we go and we do an inventory on their source systems and we look at their data flows, and then we start documenting their patterns, start figuring those things out too. This is all within the first week that we're out there.

John Furrier

>> First week.

Ken Schmitt

>> First week.

John Furrier

>> Not the first year.

Ken Schmitt

>> No, the first-

John Furrier

>> We're talking about weeks here.

Ken Schmitt

>> Two weeks.

John Furrier

>> Okay.

Ken Schmitt

>> Capped. One of the things we do is we do a source to target traceability summary. That's one of the deliverables we bring. We evaluate data quality, we assess governance, and then we do a scorecard. So we actually look at the data set that they provided us, and we give it a score. We have all sorts of metrics that we go through. They take that score that they get, and they can either use it for themselves internally to make decisions or they could take that to the executive team to justify why they're doing an AI project and need this data part of it, or where the risks are going to be from where they're at with their data at that point. We give them recommendations on how they can improve the data, we give them a high level roadmap, we provide that gap analysis, and then we do an executive summary.

John Furrier

>> Okay. So I got to play skeptic for a second.

Ken Schmitt

>> Yeah.

John Furrier

>> So I have personal experience and I have friends that tell me this, so I'm not asking for a friend, but reaction could be, "Oh, here comes another data consultant. They're going to gouge me, take my wallet. It's going to be two years." I mean, I'm over the top to illustrate the point. You talk about speed now. You did one week. This is not like a data migration, so share, one, why the speed is so fast, and then two, what's the pain point? If someone's watching, what's the smoke signals, what's their pain? Describe their environment as a fit for you. So why so fast and the methodology, and then who's the target? Explain what their environment is. Is it on fire? Is it a little bit of smoke?

Ken Schmitt

>> It could be all that. Well, and the reason why it's two weeks is because we're only going to be looking at a certain data set. We're not going to boil the ocean, right? And so we're going to ask them to provide that to us. We'll give them some examples, but we just have a really good process and methodology that we can go through and be able to execute these deliverables, and provide a company with this amount of information that allows them to at least begin to get a grasp on where they're at. They're going to understand how far they are away from having curated harmonized data, they're going to have a score that pertains to that. They're going to have an understanding of what some high level use cases can be. That's the other thing that we provide when we have these discussions and facilitations, because we find that to be one of the greatest needs that customers have, is they don't have use cases.

John Furrier

>> You got to know what you're ready for. I mean, readiness is like, hey, what am I playing? Football? Baseball? What's the-

Ken Schmitt

>> Exactly.

John Furrier

>> So my second question is, is it workflow specific or is it workflows around the domain of the data state?

Ken Schmitt

>> Domain of the data state, and then we'll also help them understand the importance of having standard data models and breaking things out like that. The data scientists, the data architects, the engineers that we have are trained in this methodology to be able to pull that data out. Now, we may have customers where we're not going to be able to get as much information from, but we're going to do our best to facilitate that-

John Furrier

>> Well, you can certainly identify the gaps.

Ken Schmitt

>> Well, we'll be able to identify the gaps. So we'll give them a score, and we'll uncover some use cases.

John Furrier

>> Ken, so what happens next? So I love the way you guys take that approach, I love the framework. What happens next and is there any augmentation with agents? Are you eating your own dog food or drinking your own champagne? Client zero, whatever they call it. I mean, there's a lot of tooling that's probably going to feed into it, because you're on the front end.

Ken Schmitt

>> Right, and so we're seeing the pain, we're getting it from the business, operations, we're getting it from IT. We're seeing their actual data, how bad it is. The recommendations are all around Boomi and other solutions that we work with to say, "Hey, these are recommendations on software that you may want to consider. These are recommendations on best practices for data that you may want to consider." And once we're out there for two weeks and they meet our guys, they generally are going to start building a nice relationship and we'll have some credibility that we'll gain and earn, that they'll probably ask us about different things that we could do from a project perspective, or ask us to evaluate, "Would you do this or would you prioritize that?" And so it can go in different ways, but generally, it's recommendations on solutions and tools.

John Furrier

>> All right, let's get into the Boomi integration. I was talking to ... This happens every year when I come to Boomi World. At the bar or in the hallway, I meet some customers, and I always ask, "Hey, how do you use Boomi?" And the theme is always this is really good at integration, but one specific use case I want to get your reaction to is, and it fits two kind of scenarios. "Oh, my company's buying all these companies. We're rolling up something, we made an acquisition, I got five different IT department data schemas, all kinds of data state issues," or, "Hey, I got divisions with silos." And I'm like, Boomi makes it really ... A week, it gets integrated. So the scale and scope of their capabilities is fast, and it's getting faster.

Ken Schmitt

>> And it's getting faster, especially with Boomi Companion.

John Furrier

>> So talk about how this is working with the work you're doing. How does that feed into the customer when Boomi walks in the door?

Ken Schmitt

>> Well, it's-

John Furrier

>> What are you tying with Boomi in the front end?

Ken Schmitt

>> It varies. So the relationship we have with Boomi is we're very sales oriented. We've got a really strong delivery team, but as a partner, what we've always been a little bit different in is that we have very much a sales approach, meaning we understand from a solution set where the fit's going to be for clients, so not only can we execute to deliver, but we can understand the company's problems, their use cases, and then from all of our experience, we could figure out what kind of ways to solve those, right? And so our job is to figure those out, prioritize those, and then help paint a picture of how a company can get there. What we see with Boomi is Boomi's always been the product, and the reason why we chose Boomi 10 years ago, that is truly an iPaaS solution, compared to what we had come from with hub and spoke enterprise service buses, that you can do things quicker, better, easier, more intuitively, but with a robust solution and robust framework that provides enterprise solutions, enterprise needs and scalability. For mergers and acquisitions, for instance, one of our clients in Houston, which was our first one, one of our first clients, they buy companies every quarter. They have 250 companies now, operating companies, and so the main thing they need to do-

John Furrier

>> That's a super CIO.

Ken Schmitt

>> Super CIO. Same guy too.

John Furrier

>> Really? He's the layer.

Ken Schmitt

>> Yes. And so it's mastering that data, right? That was the first thing we had to do is master just employee data. Then it became, oh, all these companies, they acquire have different banks. Let's master treasury data. Let's integrate all of this as well too, these systems. So it was getting their book of accounts, charter of accounts in as quickly as possible so you could start doing business, intercompany type business. Boomi enabled that. Now with Boomi, Claude, with the AI piece, you're going to be able to do a project and integration that maybe took two to four weeks, you could do it in now two days.

John Furrier

>> Well, again, this is why I like the data activation, although it's kind of in the weeds, very specific to Boomi. I think it's going to be more an economic value, and what's interesting now in the projects, these business transformation projects, it's not an IT project anymore.

Ken Schmitt

>> No, it's changed.

John Furrier

>> There's revenue on the line.

Ken Schmitt

>> Totally.

John Furrier

>> Speed is there, I love the readiness score. I guess my final question for you is, what are some of the cool AI value creation extraction things you've seen coming out of some of your work as you look downstream on the outcome? Because people are just resetting their mindset and say," I'll just work backwards from the outcome, drive more revenue in this workflow, work backwards and knock it down that way, not just cost takeout."

Ken Schmitt

>> Right. Well, we've got one I was just in a meeting with, with a client that we've had, I think they were our second or third Boomi client 10 years ago called Select Water, and Select is an oil field company, does a lot in water tank truck type of services for the oil field. They've had Boomi for 10 years, we introduced Boomi to them, and we're looking at doing things around day sales outstanding and minimizing those with their treasury group. So it's a Boomi software solution, but the audience is the treasury department, the VP of Treasury, and he's looking at, "Okay, well, how can I do problem resolution with receivables and things like that?" So Boomi's building agents, we're doing an AI workshop with them. At the same time, we're mastering data, customer data for them with Boomi's Data Hub and parallel, so it all fits together really well, and that's a really good ... Things around finance and the CFO's office have always been, I think, a good fit for what we do, and then especially with the AI piece.

John Furrier

>> Ken, I really appreciate you coming on and congratulations. It's a dynamic market. The velocity and the speed is so fast. I got to bring up the rolling stone, collects no dust, tech stone.

Ken Schmitt

>> Appreciate that.

John Furrier

>> You're moving so fast. I mean, just comment on a personal note the velocity of this market right now. It's so fast. How would you talk to that?

Ken Schmitt

>> Well, I mean-

John Furrier

>> The rolling tech stone.

Ken Schmitt

>> I've been doing this for almost 30 years. When I got into it, it was moving fast, and then it kind of stayed the same for a long time. But in the last three years, we've seen more changes, more growth, more velocity, as you've said, than we did in the 27 years before it.

John Furrier

>> Well, congratulations. It's going to be super exciting. Well, the technology has gotten better so that's going to help with the tooling for the folks working on it.

Ken Schmitt

>> They'll never retire.

John Furrier

>> Never retire. The data tsunami is still coming. It's been coming for over 15 years. Thanks for coming on. I'm John Furrier, we're rolling along here on day two. We'll be right back with Gemma Allen here on theCUBE. We'll be right back. Thanks for watching.