Empowering Responsible AI: Governance, Innovation, and Scaling Enterprise AI

Narrator: Welcome to Coruzant Technologies, home of the Digital Executive Podcast. Welcome to The Digital Executive. Today's guest is Pete Foley. With more than 25 years of executive and entrepreneurial experience in enterprise software and a track record of successful business exits, Pete Foley's leadership gives ModelOp customers, partners, and employees a high level of trust and confidence in the company and its future.

Prior to founding ModelOp, Pete held several chief executive roles, including CEO of RingCube Technologies, a desktop virtualization software solution provider acquired by Citrix in 2011, CEO of Port Authority Technologies, a provider of data leak protection systems from 2005 through its acquisition by Websense in 2007, and CEO of Infoblox from 2002 to 2005. In addition, Pete was the executive chairman of Graphite Systems, a low latency flash based big data appliance that was acquired by EMC, from 2012 to 2015.

Brian Thomas: Well, good afternoon, Pete. Welcome to the show.

Pete Foley: Thank you, Brian. Glad to be here.

Brian Thomas: Absolutely. I appreciate you making the time hailing out of the great windy city of Chicago today. Down here in Kansas City, we're both suffering a little bit of the cold, but we still love being in the Midwest some days, maybe not today. But, again, appreciate your time.

And, Pete, let's jump right into your first question here. With over 25 years in executive roles and multiple successful business exits, what key lessons have you learned about leading enterprise software companies?

Pete Foley: Yeah. Good question. I think, you know, for me, it's kind of wrapped into three distinct areas. I think the first thing is the people that you are involved with within those companies.

I've been, you know, very fortunate to work with core teams that have been, you know, kind of dynamic and entrepreneurial. And by building a, I think, a strong core team, you're you're able to shape a product. And, you know, for me, it's, you know, kind of if you can build that core team, create a distinctive technology, and then, you know, a lot of it's luck. Let's face it.

Right? Market timing. So it's, you know, people, technology, and market. At ModelOp, we're, you know, been, as I said, fortunate.

We've got a strong nucleus of people. They built an extremely powerful software platform. And our market timing is such as, though, we don't have control over that. I think that, you know, by focusing extremely hard on our early customers, we can start to build some indicators of a market need.

Brian Thomas: Thank you. You highlighted those three things, people, technology, marketing, but people is always foundationally. Everything we talk about in these podcasts centers around the people, and I know that's a big part of this. So I appreciate your share and really do like to hear from entrepreneurs that have done some great things over their career.

Pete, what inspired you to co found ModelOp and how does the company address the challenges enterprises face in AI governance?

Pete Foley: Well, in, you know, in my opinion, you know, we looked at AI as being kind of one of the most transformational technologies since the web. I mean, there's leadership in every single company that, you know, whether it's at the board level or at C level, they want to know, you know, how are their companies best leveraging AI. So I think, you know, a lot of folks saw this as an enormous amount of awareness of the power of AI. You look at the amount of money that's been put into innovative products, to help build these AI assets, whether it's been, you know, the kind of the big press releases around the venture money that's been thrown into this space or, you know, with the hyperscalers, the Googles, the Amazons, Microsofts.

What large software vendors, you know, Oracle, Salesforce, ServiceNow, you know, people have invested billions in dollars in trying to create these AI assets. And we kind of recognize though that, you know, within those enterprises, the eventual customers for these assets, there is an inherent understanding that there has to be not just this opportunity to take advantage of this technology, to use these assets to create, you know, distinct advantages for their companies. But it's at some level within that executive level, there's also this inherent understanding that there has to be some level of guardrails put in place. And these guardrails, this governance comes not only just from the regulatory bodies within the government and their community, but also recognized within this executive leadership, these enterprises really have to be able to enforce this AI responsibly.

And at ModelOp, you know, we really enable those companies to do it effectively. We're one of the few purpose built AI software companies. Our biggest value proposition to our customers is go ahead and we can allow you, we can enable you to make these large investments to really transform your companies using these extremely strong AI assets. And you can do it responsibly.

And so in the end, our value proposition, our challenges that we solve for our customers is how to allow them to really leverage AI at scale. And one of my investors kind of put it best when he said, look, we're more like the picks and shovels that are extremely necessary though for companies to get to that AI gold. I mean, AI without governance does not work within these organizations. AI governance is an absolute necessity for companies to be able to scale.

Brian Thomas: Thank you, Pete. I appreciate that. And the question was centered around governance. Obviously, there's some great technology.

People are making leapfrog advances, light speed advances in this space. And as you know, being in tech and myself being a CIO for many years, governance is such a big near and dear to my heart and what I do. IT governance has always been a big part, and I think we need to make sure that this is extended into this AI realm. We're seeing some questionable things happening with AI and how it's influencing social and media and all these different things.

So I appreciate your insights on this. I really do. And, Pete, being named to Inc.'s 2024 best in business list in the AI and data category is a significant achievement.

What does this recognition mean for ModelOp, and how does it reflect your company's contributions to the industry?

Pete Foley: Thank you for that question because, you know, obviously, we're very proud of this award. I mean, one of the unique things that, again, we pride ourselves on is that we were the only AI governance software vendor selected on this Inc. Best in business list. And we really look at, you know, as you know, that award is all about, you know, contributions that companies have made, not only on the industries, but on the society at large.

So kind of back to your comment earlier about responsible AI. And we are, you know, at ModelOp extremely proud because, again, not only the celebration of that contribution, but the other types of companies that were looked at, companies like IBM, like SAS, And, you know, we had an opportunity to be chosen over those large competitors. In addition to that, it's kind of indicative of the fact that we have kind of emerged this market leader for AI software governance. We're recognized by Gartner, other analysts kind of being a leader in this space.

But, you know, most importantly for me and for the company is our partnership with our customers. So, you know, leading Fortune one hundred companies, enterprise global companies like Prudential, Procter & Gamble, Bristol Myers, Fidelity, again, kind of going back to our value proposition, we've seen them being able to leverage AI at scale beyond what their competitors can do. And that exponential ability to be able to take advantage of this move into, you know, the AI technology allowed them to be able to scale their AI assets is a big reason why we're this market leader. The second piece of that too is if we just raised a Series B.

And as you know, it's an extremely difficult venture environment right now, really particularly in the business to business software. But we were fortunate to partner with a local Midwest based firm, Baird Capital. It allowed us to kind of invest, continue to invest in that market leadership. The other kind of fallout from or result of building a product and building a company that's been recognized is our ability to continue invest in our product.

We just finished our third generation of our software. It's really been the result of those types of customers that I mentioned earlier, that blue chip customer list that has really provided input into our successive releases of our product. We're now on our version 3.3. And the unique thing about it is this, is you build any type of business to business software for the enterprise, understanding the environments within those large enterprises.

Being able to scale to have an enterprise class product for us is something, again, we're very proud of. We're agnostic to all AI and analytic tools. We allow our customers to really kind of answer big AI accountability questions. How is that AI being used in my organization?

What are the risks? And just as importantly, what is the return that we're getting for that?

Brian Thomas: Thank you. You've highlighted some great things there. And what I really, I guess, resonate with is you've built such trust within the industry, but also with your customers, and they trust you to provide that service at a very high level and high quality. But also you're reinvesting your margins.

You're reinvesting into r and d, which I think is really important. And that's helps hit that list of Inc's best in business for AI and data, the data category. So I appreciate that. And, Pete, with the increasing number of AI related regulations, how does ModelOp assist enterprises in ensuring compliance while fostering innovation?

Pete Foley: Yeah, I think that's probably one of the biggest challenges is the ability to provide an AI governance solution or any governance solution, right, extends across all technology without throttling innovation. I think a couple of things that we do is answering that challenge is, number one, as I mentioned earlier, we're extremely comprehensive. So meaning we support all AI. In today's world, GenAI has certainly, you know, been the most talked about, but there's been a number of analytic tools that have been around for a long time.

So there's a number of different AI or analytic tools that every enterprise needs to be able to support. And ModelOp supports every single GenAI, every single vendor, every single embedded type of model, every type of analytic. Again, extremely comprehensive support for those tools. I'll give you just an example.

One of our financial services customers has over 32 different model development technologies, meaning those AI assets are being developed by 32 different tool sets. So that agnostic approach is an extremely strong differentiator for us. We're very much focused around life cycle management, right? Kind of that cradle to grave meaning, you know, looking at the use case ideation first within our governance platform and then all the way through the intake of those models, and through that full life cycle of a model and against its use case.

Provide a lot of out of the box templates for external compliance workflows. Couple of examples of that for financial services customers, we provide out of the box templates for SR 11-7 or NIST. And then also for all enterprises, there's new compliance requirements. Biggest one probably has been most in the news is the new EU AI Act.

We provide templates for that as well so we can get customers started quickly, you know, start to see value very quickly, allow them again to start leveraging those AI assets quickly as well. We talk a lot about getting started. How do you get started, right? Because you've got this kind of onslaught, this extreme push, I think, from the business, the department levels, and the corporate level that says, why aren't we leveraging more AI assets?

It is the gen AI is extremely early. There's just been a tremendous amount of hype. It really is just starting as a market. But the demand for use cases for GenAI within these enterprises is extremely strong.

So we work with our customers on what we call a minimal viable governance, meaning it's just the right level of governance. Start with AI portfolio management. Understand what assets you have. What are the AI assets that are complete?

I mentioned earlier, whether it's a gen AI, a vendor supported model or something that's embedded like a ChatGPT, because governance can feel overwhelming. And typically with our customers, we can get them up and running in ninety days. And that's extremely valuable for organizations that want to show value right away. Right?

You want to be able to invest. You want to not throttle innovation, provide those different departments with a value that, look, we can now start to take advantage of these AI assets. Pointing to us as a thought leader is extremely important for our champions within those enterprises. We're all about using our customers today to drive thought leadership, bringing AI governance leaders together.

We do an annual AI governance summit. We have over 700 people that attended this past fall, folks like FINRA, Prudential. We had California senator Scott Wiener. They were all speakers.

So there's this community, I think, that's being formed that understands the value and how important AI governance is in addition to obviously that innovation that we all are aware of and this, tremendous ability to use AI to drive companies forward.

Brian Thomas: Thank you, Pete. I appreciate that. A lot to impact there, but I know that you and your company are doing some great things around helping companies to ensure compliance in this AI related space that we're getting into these days. You know, there's challenges all across the board.

I know, for example, Microsoft launched their copilot, yet there was a lot of delay and, I don't know, probably some contention, some scrutiny around releasing that into the government sector of their Microsoft product platform. So lots going on across the industry. So I appreciate your insights today. Pete, it was such a pleasure having you on, and I look forward to speaking with you real soon.

Pete Foley: Alright, Brian. Appreciate it. And, I thank you again for the time today. Bye for now.