Google Cloud Next 2025 | Vishal Iyengar, Deloitte Consulting LLP & Matt Rhenish, Maynd Jolly, enGen

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Vishal Iyengar

Principal

Deloitte Consulting LLP

Matt Rhenish

SVP & COO Health Plan Operations

enGen

Maynd Jolly

CFO & Commercialization SVP, Client Executive, Growth and Partnerships

enGen

play_circle_outline enGen, part of Highmark Health, connects members, providers, and patients in healthcare ecosystem

play_circle_outline Enhancing Patient Care: AI in Healthcare and Selecting Tools for Data Security and Privacy

play_circle_outline Claims Examiner automates decision-making for manual claims processing in at-scale health plans

play_circle_outline Success of AI adoption depends on building with users, not just implementing for them

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Vishal Iyengar, Deloitte Consulting LLP & Matt Rhenish, Maynd Jolly, enGen

Vishal Iyengar

Principal Deloitte Consulting LLP

Matt Rhenish

SVP & COO Health Plan Operations enGen

Maynd Jolly

CFO & Commercialization SVP, Client Executive, Growth and Partnerships enGen

Vishal Iyengar of Deloitte, along with Matt Rhenish and Maynd Jolly of enGen, highlights AI innovations at Google Cloud Next 2025 in Las Vegas. The discussion on the transformative role of AI in healthcare is expertly navigated by hosts from theCUBE Research, emphasizing pathways for operational excellence in the industry.

In this session, Vishal Iyengar, an executive at Deloitte, shares expertise on leveraging technology to optimize healthcare operations. Joined by enGen's Matt Rhenish and Maynd Jolly, they explore the nuances of AI integration and ... Read more

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What is enGen and what role does it play within Highmark Health? add

What factors do you consider when selecting tools to recommend to companies like enGen for optimizing processes in sensitive industries like healthcare? add

What is the significance of decision automation in processing millions of insurance claims each year? add

What approach does the healthcare industry usually take when it comes to embracing newer technology, especially AI, and what has been a key factor in the success of certain programs utilizing AI in healthcare? add

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Vishal Iyengar, Deloitte Consulting LLP & Matt Rhenish, Maynd Jolly, enGen

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Savannah Peterson

>> Good afternoon, nerd fam, and a welcome back to Fabulous Las Vegas, Nevada. We're here on the back end of day two of our three days of live coverage. My name is Savannah Peterson, super excited to be building on and continuing the conversation in this particular segment about AI and healthcare. Who better to do it than our fabulous trifecta of guests sitting next to me? Vishal, Matt, and Mayan, thank you so much for taking the time to be here, gentlemen. Really appreciate it.

>> Thanks for having us. - I know it is a busy week

Savannah Peterson

>> for you all, so this is going to be cool.

Matt Rhenish

>> I'm glad we were just catching up before we got started. Let's talk about NGiN real quick just to ground folks in the conversation. Matt, I'm going to let you start off. Tell us about y'all, what you do, and what brought you to this fabulous table.

Matt Rhenish

>> Sure. So NGiN is a part of Highmark Health, which is a payer and provider and technology company. We have all of the technology and the operations for Highmark Health, which serves millions of blue plan members, millions of provider patients, frankly, and is really the connection point between members getting care and patients and providers on the other side of that.

Savannah Peterson

>> Which is a really critical bridge.

Matt Rhenish

>> Yeah, it's the reason people need healthcare, is they need us to be there at that connection when they most need us to support them through the care that they're on, so they don't have to worry about things like claims, or is my coverage accepted here? Any of those sorts of things. Yeah.

Savannah Peterson

>> Absolutely. So Vishal, you mentioned that you've been working with these folks for about three years.

>> Yeah. - And I'm curious, when a company like NGiN comes

Savannah Peterson

>> to you or starts working with you to optimize processes,

Vishal Iyengar

>> healthcare is a very sensitive topic, a lot of data that's really sensitive. I mean, those claims themselves, if something happens and privacy is breached, that's an extremely big deal. So how do you select which tools to recommend to them so that they can build with confidence and do their jobs?

Vishal Iyengar

>> Yeah, great question. I think the first thing that we focus on is, what is the business objective that they're looking to achieve. We start there, because we want to make sure that we have a clear understanding of what success looks like. The second thing we do is, as you described, data security, data privacy is incredibly important. So we have to make sure that while we have the objective in mind, we're picking the tools that'll keep the integrity of the solution, but also the privacy of our members and our providers, and all the stakeholders involved in healthcare keep that protected. And then last but not least, we need to look at what is the value, the fastest speed to market, something that Google provides in spades, the ability to actually bring in disparate solutions all in one place, get to market as soon as possible, right? And that's really what's important for NGIN and for Highmark.

Savannah Peterson

>> Yeah, you're really balancing that time, confidence, and value triangle. Very much so, especially on the success front. Mayan, I'm curious, when you're strategizing here and coming to Vishal to say, "Hey, these are the outcomes that we need," what does a W look like in your game? What are those metrics for success?

Maynd Jolly

>> First of all, thinking about health plan as our customer, it's our job to make the most efficient. That's number one factor, because they're processing billions of dollars in claims, and we need to get the cost of efficiency to the lowest of the cent. That's number one. Second is, how do I make an experience for a member and provider excellent and let the provider perform at the top of the credentials? So if it meets those criteria, then it's North Star for us. Because I can solve the problem not just for health plan, but for provider and for members at the end. And I'm ready to invest top capital dollars into it, because it not only helps us in bringing the best technology, but scale the solution and then go to market. That's how I think about it.

Savannah Peterson

>> Yeah. No, and I mean, those are important pieces, and probably though in this case, relatively measurable. So at least you know if you're doing a good job.

Matt Rhenish

>> The kind of solution we built with Deloitte and Google and other parts of our enterprise, we can tell that we're moving through and getting answers back faster to members, getting answers back faster to providers, so that they can be satisfied and then focus on what's really important, which is their care and caring for their patients.

>> Yeah, absolutely. Talk to me a bit about Claims Examiner,

Savannah Peterson

>> what that is and how that helps you drive these solutions.

Matt Rhenish

>> So any at-scale health plan pays hundreds of millions of claims a year. And there's this percentage and even a-

>> It's an incredible volume.

Savannah Peterson

>> Incredible. - Truly incredible volume.

Matt Rhenish

>> You think about it, the average person probably has 10

Savannah Peterson

>> to 15 claims a year.

Savannah Peterson

>> And even an average healthy person, let alone someone

Matt Rhenish

>> who might be in with something more chronic.

Matt Rhenish

>> And a small portion of those sometimes have to be held and manually processed. There's any number of reasons. The provider name is a mismatch, or I have a friend, he's the third and his dad is the fourth, right? And so, it's like, "Who is this claimed for? " And when you do that, it's a tiny percentage on hundreds, still millions of claims that we're holding and we're working through manually. And so, this solution provides decision automation really for the people that do these manual claims, so that they can tell, "Yes, approve and move on. Approve and move on. Hold this, look in more detail. " And it then allows them to go on and do more important work for our members and for our customers.

Vishal Iyengar

>> Just to add to that, I think the intent is to remove the friction that exists in the healthcare ecosystem, make the decisions faster so that you get the members and the providers the answers they're looking for and some peace of mind. Nobody wants a surprise bill. Nobody wants something that they were not expecting. And so, this really removes the friction. And they're sort of at the leading edge of that change, of trying to change the experience for members, providers, all of the stakeholders within the healthcare ecosystem.

Savannah Peterson

>> I think that's a really good point. I say this lovingly, we've all potentially had an issue at some point with confusion or rejection of a claim or an unexplained EOB that comes spitting out of some system based on something that's data that might've gotten a little mushy. And so, I'm curious, what level of... Do you have any numbers that you can share with us in terms of-

Matt Rhenish

>> Yeah.

Matt Rhenish

>> Yeah, so please. - So we are right now using this

Savannah Peterson

>> solution on about two million claims. And it's still fairly new. This isn't like we've been doing this for years and years with this solution, it's in the last three to four months. And we continue to grow and build that base. And we even talked this morning about the next horizon of use cases, that we can go from two million to five million to seven million.

Vishal Iyengar

>> To put that in perspective, that's about 200, 000 members in a given year that you're able to get answers faster, that you're able to give them peace of mind so they can focus on care.

Maynd Jolly

>> Let me add from an operation standpoint, as Matt are in massive operations, a person who's managing the claim might spend, I don't know, 20 minutes on just looking at that claim and working through it. This Claim Examiner can do it in a few seconds. So I think the experience of the user who's using the platform changes differently as well. And it allows us to not only process the claim more accurately, but make the life of the user who's working in the job day to day much more easier.

Savannah Peterson

>> And free up that cognitive load for other activities.

Matt Rhenish

>> Yeah, exactly. - Not staring at paperwork.

Matt Rhenish

>> That's right. - Which is nobody's favorite activity.

Savannah Peterson

>> If it is, I'd like to meet that person

Savannah Peterson

>> and show them a few other hobbies. I would like to open their mind, perhaps to the great, wide wild world outside and around us. I think that's really, it's interesting and it's powerful, because the healthcare system is such an emotional arena. This is not an industry of... It's not passive. Typically, if you're dealing with your healthcare provider or you're dealing with your insurance company, something's going on.

Matt Rhenish

>> Yeah. - At least at velocity.

Savannah Peterson

>> You mentioned those use cases, Matt, and I'm curious to drill down there a little bit. How do you identify the best use cases for this rollout and scale it up?

>> So for us, it's a combination of, we need

Matt Rhenish

>> to make sure it's something that's not only at scale, but also as you said, measurable, that we can add outcomes too on the back end. It can't be a one-off, kind of interesting science project. That does not work. So we need to be able to show and prove that it's bringing value. We need to make sure with our partners, Deloitte, Google, others, it is market-leading, and this is putting us in a position that continues to reduce that friction and puts us in a better spot than our competitors. And I think lastly is really something that brings together all the rest of our organization. Analytics teams, IT teams, my operational teams, all those people working together makes it happen. Because at the end, if someone is like, "Well, we can use AI at scale in boring old operations," and then those kinds of stories are how you build an AI culture in an organization and continue to find new use cases.

Savannah Peterson

>> I think that's a really good point you just brought up. We can build everything we want to build, but if the humans in this world aren't using them and optimizing them, it really doesn't matter. And I can imagine, Vishal, I'm curious to get your take on this, and I'd love to hear what either of you have to say. In terms of the cultural adoption in this industry specifically, how are you coaching customers like NGiN to integrate that in a way that is approachable and empowering, versus scary and annoying?

Vishal Iyengar

>> Well, I would agree that I think the healthcare industry always takes a cautious approach to sort of embracing newer technology, leading the technology, technology in general. But one of the things that has been the success of this program, and I can say that knowing that this is absolutely true, is from day one we actually brought the entire set of people that were going to use the solution, design and use the solution, to come and say, "Here's why this AI is going to be helpful. " Sometimes there's this concern that AI might actually not give me the answer that I'm looking for, and therefore I'm going to be held responsible for that. So there's a little bit of the bias towards not using it because of what it may impact or how it may impact you. The other side of it is there's just the skepticism that a machine can actually give you information and decisions better than what you've been doing for the last two or three decades, because a lot of these folks have been doing it. And so, it's very important that you don't do the solution to them, you do the solution with them. And I will say this, I've said this on multiple forums, that NGiN and Highmark have been very embracing of the technology, and that has been a huge part of the success. And it is why I think that with the portfolio that the two of them have sort of outlined, I think there's more successes in the future for them to take to market.

Savannah Peterson

>> Mayan, would you agree? - Yeah, I agree.

Maynd Jolly

>> I think one thing to add to Vishal's point, if you think about insurance companies, these businesses are built over the last 50 to 100 years. They have some very old technology, there's some new technology, and there is a modern tech stack sitting in GCP. So we have the mix of all of that. So we need to figure out, "Okay, can I take my enterprise data in GCP? " We did that. "But my platform still runs on an older technology, how do I create an integration layer which allows me to implement AI, but at the same time do my ops? " It becomes tricky. And that's where Deloitte or Google, they can come in and they can help us out, how to solve that last mile connectivity integration, the last tiny bit of problem which makes it happen. And that's what I love about the partnership, which we came together with Deloitte and Google and Highmark and NGiN together, and it really blossomed into this big product. I think I love the product. It's going to be a market-leading product.

Savannah Peterson

>> It sounds like it already is.

Matt Rhenish

>> It's great. Yeah. - It's great.

Matt Rhenish

>> It has been great to see the adoption of all the teams,

Maynd Jolly

>> kind of day-to-day teams, especially non-tech folks that are now kind of bought in and can evangelize.

Savannah Peterson

>> That's really kind of what I was driving at a little bit, because us nerds are kind of always a little gung-ho about trying whatever is next. But I do think especially, where as you are integrating, I mean it's a revolutionary technology moment that we're all living in, even as deep nerds, let alone when you're rolling it out to folks who maybe don't read about this stuff in their spare time. I think it's really powerful. And I love what you said, Vishal, I'm going to appropriate that from you moving forward, because I love that it's not about teaching, it's about building with them, not just implementing and saying, "Hey, go use this new thing. It's great, we promise. Well, why? My brain is great, and it has been working for 30 years. " I think it makes a lot of sense. So outside of scaling out this rollout, what else are you all working on now? What are you going to tackle next?

Matt Rhenish

>> Yeah, I can just say in operations, and my end hit on it, there's lots of complicated processes with lots of friction in them. And so, now it is, continue to hunt for ways we can take that friction out of the system. Whether it's EOBs, providers that want to ask us questions that don't understand how a claim is paid, all of those friction points in those old processes are an opportunity to bring AI in and help with decision-making and that kind of thing. So it's exciting.

Maynd Jolly

>> I think what I love about our role is that we see the messy part of the business. So there's a lot of mess. Now we need to decide where to apply the AI and the new tools which are coming along. I think Matt said it nicely, there's so much challenges in just talking to a provider. They have a thousand inquiries coming in and the inquiries just keeps on going up. Shall we tackle that or shall we talk to a member who does not understand their benefits? Or shall we talk to an employer group who wants to explain the benefits to their own employees better? I think the way that we took it, the lens is that, which challenge we take, but it hits everyone, a member, a provider, and a health plan. If it fits all of them, we want to take on that challenge. So that's how we look at the filter when choosing all the next challenges we are taking on in the next few months.

Vishal Iyengar

>> Just to add, the criteria, the three tenets, make sure that you know what the outcome it is, what outcome and objective you're going after. Second, bring or integrate the teams to bring everybody together to solve. And then three, be willing to sign up for business outcomes. If those three things fit a use case, I think that should be there and I think that has been the thought process.

Savannah Peterson

>> Yeah, I love it. All right, kind of building on that, one final question for you all, because this has been really fun and I think we should continue the conversation next year at Google Cloud Next in 2026. What do you hope to be able to say then that you can't yet say today? Mayan, I'm going to start with you and we'll work our way in this way.

>> Oh, that's a big one, a good one.

Maynd Jolly

>> So what I would love to say is that from an operation standpoint of a health plan, we have been able to put AI in every piece of operations. Not just claims, but call center, by just managing day-to-day entries, just managing day-to-day paperwork. So have I used AI technology in every aspect of operations? That'll be a big goal for me.

Savannah Peterson

>> Cool. Well, I'm going to hold you accountable for that. Can't wait to hear your .

Matt Rhenish

>> And it's recorded so you- - Exactly.

Savannah Peterson

>> It's on tape, it's in my brain. Our AI will be trained on that sentence. It's actually not false, that's a true statement, so yes. What about you, Matt?

Matt Rhenish

>> Similar for me. I would say that I want my ops teams to be able to leverage this solution and other AI solutions at every touch point that we have with a member and with a provider to provide better answers faster and a better experience to them, so that they can focus on their own health or care for their patient if they're a provider.

Savannah Peterson

>> Love that. Keeping that brain working in the right place and not distracted by-

Matt Rhenish

>> People that matter, right? It's the people that matter in the end.

>> It is the people that matter.

Savannah Peterson

>> Absolutely. All right, Vishal?

Vishal Iyengar

>> Well, on that note, just to say it, the members and providers, the portfolio of solutions and the thinking that you guys are putting into it, if we can get a member testimonial, a provider testimonial to say, "We're seeing the impact of that, we love that this is in place and we're willing to embrace it as well," because now you can come in from both sides. I think that would be a fantastic 2026 goal, I guess.

>> All right. Well, the audience heard it here first.

Vishal Iyengar

>> All right. - I'll be holding you accountable to those.

Savannah Peterson

>> Absolutely. Thank you so much.

Vishal Iyengar

>> And thank you, you three really,

Savannah Peterson

>> this has been a great conversation

Savannah Peterson

>> and thank you for the important work that you do optimizing at the end of the day, a better patient experience for all of us. So cheers to that.

Matt Rhenish

>> Thanks. - I hope y'all got as much as we got out

Savannah Peterson

>> of this fun 15 minutes of joy here on theCUBE from the show floor at Google Cloud Next in Las Vegas, Nevada. My name is Savannah Peterson. You're watching theCUBE, the leading source for enterprise tech news.