Saurabh Gupta [00:21]
Hi, everyone. Welcome to today’s episode of HFS Unfiltered. I have the immense pleasure of having Hiral, who’s firstly my friend, but secondly, he’s also the CEO of Veltris, a really up-and-coming digital product engineering company built around verticalized AI. So, Hiral, welcome to the show.
Hiral Chandrana [00:47]
Thank you, Saurabh, and always a pleasure to speak to a fellow Chicagoan, sir.
Saurabh Gupta [00:54]
So, Hiral, let me jump into this. You and I have had several conversations around Veltris, and you position it as a digital product engineering company, and I really like your verticalized AI approach. But if you go under this positioning statement and look at it very practically — how does this vertical AI approach change the way that you think through the design, pricing, and solutioning of your services compared to a traditional services firm?
Hiral Chandrana [01:34]
So, as you know, it seems like this whole AI-first vocabulary is being abused, and there’s obviously a lot of agents and a lot of hype. Having said that, we’ve taken a slightly nuanced approach, like you mentioned, on the vertical AI side, so let me maybe take a step back. The whole cycle — whether it’s design, just even thinking about the blueprint of design, all the way to solutioning slash pricing, and then, of course, what’s most important, the delivery — has to change in this kind of new world of AI-native or AI-first. The interesting thing though is that what was not possible in the past is happening in seconds or minutes. So when we look at the traditional model of assessments and analysis, etc., there’s nothing wrong with that, but what we’re doing differently now is moving to a quick diagnostic and then turning alignment to action. It’s really cutting down the entire initial part of the scoping and the solutioning. But you and me have been in the industry for 2.5 decades, and we’ve been hearing about business outcomes and customer-aligned SLAs, etc. for a while. What’s different this time, I would say, is we’ve used a much simpler framework called build, modernize and monetize. It creates a self-funding cycle, whether it’s product development, engineering, or even delivery, and bringing in those industry-specific workflows and industry-specific use cases — that’s really what’s changing the pricing model. And then the most important thing is that you have to finally deliver this with a combination of domain and product squads, as we call it. So it’s no longer just domain depth; you need to have a product mindset plus the industry use-case mindset, bringing that together, of course, with technology and architecture. So, Saurabh, there’s a lot changing in the world, as you rightly mentioned, in the way that we buy and sell services, but I think as this world changes, all of us also have to change.
Saurabh Gupta [04:22]
You’ve led large P&Ls at very large companies like Wipro. You were the CEO of Mastech before this. How has your leadership playbook changed at Veltris, looking at this AI era that we are entering into? What are the things that you had to unlearn, or are there things that you had to learn? How are you changing as a leader?
Hiral Chandrana [04:22]
There are some things that don’t change, right? Customer intimacy, customer intelligence, being close to the customer, understanding their business and their processes — that’s something that goes forever, irrespective of where you are. But there’s a lot to unlearn, and I was fortunate to be part of some large organizations, but also some small to mid-size organizations. From an unlearning perspective, we all talk about leading by example, but one of the biggest things you have to continue to unlearn is how that leading by example is amplified in smaller but subtle and still impactful things. It could be leading by example to win a deal, to do a presentation, or, interestingly, even on culture. It’s so important in the AI-native organizations from a culture and work-life balance perspective. Interestingly, last week we had an all-hands meeting for the entire company, and our entire presentation and interaction was based on Gen Z lingo. Everyone from my leadership team, or ELT, was in Gen Z lingo. So that’s an example of not just the technical side of the AI side, but also the cultural side.
Saurabh Gupta [06:12]
So, Hiral, we should have another session just to teach me the Gen Z lingo. But another very interesting aspect of Veltris is that you are a PE-backed firm, right? You have multiple PEs that back you. And you and I have talked about an aggressive M&A approach as you move forward. What’s your investment thesis? What are you trying to acquire? And then also, as we’ve always seen, how do you avoid becoming just a stitched-together IT services company which has 5 brands, but they don’t talk to each other?
Hiral Chandrana [06:52]
Yeah, M&A is not easy, as you know. There have been some successful M&As, but there’s a lot of failures. So it’s really important to have a sharp, crisp strategy and then, of course, execute the hell out of it. Having said that, there are some foundational expectations from our M&A thesis, which are more table stakes — financial health and growth mindset, the right team, high-potential areas, etc. Those go without saying, but what we’re looking at, as Veltris is a vertical AI solutions orchestrator, is companies which can accelerate AI readiness and AI adoption. And I love the aspect of being part of a private equity ecosystem because there’s a lot sharper value-creation focus, both for the customer and for the organization. When it comes to AI readiness, it’s about data modernization, it’s about cyber readiness, but in the context of verticals or micro-industries. And this is interesting, because even firms like Databricks and Snowflake are building their data intelligence platforms with industry-specific use cases. When it comes to AI adoption, we use the word monetize quite a bit, because there are a lot of investments that have gone into products or platforms, and the ROI from that is still questionable. So the way we can unlock that is to really look at micro-industry-specific workflows, automate and embed intelligence into those workflows with AI, but also create new revenue streams, create new products to grab market share and truly monetize and get ROI from those investments. So those would be some of the examples of firms and assets that we’re looking for.
Saurabh Gupta [08:56]
Yeah, I think the aspect of AI readiness is very, very important here. In fact, our research indicates that for every $1 companies spend on AI, they need to spend probably $2.5 to $3 on data to get that ready, because otherwise we’ll have another shining tool which doesn’t really get to the ambitions that we all have with it. But the other point I wanted to pick on was this whole micro-industry aspect of the Veltris go-to-market strategy. You recently acquired this company, BPK Technologies, and so clearly you are doubling down on healthcare, but also very interestingly on micro-segments within healthcare like dental practice, with this acquisition. What are you seeing in terms of this micro-segmentation, AI SaaS play? How does this play out in healthcare over the next 3-4 years, Hiral?
Hiral Chandrana [10:08]
Yeah, like you said, BPK Technologies gave Veltris an additional micro-industry, particularly in the dental slash multi-unit — as we call it, multi-unit retail health — ecosystem. But there’s a lot more to do even just in dental or multi-unit health, because there itself you start with working with some of these multi-practice-based dental clinics or veterinary animal-health vet-care clinics, but there’s an entire ecosystem, like, for example, dental insurers or payers. It is a huge market. But then if you take a step back on healthcare, because that’s so wide and broad, as you know, even we’re focused on very specific segments. There’s obviously the macro elements of the big bill and worker shortage and nursing shortage, etc. But keeping that aside, the operational and administrative workflows are still broken, and I’m hoping that in our lifetime we can collectively make an impact on that. And I do think that vertical SaaS moving to vertical AI is now playing a meaningful role there. So that’s clearly one area. There’s a lot that’s said about putting the patient at the center, but if you look at all the activity, it’s still around payers and providers and all these bigger companies. I feel that’s one thing that will change in the next 2 to 3 years, because the personalized patient journeys, whether it’s home care or care delivery — we’re working with a lot of health tech platforms that have put patients truly at the center, and it’s really exciting to see how that could be a journey of a patient, from a dentist perspective or all the way from a pharmacy perspective. So that set of workflows on patient personalization is going to be huge. And the other thing that I think will happen, and we’re seeing it in parts as well, there are some disruptors in terms of platforms that are challenging what a UnitedHealth or what a CVS Pharmacy does in some of these areas, and that is going to be interesting. Because I do believe that there are more efficient ways of embedding automation and intelligence into the various workflows that exist today. I do like certain nuanced things. There’s an interesting company called — I don’t know if you’ve heard of — Hippocratic AI. They can work on patient safety as an example. Something so specific but doing so well, and so we’re really banking on some of these industry-specific use cases as we look at the future of Veltris’s growth in healthcare as well.
Saurabh Gupta [13:14]
Yeah, that’s fantastic, and I really like how you’re not just going after payers and providers, but really micro-segments, and I think that’s a big aspect of the Veltris differentiation, at least in my mind. And talking about healthcare, I’m wishing for the day where I can understand my EOB — I don’t know if that’ll happen in my lifetime or not, but the day I can explain my explanation of benefits, I’ll be a happy person. But one more — look, Veltris serves a number of small clients as well as large clients across industries: healthcare, media comms, industrial manufacturing clients. As you look at your client base, Hiral, where do you see the maximum urgency — and by urgency, I also mean budget — for AI-related initiatives?
Hiral Chandrana [14:19]
We want to really be one of those boutique specialist, differentiating orchestrators that truly bridges the hype-to-reality gap and resets the needle. So from that perspective, yes, we talked about healthcare earlier, and clearly there is funding and money in specific areas. So maybe I’ll pick a slightly different area. One of the areas which is hard to crack is the whole aspect of physical worlds and hard tech, right, when there is product, hardware, and software embedded together. Yes, there’s been Industry X.0 and edge and all these other things with digital twins, etc., but I truly think that some of those underrated use cases, while maybe slightly difficult to crack, on the smart manufacturing, smart factory floor side, will be truly ROI-generating. I’ve spoken to so many different upper-mid-market or even lower-enterprise type of clients who are right now just looking at predictive maintenance on the shop floor, and looking at just basic field-operations automation, etc. — small things which are still highly impactful. But when things like procurement or logistics can get combined with supply chains and factories, in this truly converging or connected world — because we have this thesis that smart, secure networking will actually power smart cities and smart factories, etc. In fact, earlier this month at our annual customer event, Velnova, this was one of those themes. So we believe that on the whole communications-manufacturing side, there are some interesting things, in addition to the healthcare use cases that we talked about.
Saurabh Gupta [16:22]
Yeah, no, I agree. So, Hiral, this has been a fascinating conversation, but before I let you go — we are almost about to end this year, and I’m pretty sure you’ll have some personal wishes for 2026. But what’s your one wish, if there was one wish that could come true from an industry perspective, in the industry that both of us live in — what would that be for 2026?
Hiral Chandrana [16:53]
Oh wow, that’s an interesting and tough one. There is so much going on that is starting to unravel in front of us. I would say that my big wish, not necessarily from an industry perspective, is that our next generation continues to truly have this continuous-learning mindset, because there is so much ahead of us. We talked about our lifetime and healthcare, etc., but there are so many difficult problems that are yet to be solved. So it’s not even about 2026, but what we do in 2026 — in terms of education, in terms of attitude, in terms of truly solving some problems — I think will set the stage for maybe even the next 2-3 decades to come. So that’s really what’s exciting.
Saurabh Gupta [17:52]
Oh, that’s fantastic. So you’re, as always, a glass-half-full kind of guy here. Well, this has been a fascinating conversation. I learn, I always do, whenever I speak with you, I learn something new. And Hiral, best of luck for the future of Veltris, our best wishes, and I hope people who are listening to our conversation will have gained some insights and wisdom from you, Hiral. So thanks a lot for joining us.
Hiral Chandrana [18:00]
No, always a pleasure, Saurabh. HFS continues to be doing some really disruptive, interesting thought leadership work, so continue to push that envelope. Looking forward to what’s to come for all of us.
Saurabh Gupta [18:40]
Super. All right. Thank you. Thank you.
